Search Results - EGA European Genome-Phenome Archive

The Genomic Map of Poland in Open Access

The main goal is to prepare and share WGS/WES of Polish population In this project NGS (next generation sequencing) was performed using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner was used. Shared BAM and BAM.BAI files Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Study EGAS50000000096

Center for Common Disease Genomics [CCDG] - Cardiovascular: TexGen

Cardiovascular disease (CVD), especially coronary heart disease, heart failure and cerebrovascular disease remain the leading causes of death in men and women across all race groups in the United States. Substantial evidence exists for genetic factors underlying CVD risk, and their discovery offers an opportunity to enhance understanding of disease mechanisms, to provide specific diagnostic and prognostic indicators, and to identify novel therapeutic targets. The Centers for Common Disease Genomics (CCDG) are a large-scale genome sequencing effort undertaken as a collaboration to identify rare risk and protective alleles for common chronic diseases, with a current focus on early onset heart disease, hemorrhagic stroke, and autism. In this study, whole genome sequencing (WGS) was performed in 6,146 individuals with any personal or family history of CVD from the TexGen study who were recruited from several institutions in the Texas Medical Center located in Houston, Texas. The participants included patients who were admitted with a variety of diagnoses including acute coronary syndromes, strokes, and transient ischemic attacks, or who underwent percutaneous coronary interventions or coronary artery bypass grafting (CABG) (Virani SS et al. Am J Cardiology 107:1504-1509, 2011). Patients in the TexGen cohort with a confirmed diagnosis of acute coronary syndrome (ACS) or CABG when discharged from the hospital between 2001-2008 were eligible for a follow-up study of recurrent myocardial infarction (Virani SS et al. Circulation J 76:950-956, 2012), while those presenting with ACS beginning in 2007 were recruited for an investigation of the role of depressive symptoms in the risk of major adverse coronary events (Sanner J et al. Biol Res Nurs 20:168-176, 2018). In addition, the initial criterion for enrollment in a third TexGen sub-study undertaken between 2007 and 2013 was the occurrence of premature acute myocardial infarction in men ≤ 50 years and women ≤ 55 years in order to establish a blood sample collection resource with the intention of localizing genes that contribute to disease risk. This definition was later expanded to include individuals with a clinical history of premature coronary heart disease such as CABG or percutaneous coronary interventions.

Study phs003010

AACR Project Genomics, Evidence, Neoplasia, Information, Exchange (GENIE)

AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international pancancer registry of real-world data assembled through data sharing between 19 leading international cancer centers with the goal of improving clinical decision-making. The registry leverages ongoing clinical sequencing efforts (CLIA/ISO-certified) at participating cancer centers by pooling their data to create a novel, open-access registry to serve as an evidence base for the entire cancer community. Genomic and baseline clinical data from more than 70,000 tumors is accessible through the efforts of our strategic and technical partners, Sage Bionetworks and cBioPortal. The consortium and its activities are driven by openness, transparency, and inclusion to ensure that the project output remains accessible to the global cancer research community and ultimately benefits patients.

Study phs001337

NEI CIDR Methylation Profiling of Primary Open Angle Glaucoma in GLAUGEN Samples

This is a case-control study of Primary Open Angle Glaucoma (POAG). POAG is a progressive optic neuropathy that eventually leads to blindness. More than 30 million people worldwide have Primary Open Angle Glaucoma (POAG), of which greater than 3 million are blind. Gene expression changes in the retina have been observed for POAG. Several recent studies, including the GLAUGEN (Glaucoma Gene Environment) initiative have used GWAS to identify correlative regions of the genome. Despite this, the genetic basis of Glaucoma is not well understood. Epigenetic variation may account for low heritability and environmental effects on human disease. Despite the significant advances being made in understanding the role of epigenetics in gene regulation in other fields, little is known about the relationship between DNA methylation patterns, retinal gene expression, and retinal disease. The goal of this study is to identify differentially methylated regions in the peripheral blood of patients with POAG. The case identification is as per the GLAUGEN description: Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. POAG and control samples come from Massachusetts Eye and Ear Infirmary (MEEI). These samples were collected and genotyped as part of the GLAUGEN study. From the MEEI, 50 patients were selected from POAG pedigrees, to include all the probands genotyped by CIDR and are currently undergoing exome sequencing, and to include additional genotyped probands who belong to pedigrees of sufficient size and structure that parent of origin effects could be evaluated. Additional individual-level phenotype and genotype data may be obtained through the authorized access portal of phs000308 (Geneva - Glaugen GWAS Study).

Study phs000461

A phase II trial of the aurora kinase A inhibitor alisertib for patients with castration resistant and neuroendocrine prostate cancer: efficacy and biomarker evaluation

Neuroendocrine prostate cancer (NEPC) is an aggressive variant of prostate cancer that may develop de novo or as a mechanism of treatment resistance. N-myc is capable of driving NEPC progression. Alisertib inhibits the interaction between N-myc and its stabilizing factor Aurora-A, inhibiting N-myc signaling, and suppressing tumor growth. In this single arm, multi-institutional open label phase 2 clinical trial of alisertib, sixty men were treated with alisertib 50mg twice daily for 7 days every 21-days. Eligibility included metastatic prostate cancer and at least one: small cell neuroendocrine morphology; ≥50% neuroendocrine marker expression; new liver metastases without PSA progression; elevated serum neuroendocrine markers. The primary endpoint was six-month radiographic progression free survival. Pre-treatment biopsies were evaluated by whole exome and RNA-seq.

Study phs001666

High-Risk Breast Cancer GWAS

The GWAS includes High Risk Women from the following epidemiological studies of breast cancer, comprising a total of 3,719 cases and 3,642 controls (cases/controls: MEC, 0/200; ABCFR, 326/418; FCCC, 56/3; BCFR-UT, 66/32; CNIO-BC, 87/92; GESBC, 65/0; LIFE, 164/0; MARIE, 41/105; MAYO, 208/210; MNYR, 293/409; MSKCC, 310/0; NC-BCFR, 234/233; OFBCR, 553/560; POSH, 377/0; HBOC, 47/47; BBCS, 612/1333; UPENN, 280/0 This study was funded by a grant CA165038 to Christopher Haiman (University of Southern California) and John Hopper (University of Melbourne) from the National Cancer Institute, National Institute of Health. The contributing studies: Multiethnic Cohort (MEC). This study was supported by grant UM1 CA164973 from the National Cancer Institute, National Institute of Health. Ontario Familial Breast Cancer Registry, the Ontario site of the Breast Cancer Family Registry Cohort (OFBCR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Utah Breast Cancer Family Registry (BCFR-UT). This study was supported by grant UM1 CA164920 from the National Cancer Institute. New York site of the Breast Cancer Family Registry (MNYR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Northern California site of the Breast Cancer Family Registry (NC-BCFR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Australian Breast Cancer Family Registry (ABCFR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Breast Cancer Study (CNIO-BC). This study has been partially funded by The Spanish Network on Rare Diseases (CIBERER) and the Spanish National Genotyping Center (CEGEN). Genetic Epidemiologic Study of Breast Cancer (GESBC). The GESBC was supported by the Deutsche Krebshilfe e. V. [70492] and German Cancer Research Center (DKFZ). Mammary Carcinoma Risk Factor Study (MARIE). This study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH). Funding for the POSH study was provided by Cancer Research UK (grant refs A7572, A11699, C22524), the Breast Cancer Campaign (grant number: 2013MayPR044) and from 2003-2006 by a grant from The Wessex Cancer Trust. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH). Funding for the POSH study was provided by Cancer Research UK (grant refs A7572, A11699, C22524), the Breast Cancer Campaign (grant number: 2013MayPR044) and from 2003-2006 by a grant from The Wessex Cancer Trust. Hereditary Breast and ovarian Cancer: Genetic and Molecular Studies (HBOC). This study was supported by National Cancer Institute grant CA58860 and The Lon V Smith Foundation: LVSF-44528. Mayo Clinic inherited breast and ovarian cancer study (MAYO). This study was supported by the Breast Cancer Research Foundation, NIH grants CA192393, CA176785, and an NIH CA116201 Specialized Program of Research Excellence (SPORE) in Breast Cancer. British Breast Cancer Study (BBCS); Mammographic oestrogens and growth factor study (MOG). The BBCS and the MOG study are funded by Cancer Research UK and Breakthrough Breast Cancer and acknowledge NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). Genotyping of non-BRCA1/2 mutation carriers (UPENN). The study is supported by the Basser Research Center at the University of Pennsylvania, Rooney Family Foundation, NIH grants CA176785 and CA192393, the Breast Cancer Research Foundation, the Susan G. Komen Foundation for the Cure and Macdonald Family Foundation. Clinical Significance of Germline BRCA Mutations (MSKCC). The study is supported by the Robert and Kate Niehaus Clinical Cancer Genetics Research Initiative, The Breast Cancer Research Foundation, and the Cancer Center Support Grant from the National Institute of Health, National Cancer Institute 5P30 CA08748-40. Women's Learning the Influence of Family and Environment (LIFE). This study was supported by grants CA17054 and CA74847 from the National Cancer Institute, National Institutes of Health, No. 4PB-0092 from the California Breast Cancer Research Program of the University of California. Philadelphia site of the Breast Cancer Family Registry at Fox Chase Cancer Center (FCCC). This study is supported by NIH grant CA164920.

Study phs000929

An atlas of the developing human fetal spine

The primitive streak emerges during the 14th day of human development and establishes dorsoventral and antero-posterior (craniocaudal) body axes. Segmentation along the craniocaudal axis is governed by Hox genes; four clusters of transcription factors whose 3’ to 5’ expression correlates with position along the axis. The precise utilisation of Hox genes in different cell types remains incompletely characterised in humans. In this study, we applied single-cell and spatial transcriptomics to contiguous regions of the human fetal spine between the 5th and 13th post-conception weeks. We built a detailed developmental atlas to examine the segmental expression of Hox genes across different cell types, observing that the Hox code was displayed by all anatomically fixed cell types along the craniocaudal axis. By contrast, mature derivatives of neural crest cells retained the anatomical Hox code of their origin within the crest, a pattern reproduced across neural crest derivatives in other human fetal organs. These findings indicate that scars of Hox gene expression persist in crest cells which may serve as barcodes of neural crest migration.

Dataset EGAD00001009801

Chromatin_Profiling_in_Twins

50 lymphoblastoid cell lines of adult female Twins which are part of the MuTHER study, processed with the FAIRE assay in order to generate maps of open chromatin.

Study EGAS00001000097

Spatial Dynamics of the Developing Human Heart

Heart development relies on a topologically defined interplay between diverse cardiac cells. We finely curated spatial and single-cell measurements with high-resolution imaging-based transcriptomics validation to explore spatial dynamics during early human cardiogenesis. Analyzing almost 80,000 individual cells and 70,000 spatially barcoded tissue regions between the 5.5th and 14th postconceptional weeks, we identified 31 coarse- and 72 fine-grained cell states and mapped them to highly resolved cardiac cellular niches. We provide novel insight into the development of the cardiac pacemaker-conduction system, heart valves, and atrial septum, and decipher heterogeneity of the hitherto elusive cardiac fibroblast population. Furthermore, we describe the formation of the cardiac autonomic innervation and present the first spatial account of chromaffin cells in the fetal human heart. Our study, supported by an open-access, spatially centric interactive viewer, delineates the cellular and molecular architecture of the developing heart, offering links to genetic causes of heart disease.

Study EGAS50000001122

Spatial Dynamics of the Developing Heart (single-cell)

Heart development relies on a topologically defined interplay between diverse cardiac cells. We finely curated spatial and single-cell measurements with high-resolution imaging-based transcriptomics validation to explore spatial dynamics during early human cardiogenesis. Analyzing almost 80,000 individual cells and 70,000 spatially barcoded tissue regions between the 5.5th and 14th postconceptional weeks, we identified 31 coarse- and 72 fine-grained cell states and mapped them to highly resolved cardiac cellular niches. We provide novel insight into the development of the cardiac pacemaker-conduction system, heart valves, and atrial septum, and decipher heterogeneity of the hitherto elusive cardiac fibroblast population. Furthermore, we describe the formation of the cardiac autonomic innervation and present the first spatial account of chromaffin cells in the fetal human heart. Our study, supported by an open-access, spatially centric interactive viewer, delineates the cellular and molecular architecture of the developing heart, offering links to genetic causes of heart disease.

Study EGAS50000001029

MARS-seq dataset of five obese human subjects and a lean human subject

Biopsies from visceral adipose tissue from the omental depot (OAT) were obtained from five obese individuals and one lean donor with participant informed consent obtained after the nature and possible consequences of the studies were explained under protocols approved by the Institutional Review Boards of the Perelman School of Medicine at the University of Pennsylvania, the Children’s Hospital of Philadelphia, or the Tel Aviv Sourasky Medical Center. The obese donors underwent bariatric surgery, the lean donor underwent cholecystectomy. OAT samples were placed in 1 mL of DMEM, and finely minced under sterile conditions before digestion in 50 mL of DMEM with 3 mg/1 mL collagenase IV (Gibco). Samples were incubated at 37°C in a rotating oven for 20-60 min. Adipocyte and stromal vascular fractions (SVF) were separated by centrifugation, and red blood cells (RBCs) were removed from the SVF by histopaque gradient (Sigma). Single-cell RNA-sequencing libraries were prepared using the MARS-seq pipeline, and sequenced on the MiSeq 500 or HiSeq 2500 Sequencing System (Illumina).

Dataset EGAD00001005100

The genetic structure of Norway

The aim of the present study was to describe the genetic structure of the Norwegian population using genotypes from 6369 unrelated individuals with detailed information about places of residence. Using standard single marker- and haplotype-based approaches, we report evidence of two regions with distinctive patterns of genetic variation, one in the far northeast, and another in the south of Norway, as indicated by fixation indices, haplotype sharing, homozygosity and effective population size. We detect and quantify a component of Uralic Sami ancestry that is enriched in the North. On a finer scale, we find that rates of migration have been affected by topography like mountain ridges. In the broader Scandinavian context, we detect elevated relatedness between the mid- and northern border areas towards Sweden. The main finding of this study is that despite Norway’s long maritime history and as a former Danish territory, the region closest to mainland Europe in the south appears to have been the most isolated region in Norway, highlighting the open sea as a barrier to gene flow into Norway.

Study EGAS00001004826

The Genomic Map of Poland in Open Access

The main goal is to prepare and share WGS/WES of Polish population In this project NGS (next generation sequencing) was performed using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner was used. Shared BAM and BAM.BAI files Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

Study EGAS50000000091

dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

The National Heart, Lung, and Blood Institute (NHLBI) Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research has concluded. The NHLBI will continue to make this collection of data available to the research community.Past information regarding the Data Collection for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research is below.The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is inviting novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and "other omics" data for more than one-hundred thousand individuals. To provide challenge participants with streamlined access to data across NHLBI's numerous studies containing heart failure data, the NHLBI has created this dbGaP study collection. Data access for this collection is controlled by NHLBI's Data Access Committee. Challenge participants are required to follow the use restrictions and acknowledgement instructions from the original dataset(s). Please note that the data in this collection are not harmonized across studies or otherwise altered from the original study. The NHLBI Big Data Analysis Challenge: Heart Failure Data Collection contains all NHLBI studies currently in dbGaP that contain data that may be relevant to research on heart failure. The studies in this collection are approved for General Research Use (GRU), Health/Medical/Biomedical Use (HMB), or Disease-Specific Use (DS) that permits research on heart failure. These studies span a variety of study designs, inclusion and exclusion criteria, sample sizes, and provide a wide breadth and depth of phenotype data on study participants. The available genomic data in these studies also varies, including genotyping arrays, sequencing (targeted, exome, whole genome), and additional -omic data (e.g., RNA or metabolite profiles). Please refer to each study's individual accession page to learn more about how study data were collected. Challenge participants are reminded that in addition to dbGaP, NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) contains other studies that have collected data relevant to heart failure and may wish to utilize BioLINCC data in the development of their Solution. Please refer to the individual accession page for each study in this collection to learn more about the history of each study.

Study phs001991

International Verapamil SR/Trandolapril [INVEST] Genes Study

INternational VErapamil SR-Trandolapril STudy (INVEST) was a prospective, multicenter, randomized, open-label, parallel-clinical trial that evaluated blood pressure response and adverse outcomes in patients randomized to either an atenolol-based or a verapamil SR-based hypertension treatment strategy in 22,576 patients with documented coronary artery disease and hypertension (PMID: 9809930,14657064). Hydrochlorothiazide and trandolapril were added as needed to achieve BP control or end organ protection in a protocol-defined manner. Briefly, the protocol required patients to be followed up at bassline, 6, 12, 18 and 24 weeks and then every 6 months thereafter until 2 years after the last patient was enrolled. At each visit, patients had BP and heart rate measured, clinical assessment performed, and additional antihypertensive medications added as needed to meet JNC VI blood pressure goals. The primary outcome was the first occurrence of all-cause death, nonfatal myocardial infarction (MI), or nonfatal stroke (clinicaltrials.gov identifier: NCT00133692). The genetic substudy of INVEST, INVEST-GENES, collected genomic DNA samples from 5,979 INVEST study participants. INVEST-GENES samples were genotyped on the Illumina OmniExpressExome GWAS chip. This data release includes 1529 samples that passed quality control including 657 whites, 537 Hispanics and 155 blacks. Two case-control subsets were created: one for the primary outcome of all-cause death, nonfatal MI or nonfatal stroke; the other one is for new-onset diabetes. Resistant hypertension was also evaluated in 1349 participants based on the medication use and blood pressure measurements at the visit prior to experiencing study outcomes or censoring (PMID:30237584).

Study phs002319

Metastatic Adult Pancreatoblastoma: Multimodal Treatment and Molecular Characterization of a Very Rare Disease (NCT MASTER)

Pancreatoblastoma is a rare malignant tumor that occurs predominantly in children. We identified four adult patients with metastasizing pancreatoblastoma at a high-volume German university cancer center which were treated with multimodal therapies between 2013 and 2018. In three cases, we performed a comprehensive molecular analysis that included whole-genome sequencing (WGS) or whole-exome sequencing (WES); transcriptome sequencing was performed in two cases, respectively. Subsequent recommendations of molecularly stratified treatment options were discussed within a dedicated molecular tumor board (MTB) embedded in a precision oncology program (NCT MASTER).

Study EGAS00001004157

Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

To elucidate the regulation of gene expression in immune cell subsets and its contribution to autoimmune diseases, Whole blood and various immune cell subsets from 119 Systemic Lupus Erythematosus (SLE), 65 Dermatomyositis & Polymyositis, 67 Systemic Sclerosis, 19 Mixed Connective Tissue Disease, 18 Sjogren's syndrome, 24 Rheumatoid Arthritis, 23 Behcet's disease, 18 Adult Onset Still��s Disease, 25 ANCA-associated Vasculitis, 16 Takayasu��s Arteritis and 141 healthy controls (C) were collected (Naive_CD4, Mem_CD4, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, Th1, Th2, Th17, Tfh, NK, Naive_CD8, Mem_CD8, EM_CD8, CM_CD8, TEMRA_CD8, Naive_B, USM_B, SM_B, DN_B, Plasmablast, CL_Mono (or CD16n_Mono), CD16p_Mono, Int_Mono, NC_Mono, mDC, pDC, LDG, Neu). Whole genome sequencing was performed with whole blood samples. RNA-seq was performed with each immune cell subset samples. After filtering and normalization of the gene expression data, eQTL analysis was performed in each immune cell type. 15 immune cell subsets ATAC-seq was also performed in 8 SLE and HCs, each.

Study JGAS000220

Next Generation Mendelian Genetics: Auriculocondylar syndrome (ACS)

This project is part of an ongoing project to identify the molecular genetic basis of rare craniofacial disorders. This specific project involved the collection of DNA samples from four probands with severe manifestations of auriculocondylar syndrome and their parents. Detailed clinical phenotypic data is available on each proband. The sole purpose of this research is to identify the molecular cause(s) of auriculochondylar syndrome.

Study phs000437

Investigating_low_frequency_variants_in_CAD_MI_cases__controls_and_pedigrees_using_whole_exome_sequencing_and_custom_pulldowns

The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

Study EGAS00001000043

Investigating_low_frequency_variants_in_CAD_MI_cases__controls_and_pedigrees_using_whole_exome_sequencing_and_custom_pulldowns

The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

Study EGAS00001000050

Cardiogenics_re_sequencing

The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

Study EGAS00001000079

Metadata Public API

Metadata Rest Endpoints Common Aspects Functionality Identifiers Requests and Responses Request Response Querying Querying by Object Cross-Querying by Object Common Aspects Functionality The Metadata REST API allows EGA users to request metadata from the EGA. Using this api you will be able to obtain the publicly available information from EGA study, sample, experiment, run, analysis, policy, dac and dataset. The API also allows for objects to be cross-referenced in order to obtain for example all the datasets linked to a dac. Identifiers EGA objects can be identified by their unique accession. These are ID's displayed everywhere, shared among all EGA locations and specific for each data type (More information on the list below) EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID Server Request and Response Request All the endpoints implement these two HTTP methods, GET and HEAD. Moreover, there is an authentication layer that allows to disclose the private information about each object if the user runs the endpoint with their token and has permissions to the related dataset. HTTP Method Description GET Returns the objects and their public information (including private information if the user has permissions) HEAD Returns the count of objects to be returned Response API responses are diverse but they always return a status call. Below you have a summary on what these codes mean and some tips that can help you troubleshooting them: HTTP Status Code Description Resolution 200 OK No error handling necessary 206 Partial Content Expected status code when paginating the results. No error handling necessary 400 BAD REQUEST Request incorrectly formulated 401 UNAUTHORISED/FORBIDDEN You do not have permissions over the object you are trying to access. / The authorised user is not permitted to make the given request. 404 NOT FOUND The object/resource you are trying to access does not exist. 500 INTERNAL SERVER ERROR This is a server-side error, try later. If the issue persists, contact the Heldpesk. Querying Querying by Object In the below documentation, worked examples can be found on how to use the API, to query about each unique EGA object. https://metadata.ega-archive.org/analyses/{id} https://metadata.ega-archive.org/dacs/{id} https://metadata.ega-archive.org/datasets/{id} https://metadata.ega-archive.org/runs/{id} https://metadata.ega-archive.org/samples/{id} https://metadata.ega-archive.org/studies/{id} Worked example for the EGA data access committee(DAC) EGAC00001000514 https://metadata.ega-archive.org/dacs/EGAC00001000514 Points to notice Please, be advised that all EGA objects can be queried by using the same endpoint. For example: https://metadata.ega-archive.org/datasets Returns all the datasets registered at the EGA. https://metadata.ega-archive.org/datasets?limit=5&offset=15 Returns 5 results skipping the initial 15 results. Cross-Querying by Object The EGA REST API Metadata also allows for the crossquerying of public metadata. For example, should I want to query the datasets included in the ICGC DAC: https://metadata.ega-archive.org/dacs/EGAC00001000010/datasets Below, you can find worked examples on how to perform the call to the API. https://metadata.ega-archive.org/datasets/EGAD00001000645/analyses https://metadata.ega-archive.org/datasetsEGAD00001000645/files https://metadata.ega-archive.org/datasets/EGAD00001000620/runs https://metadata.ega-archive.org/datasets/EGAD00001000620/samples https://metadata.ega-archive.org/samples/EGAN00001092114/datasets https://metadata.ega-archive.org/files/EGAF00000056146/dacs https://metadata.ega-archive.org/files/EGAF00000056146/datasets https://metadata.ega-archive.org/files/EGAF00000056146/studies There are more endpoints included in this category. Please, find all the possibilities (green tick) in the table below. Table The table displays in a ordered fashion the objects that can be crossreferenced using the metadata API. BY Analysis Dac Dataset Experiment Policy Run Sample Study File Analysis ✔ ✔ Dac ✔ ✔ Dataset ✔ ✔ ✔ ✔ Experiment ✔ ✔ ✔ ✔ Policy ✔ Run ✔ ✔ ✔ Sample ✔ ✔* ✔ Study ✔ ✔ ✔ ✔ ✔ ✔* File ✔ *: These cross queries do not include data from Array-File submissions. Check out the SPEC

Documentation discovery/metadata/public-metadata-api

National Eye Institute (NEI) Exfoliation Genotyping Study

The overall goal of our research is to elucidate the pathogenesis of exfoliation syndrome and the associated glaucoma, making it possible to implement effective screening and prevention strategies and to develop novel therapies. Cases genotyped for this project are from the Nurses Health Study (NHS), the Health Professionals Follow-up Study (HPFS), the Women's Genome Health Study (WGHS), the Massachusetts Eye and Ear Infirmary (MEEI), Mayo Clinic, the University of Iowa, the University of Miami and Duke University Medical Center. Exfoliation syndrome (XFS) is a common condition that is a major risk factor for high-tension open-angle glaucoma, pre-mature cataract formation, and increased risk of complications during cataract surgery. Previous studies suggest that exfoliation syndrome and the related glaucoma (XFG) are genetically complex, and one gene, LOXL1, has been identified as a major genetic risk factor. LOXL1 variants are found in up to 98% of affected patients; however, these same variants are also present in up to 80% of unaffected individuals, indicating that additional genetic and/or environmental factors are necessary for disease development. Samples genotyped for this study are a case set (1,096 samples) and 24 pedigrees (98 samples). Controls for association analyses are selected from the NEIGHBORHOOD study.

Study phs001053

Multiple migrations to the Philippines during the last 50,000 years

A key link to understand human history in Island Southeast Asia is the Philippine archipelago and its poorly investigated genetic diversity. We collected and analyzed the most comprehensive set of population-genomic data for the Philippines, 1028 individuals covering 115 indigenous communities. We demonstrate that the Philippines were populated by at least five waves of human migration. The Cordillerans migrated into the Philippines prior to the arrival of rice agriculture, where some remain to be the least admixed East Asians carrying an ancestry shared by all Austronesian-speaking populations; thereby challenging an exclusive Out-of-Taiwan model of joint farming-language-people dispersal. Altogether, our findings portray Philippines as a crucial gateway, with a multilayered history, that ultimately changed the genetic landscape of the Asia-Pacific region.

Study EGAS00001005083

99 Cases of Small Cell Lung Cancer Study

Small cell lung cancer (SCLC) is an aggressive disease with poor survival. A few sequencing studies performed on limited number of samples have revealed potential disease-driving genes in SCLC, however, much still remains unknown, particularly in the Asian patient population. Here we conducted whole exome sequencing (WES) and transcriptomic sequencing of primary tumors from 99 Chinese SCLC patients. Dysregulation of tumor suppressor genes TP53 and RB1 was observed in 82% and 62% of SCLC patients, respectively, and more than half of the SCLC patients (62%) harbored TP53 and RB1 mutation and/or copy number loss. Additionally, Serine/Arginine Splicing Factor 1 (SRSF1) DNA copy number gain and mRNA over-expression was strongly associated with poor survival using both discovery and validation patient cohorts. Functional studies in vitro and in vivo demonstrate that SRSF1 is important for tumorigenicity of SCLC and may play a key role in DNA repair and chemo-sensitivity. These results strongly support SRSF1 as a prognostic biomarker in SCLC and provide a rationale for personalized therapy in SCLC. The manuscript has been accepted by Plos Genetics.

Study phs001083

Clinical Outcomes of 344 Diffuse Large B-Cell Lymphoma patients

This study examines clinical outcomes of patients with diffuse large B-cell lymphoma (DLBCL). We analyzed a cohort of 344 patients from the German High-Grade Non-Hodgkin Lymphoma Study Group (DSHNHL). To protect patient confidentiality, all samples were pseudonymized. The dataset includes clinical key characteristics, such as patient age at diagnosis, sex, ECOG performance status, disease stage, serum lactate dehydrogenase levels, bulky disease, bone marrow involvement, extranodal involvement, and B-symptoms. We used these data alongside proteomic and transcriptomic profiles to explore relationships between clinical features and molecular signatures, reconstructing regulatory networks. Insights from this integrative analysis aim to identify key pathological drivers and biomarkers of DLBCL progression, ultimately informing improved risk stratification and targeted therapeutic approaches.

Study EGAS50000001054

CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR).

Study phs000930

HeLa Cell Genome Sequencing Studies

HeLa is a human epithelial adenocarcinoma cell line that was derived from biopsy specimens of a 31-year old patient named Henrietta Lacks who was being treated for cervical cancer at The Johns Hopkins University Hospital in 1951. The specimens were obtained without her knowledge or consent just before her death in 1951. HeLa is the oldest and most widely used human cell line and has been an extraordinarily important resource for researchers throughout the world. HeLa cells have served as a standard for understanding many fundamental biological processes, such as testing the polio vaccine, establishing basic techniques for cloning and in vitro fertilization, identifying the cause of cervical cancer (HPV), and advancing the development of anti-cancer drugs.This study contains all authorized whole genome sequence data of the HeLa cell line from datasets currently in dbGaP. These data have been approved for health, medical, and/or biomedical research purposes. Access to these data can be granted for one year. Accessible data will include the studies listed on this page and any additional authorized datasets that become available during this one-year period. The HeLa Genome Data Access Working Group of the Advisory Committee to the Director (ACD) will review requests from the research community for access to these datasets and assess whether the requests align with the terms of use defined in the HeLa Genome Data Use Agreement. The Working Group's findings will be reported to the ACD, and the ACD will make recommendations to the NIH Director about whether a request should be approved or disapproved. The NIH Director will decide whether access to the data will be granted.

Study phs000640

eIMPACT Trial: Modernized Collaborative Care to Reduce the Excess CVD Risk of Older Depressed Patients

Cardiovascular disease (CVD) is the #1 killer of American men and women, and its economic burden is substantial and on the rise. Adults with depression are at elevated risk of CVD events and poor CVD prognosis. Unfortunately, past clinical trials of depression treatments have not observed the anticipated cardiovascular benefits. A novel explanation for these null results is that the depression interventions in these trials, which all involved patients with preexisting CVD, were delivered too late in the natural history of CVD. Accordingly, the objective of this single-center, parallel-group, assessor-blinded randomized controlled trial was to determine whether successful depression treatment before, versus after, the onset of clinical CVD reduces CVD risk in depression. Primary care patients with depression and elevated CVD risk from a safety net healthcare system (N = 216, Mage = 59 years, 78% female, 50% Black, 46% with income <$10,000/year) were randomized 1:1 to 12 months of the eIMPACT intervention (a modernized collaborative stepped care program involving internet cognitive-behavioral therapy [CBT], telephonic CBT, and/or select antidepressants) or usual primary care for depression (primary care providers supported by embedded behavioral health clinicians and psychiatrists). The primary outcome was endothelial dysfunction (brachial flow-mediated dilation) at 12 months, and the secondary outcomes were self-reported depressive symptoms (Hopkins Symptom Checklist-20), autonomic dysfunction (high-frequency heart rate variability), systemic inflammation (interleukin-6 and high-sensitivity C-reactive protein), and platelet activation (β-thromboglobulin and platelet factor 4) at 12 months. The central hypothesis was that the eIMPACT intervention would improve endothelial dysfunction in depressed adults by decreasing depressive symptoms, autonomic dysfunction, systemic inflammation, and platelet activation. Primary results are posted to ClinicalTrials.gov at NCT02458690. The de-identified limited dataset available on BDC consists of only the individual phenotypic data needed to confirm this trial’s primary results – i.e., randomization status, primary and secondary outcome variables, and participant characteristics utilized in the hypothesis-testing models (age, sex, race, education, income, and systolic blood pressure). We also provide the SAS code to replicate the results of the hypothesis-testing models reported in Table 4 and Supplemental Tables 1-3 in the main outcomes paper (#2 in Selected Publications). Of note, the user will need to specify the file path for the dataset to run the SAS code. Instructions for requesting individual-level data are available on BDC at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BDC. For questions about availability, you may contact the BDC team at https://biodatacatalyst.nhlbi.nih.gov/contact.

Study phs003283

Distribution of data using Live Distribution

Live Distribution Welcome to the documentation for using the Live Distribution feature for distributing data files securely through the EGA platform. This guide will walk you through the process of downloading encrypted files and decrypting them using Crypt4GH. Please follow the steps below to ensure a smooth experience. Before Downloading Create an EGA user. Make sure that you have the permissions to download the dataset of interest. In case you don’t have access, request access to the dataset. Add your Crypt4GH-compatible public key to your EGA account. Please allow a few hours for your public key to be synced with your profile. Afterwards, you will be able to connect to your EGA outbox using the SFTP protocol. Download Graphical User Interface (GUI) You can use any GUI that supports SFTP connections, such as FileZilla, an open-source FTP client. For Filezilla as your GUI, follow these steps to download files: Open FileZilla and access Site Manager (File > Site Manager). Create a new connection with the following settings (Figure 1): Protocol: SFTP - SSH File Transfer Protocol Host: __EGA_OUTBOX_DOMAIN__ Logon Type: Key file User: your EGA username Key file: path/to/your/private_key Figure 1: Process of establishing a new connection to __EGA_OUTBOX_DOMAIN__ using a key file as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the EGA outbox, ensuring seamless data transfers. Click Connect to access your Outbox. This folder serves as your storage space within the EGA cloud, containing files accessible for download in a secure way. Browse the remote directory on the right side of the FileZilla screen. Select the files you wish to download, right-click, and choose Download (Figure 2). Figure 2: Step-by-step process of manually downñoad files from __EGA_OUTBOX_DOMAIN__ using FileZilla, with FileZilla version 3.52.2 operating on IOS v11.2.3. The figure demonstrates how users can downñoad data from the EGA outbox to their local storage by following the depicted steps SFTP command line You can also use the SFTP command line to securely download files from the EGA Outbox. Using SFTP command line client in Linux/Unix Open a terminal window Enter the following command to connect: sftp username@hostname Enter your EGA password To see a list of available sftp commands type help sftp> put – Upload file sftp> get – Download file sftp> cd path – Change remote directory to ‘path’ sftp> pwd – Display remote working directory sftp> lcd path – Change the local directory to ‘path’ sftp> lpwd – Display local working directory sftp> ls – Display the contents of the remote working directory sftp> lls – Display the contents of the local working directory Type get command to download files. For example: get encrypted_file.c4gh Use the bye command to close the connection (SFTP session). Convenient SSH settings Include the following settings in your SSH config file, located in ~/.ssh/config Host __EGA_OUTBOX_DOMAIN__ EGA-outbox hostname __EGA_OUTBOX_DOMAIN__ User username IdentityFile path/to/the/private/key Replace username and path/to/the/private/key with the appropriate settings, and you will be able to connect to the __EGA_OUTBOX_DOMAIN__ simply using sftp EGA-outbox. How to decrypt Files archived at the EGA are encrypted based on Crypt4GH. Hence, to decrypt the files you need to install Crypt4GH. You can install a python implementation of it, with pip install crypt4gh or directly from the Github repository pip install git+https://github.com/EGA-archive/crypt4gh.git After installing Crypt4GH, decrypt files using the following command: crypt4gh decrypt --sk /path/private/key < encrypted_file.c4gh > decrypted_filename The command reads the encrypted file from stdin (with <) and output the decrypted version to stdout (with >). Replace encrypted_file.c4gh and decrypted_filename with the appropriate filenames but make sure to not use the same filename for both reading and writing because your SHELL would then truncate both files before you even read or write. Frequently Asked Questions What username should I use to log in to my outbox? The authentication process for logging in to the EGA website, as well as accessing your inbox and outbox, requires the use of your username, not your email address. Therefore, if you registered a username different from your email address when creating your EGA account, you must use that username to log in. If you have forgotten your registered username, please, contact our Helpdesk team for assistance. I see that some files in my dataset have 'unavailable' as extension. What should I do? Within your Outbox, you'll find a list of all the datasets available for download. Occasionally, certain files may be marked as "unavailable". These unavailable files can be identified by the "unavailable" extension added to their filenames (e.g. filename.fastq.gz.unavailable.c4gh). If you encounter an unavailable file that you need, please reach out to our Helpdesk. We'll promptly work on making the file accessible for download as soon as possible. Specific to using keys Can I access one EGA account from different devices? Yes, you can access your account from different devices by linking several public keys to your EGA account. Each device can generate a unique public-private key pair, and the corresponding public keys can be linked to the same account. This way, you can use different public keys on different devices and still have access to the same account and data. I have several keys and I don't remember which one is which When generating SSH keys, it's a good practice to add a comment using the -C flag. This will allow you to add a descriptive tag to your key, making it easier to identify later on. Here's an example command that generates an SSH key with a comment: ssh-keygen -t ed25519 -C work-pass In this example, we're generating an ed25519 SSH key with the comment work-pass. Once you have multiple keys with different comments, you can use the comments to easily identify each key. To view the comments for your existing SSH keys, you can use the following command: ssh-keygen -l -f /path/to/key This will display the key fingerprint and the associated comment. By checking the comments, you should be able to identify which key is which. What if I can't find my SSH keys for uploading files with a key file, and how can I use new keys? If you can't find your SSH keys, don't worry - you can make new ones. To do this, open your terminal or command prompt and type a command to make a new SSH key. You can pick a name for the key, and choose a password to keep it safe. After making the key, you can add the new key to your account or server where you want to upload files using the key file. This usually involves copying and pasting the key's "public" (e.g. file.pub) part to the right place. If you lose track of the key again, just make a new one and add it again. Keep in mind that SSH keys belong to you and your computer, so if you switch computers or accounts, you'll need to make new keys. I don't want to type the passphrase every time I use the key. What can I do? You can use an ssh-agent to avoid typing the passphrase every time you use the key. An ssh-agent is a program that stores your private keys in memory and provides them to ssh when needed. You can add your key to the ssh-agent using the command ssh-add followed by the path to your key file.Here's an example of the steps to follow: Open a terminal window.Start the ssh-agent by typing the command eval $(ssh-agent).Add your key to the ssh-agent by typing the command ssh-add [key filepath]. For instance, if your key file is located in the home directory with the name mykey, the command will look like this: ssh-add ~/mykey After adding your, key to the ssh-agent, you should be able to use ssh without having to enter your passphrase every time. Can I use my password for authentication (without my private key)? If you prefer to use your username and password for authentication instead of your private key, you can still do so. When using a Graphical User Interface (GUI) such as FileZilla, you can select Ask for password as your Logon Type (Figure 3). This option will prompt you to enter your password when you click Connect, instead of using your private key. Figure 3: This option will prompt you to enter your password when you click "Connect", instead of using your private key. Figure 3: Process of establishing a new connection to __EGA_OUTBOX_DOMAIN__ using your password as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the inbox, ensuring seamless data transfers. It's worth noting that using a password for authentication can be less secure than using an SSH key, as passwords can be more easily compromised through various means. However, if you choose to use your password for authentication, selecting "Ask for password" as your Logon Type is a good way to do so securely via a GUI. Why is it better to use my key and not my password? SSH keys for authentication is generally considered to be more secure and convenient than using passwords. SSH keys are more difficult to crack than passwords, and they can be restricted to specific users and machines, giving you more control over access. Once you set up your SSH keys, you can use them to authenticate quickly and easily, without having to enter a password every time. This makes automation of tasks, such as uploading encrypted files, much simpler. Additionally, SSH keys provide better logging, allowing you to keep track of who is accessing your systems and when. All in all, using SSH keys is a good practice for improving security and convenience in your authentication process.

Documentation access/download/files/live-outbox

Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - Ribo-Seq

This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

Dataset EGAD00001011193

Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - Genome-Wide Association Study Meta-Analysis

Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (http://epi.grants.cancer.gov/gameon/). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL). To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, DRIVE investigators performed a meta-analysis of eleven genome-wide association studies of breast cancer: The Australian Breast Cancer Family Study (ABCFS), the British Breast Cancer Study (BBCS), the Breast and Prostate Cancer Cohort Consortium (BPC3), the Breast Cancer Family Registries (BCFR), the Dutch Familial Bilateral Breast Cancer Study (DFBBCS), German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC), the Helsinki breast cancer family Study (HEBCS), the Mammary Carcinoma Risk factor Investigation (MARIE), the Singapore and Sweden Breast Cancer Study (SASBAC), the Triple Negative Breast Cancer Study (TNBC), and the UK2 GWAS. These studies comprised a total of 16,062 cases and 46,157 controls. Imputation to the 1,000 Genomes Project Phase 1 v3 ALL reference panel was performed by study, and summary statistics from each study were combined using fixed-effect meta analysis.

Study phs001263

COVID-19 ACTIV-4 ACUTE: A Multicenter, Adaptive, Randomized Controlled Platform Trial of the Safety and Efficacy of Antithrombotic Strategies in Hospitalized Adults with COVID-19 (ACTIV4A)

This is a randomized, open label, adaptive platform trial to compare the effectiveness of antithrombotic strategies for prevention of adverse outcomes in COVID-19 positive inpatients.

Study phs002694

INDIA

We collected PBMCs from 10 Indian and 10 Dutch individuals before BCG vaccination and 10-12 post-vaccination. We assessed the open chromatin profiles under baseline conditions, and the transcriptomic profiles upon stimulation with Influenza and SARS-CoV-2.

Study EGAS00001006417

DEEP-IHEC-release-2017

Raw data files for the German Epigenome Project (DEEP), IHEC/EpiRR submission of 2017. metadata available at: http://deep.dkfz.de/#/experiments

Dataset EGAD00001003974

HipSci - Human Induced Pluripotent Stem Cells Initiative

Human induced pluripotent stem (iPS) cells can be generated from adult tissues and differentiated into a range of specific cell types (Yamanaka and Blau, 2010). They therefore provide unprecedented opportunities for investigating disease mechanisms and understanding the phenotypic consequences of genetic variation within the normal population. HipSci brings together diverse constitutents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. Between 2013 and 2016 we aim to generate iPS cells from over 500 healthy individuals and 500 individuals with genetic disease. We will then use these cells to discover how genomic variation impacts on cellular phenotype and identify new disease mechanisms. Strong links with NHS investigators will ensure that studies on the disease-associated cell lines will be linked to extensive clinical information. Further key features of the project are an open access model of data sharing; engagement of the wider clinical genetics community in selecting patient samples; and provision of dedicated laboratory space for collaborative cell phenotyping and differentiation.

Study EGAS00001001465

Pancreatic islets PISA RNA-seq samples

GWAS have identified more than 700 genetic signals associated with type 2 diabetes (T2D). To gain insight into the underlying molecular mechanisms, we created the Translational human pancreatic Islet Genotype tissue-Expression Resource (TIGER), aggregating >500 human islet RNA-seq and genotyping datasets. We imputed genotypes using 4 reference panels and meta-analyzed cohorts to improve coverage of expression quantitative trait loci (eQTL) and developed a method to combine allele-specific expression across samples (cASE). We identified >1 million islet eQTLs (56% novel), of which 53 colocalize with T2D signals (60% novel). Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identified 8 novel cASE colocalizations, among which an SLC30A8 T2D associated variant. We make all the data available through the open-access TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translate this into therapeutic insight and precision medicine for T2D.

Study EGAS00001005535

NEI CIDR Methylation Profiling of Primary Open Angle Glaucoma in NEIGHBOR Samples

This is a case-control study of Primary Open Angle Glaucoma (POAG). POAG is a progressive optic neuropathy that eventually leads to blindness. More than 30 million people worldwide have Primary Open Angle Glaucoma (POAG), of which greater than 3 million are blind. Gene expression changes in the retina have been observed for POAG. Several recent studies, including the NEIGHBOR consortium (NEI Glaucoma Human genetic collaboration) have used GWAS to identify correlative regions of the genome. Despite this, the genetic basis of Glaucoma is not well understood. Epigenetic variation may account for low heritability and environmental effects on human disease. Despite the significant advances being made in understanding the role of epigenetics in gene regulation in other fields, little is known about the relationship between DNA methylation patterns, retinal gene expression, and retinal disease. The goal of this study is to identify differentially methylated regions in the peripheral blood of patients with POAG. The case identification is as per the NEIGHBOR description: Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. POAG and control samples come from two sources: Duke University and Massachusetts Eye and Ear Infirmary (MEEI). These samples were collected and genotyped as part of the NEIGHBOR study. From the 219 POAG cases contributed to NEIGHBOR by Duke, 75 samples were selected for exome sequencing by Dr. Terry Gaasterland (UCSD) as part of an ARRA grant. These samples were selected to mirror the distribution of the entire set of Duke patients for variables such as age, cup-to-disc ratio, CCT, and IOP. From these 75 patients, 43 were selected for our study and an additional seven patients chosen at random, for a total 50 patients from Duke. From the 219 Duke controls, 50 were selected to match the age (at the time of blood draw) and sex of the 50 Duke POAG patients. From the NEIGHBOR control samples from MEEI, 27 were selected who best matched the age (at blood draw), time since sample collection and sex of the POAG probands from GLAUGEN. Additional individual-level phenotype and genotype data may be obtained through the authorized access portal of phs000238 (Neighbor - Glaucoma GWAS Study).

Study phs000458

Parkinson's Disease Cognitive Genetics Consortium (PDCGC) Stage I, NeuroX Dataset

Cognitive impairment is a common and disabling problem in Parkinson's disease (PD). Identification of genetic variants that influence the presence or severity of cognitive deficits in PD might provide a clearer understanding of the pathophysiology underlying this important nonmotor feature. We are presently undertaking a large-scale, two-stage study designed to identify genetic risk factors for cognitive impairment in PD. The study population is divided into a discovery (Stage I) and a validation (Stage II) sample of patients enrolled in the PD Cognitive Genetics Consortium (PDCGC). Each patient has undergone a detailed neurological evaluation and cognitive testing. Clinical and genetic data for the project are stored and managed at the Coordinating Center at the University of Washington and VA Puget Sound Health Care System in Seattle. Stage I of the project is now complete; 1,219 PD patients were genotyped for 249,336 variants using the NeuroX array. Participants underwent assessments of learning and memory (Hopkins Verbal Learning Test-Revised [HVLT-R]), working memory/executive function (Letter-Number Sequencing and Trail Making Test [TMT] A and B), language processing (semantic and phonemic verbal fluency), visuospatial abilities (Benton Judgment of Line Orientation [JoLO]), and global cognitive function (Montreal Cognitive Assessment). We excluded individuals who were of non-European ancestry, failed genotyping, were missing data for one or more covariates, were related to another participant in the cohort, or failed to complete at least half of the cognitive tests. After these quality control measures were implemented, 1,105 participants remained and were included in all subsequent analyses. For common variants we used linear regression to test for association between genotype and cognitive performance with adjustment for important covariates. Rare variants were analyzed using the optimal unified sequence kernel association test. The significance threshold was defined as a false discovery rate corrected P-value (PFDR) of 0.05. Eighteen common variants in 13 genomic regions exceeded the significance threshold for one of the cognitive tests. These included GBA rs2230288 (E326K; PFDR = 2.7 x 10-4) for JoLO, PARP4 rs9318600 (PFDR = 0.006) and rs9581094 (PFDR = 0.006) for HVLT-R total recall, and MTCL1 rs34877994 (PFDR = 0.01) for TMT B-A. Analysis of rare variants did not yield any significant gene regions. We have conducted the first large-scale PD cognitive genetics analysis and nominated several new putative susceptibility genes for cognitive impairment in PD. These results will require replication in independent PD cohorts, and efforts to validate the findings in PDCGC Stage II are in progress.

Study phs001664

Khoe-San genome Project (KSGP)

The Khoe-San Genome Project (KSGP) includes whole genome data generated for 190 study participants from Southern Africa (Namibia and South Africa) representing people speaking a Namibian Khoe-San language (n=150, 12 groups) or regional non-Khoe-San groups (n=40), specifically defined here as Namibian Himba (n=10), South African Southern Bantu (n=12 and representing the Ubuntu Genome Project led by the University of Limpopo) or South African Coloured/European (n=18). Deep whole genome data has been generated for the purposes of cataloguing the extent of regional genetic diversity, creating population specific references and evolutionary trajectories, while creating a population-matched panel of normal (PoN) genetic diversity required for disease associated studies across the region.

Dac EGAC50000000798

CIDR: NCI Genome Wide Predictors of Survival in Colorectal Cancer

CIDR/Molecular Correlates: This study genotyped archived blood samples from colorectal cancer cases participating in clinical trials. The goals of this project were to identify genetic variants associated with survival outcomes treatment and treatment-related severe adverse events among patients with colorectal cancer. Another goal was to examine the impact of adding information on germline genetic loci to existing prognostic models. MOSAIC: Multicenter International Study of Oxaliplatin/ 5FU-LV in the Adjuvant Treatment of Colon Cancer (MOSAIC). A randomized, open label efficacy trial to evaluate the FOLFOX regimen versus LV5FU2 in the adjuvant treatment of stage II and III colon cancer. The primary end point was disease-free survival. CPT.ES1.604: Randomized phase 3 study of weekly irinotecan plus high-dose 5-fluorouracil (FUIRI) versus biweekly irinotecan plus 5-fluorouracil/leucovorin (FOLFIRI) as first-line chemotherapy for patients with metastatic CRC. The aim of this study was to demonstrate that a regimen without leucovorin (LV) (FUIRI) is not inferior to the standard FOLFIRI (response rate). 03-TTD-01: The purpose of this phase III, multicenter, randomized, open-label study is to evaluate the safety and efficacy of combination therapy with capecitabine and oxaliplatin (XELOX) vs. oxaliplatin and 5-fluorouracil in continous infusion (5-FU CI) as first line treatment in advanced or metastatic colorectal cancer. The primary outcome measure is time to disease progression. Secondary outcome measures are to determine safety of combination, objective response rate, time to onset of response, duration of response, time to treatment failure, one year survival time, and overall survival time. 03-TTD-01: The purpose of this phase III, multicenter, randomized, open-label study is to evaluate the safety and efficacy of combination therapy with capecitabine and oxaliplatin (XELOX) vs. oxaliplatin and 5-fluorouracil in continous infusion (5-FU CI) as first line treatment in advanced or metastatic colorectal cancer. The primary outcome measure is time to disease progression. Secondary outcome measures are to determine safety of combination, objective response rate, time to onset of response, duration of response, time to treatment failure, one year survival time, and overall survival time. N0147: Randomized phase III clinical trial for adjuvant therapy in stage III colon cancer patients enrolled at institutions across North America. Originally designed to compare three different chemotherapy regimens, and then later expanded to evaluate adding cetuximab to each original arm (leading to six total arms). Further modification later added pre-screening for KRAS mutation status, with the resulting goal to assess the potential benefit of cetuximab added to the modified sixth version of the FOLFOX regimen (mFOLFOX6) in patients with resected stage III wild-type KRAS colon cancer. Main outcome of interest is disease-free survival in patients with wild-type KRAS, while secondary end points included overall survival and toxicity. N9741: Randomized phase III trial to compare the effectiveness of various combination chemotherapy regimens in treating patients who have advanced, recurrent, or metastatic colorectal cancer that cannot be treated with surgery or radiation therapy. C-08: A Phase III Clinical Trial Comparing Infusional 5-Fluorouracil (5-FU), Leucovorin, and Oxaliplatin (mFOLFOX6) Every Two Weeks With Bevacizumab to the Same Regimen Without Bevacizumab For the Treatment of Patients With Resected Stages II and III Carcinoma of the Colon. The primary aim of the trial was to compare the relative efficacy of mFOLFOX6 + bevacizumab with that of mFOLFOX6 alone in prolonging disease-free survival and the secondary aim was to compare the relative efficacy of mFOLFOX6 + bevacizumab with that of mFOLFOX6 alone in prolonging survival.

Study phs001290

Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - RNA-Seq

This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

Dataset EGAD00001011192

Projects

Projects Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, the EGA provides an invaluable service to the worldwide biomedical research community. The teams leading the EGA are involved in several international partnerships and consortia in numerous scientific fields, where they contribute to ambitious projects. In addition to the project listed below, The EGA is in a long-standing partnership with the Global Alliance for Genomics and Health (GA4GH), as described on the dedicated page. On-going projects Project Duration Domain Funder Tags EASIGEN-DS | The EASIGEN-DS project aims to conduct a design study to establish a new European Research Infrastructure on Advanced Genomics Technologies, EASIGEN. To develop an excellent scientific, technological and operational design, we will conduct landscape studies, stakeholder consultations, and community surveying. 2025-2028 Genomic and health data Horizon Europe DATA MANAGEMENT DOCUMENTATION INFRASTRUCTURE Go-IMPaCT | Go-IMPaCT will contribute sequenced genomes and provide infrastructure as part of IMPaCT-Cohort, one of the three fundamental pillars of the Precision Medicine Infrastructure associated with Science and Technology (IMPaCT) program in Spain. Along with the Genome of Europe (GoE) project, around 18.000 people will have their genomes sequenced, also contributing to Spain's commitments in 1+MG. Go-IMPaCT will fund the development of an EGA node to manage and share this genomic and phenoclinic data, laying the foundations for regional and ethnic genomic variability in Spain to be available for research purposes. The IMPaCT cohort is created with the spirit of being an open research tool, compatible with the rest of the health research ecosystem, and other international initiatives. 2025-2027 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS FAIR-FEGA | This project seeks to accelerate data depositions into FEGA, significantly increasing the data flow in and from FEGA nodes. It will build capacity within the FEGA nodes and increase awareness in a wide range of stakeholders, thus altogether achieving the ultimate goal of enhancing data reuse. The project will be carried out by a strategic consortium comprising seven ELIXIR nodes and two ELIXIR communities. 2025-2026 Not applicable ELIXIR ACCESS DISCOVERY DOCUMENTATION INFRASTRUCTURE METADATA STANDARDS FEGA-Connect | A consortium of six ELIXIR nodes plus the Polish FEGA node (in-kind contribution) joining forces to build a solid base to develop solutions for effective multi-omic sensitive data integration between FEGA nodes and other infrastructures and specialised Data repositories. We aim to promote a more coherent data deposition, discoverability and retrieval of multi-omics datasets, providing FAIRer data and consequently accelerating research. 2025-2026 Multi-omics data ELIXIR ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE METADATA STANDARDS IMPaCT-Data 2 | IMPaCT-Data 2 will develop a digital platform for the integration and modelling of biomedical data associated with IMPaCT (Precision Medicine Infrastructure associated with Science and Technology) projects in Spain. It will deploy a sustainable infrastructure that facilitates the integration, standardisation, interoperability and analysis of clinical, genomic, molecular and medical imaging data. This platform will be aligned with European projects such as Genome of Europe (GoE), the first project to make use of the European Genomic Data Infrastructure (GDI), and EUCAIM. IMPaCT-Data 2 will benefit from advanced Artificial Intelligence and High Computing Capacity Systems capabilities, offering robust and accessible tools for researchers from the National Health System in Spain. 2025-2026 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS ERDERA | The European Rare Disease Research Alliance (ERDERA) takes over EJPRD to deliver concrete health benefits to rare disease patients in the next decade by advancing prevention, diagnosis and treatment research. To leave no one behind, over 170 organisations championed by the European Union and member states are working hand in hand to make Europe a world leader in rare diseases research and innovation. 2024-2034 Rare diseases Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution ACCESS DATA ANALYSIS DISCOVERY INFRASTRUCTURE GoE | The Genome of Europe initiative aims to build a European network of national genomic reference cohorts of at least 500.000 citizens. These reference cohorts will be selected to be representative of the European population. 2024-2028 Large-scale genomic and health data Horizon Europe ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS HEREDITARY | HEREDITARY aims to transform the way we approach disease detection, prepare treatment response, and explore medical knowledge by building a robust, interoperable, trustworthy, and secure framework that integrates multimodal health data (including genetic data) while ensuring compliance with cross-national privacy-preserving policies. 2024-2027 Neurodegenerative disorders, gut-brain interplay Horizon Europe DATA MANAGEMENT DATA ANALYSIS EOSC-ENTRUST | The mission of EOSC-ENTRUST is to create a European network of trusted research environments for sensitive data and to drive European interoperability by joint development of a common blueprint for federated data access and analysis. 2024-2026 Trusted Research Environment Horizon Europe INFRASTRUCTURE EBV-MS | "Targeting Epstein-Barr Virus Infection for Treatment and Prevention of Multiple Sclerosis". The ambitious goals of the project are to answer the questions why only a few EBV infected persons develop MS, and define the underlying mechanism of this process, as well as clarify if targeting the EBV infection can prevent MS or improve the disease course. 2023-2028 Viral-host genetics; immune response; disease modelling; Disease prevention Horizon Europe DATA MANAGEMENT DATA ANALYSIS WISDOM | WELL-BEING IMPROVEMENT THROUGH THE INTEGRATION OF HEALTHCARE AND RESEARCH DATA AND MODELS WITHOUT BORDER FOR CHRONIC IMMUNE-MEDIATED DISEASES aims to deploy novel approaches for data processing, harmonisation, management, and secure data sharing and federated access for diseases like multiple sclerosis. Using an end-user guided approach, it will facilitate responsible and critical assessment of the use of AI in healthcare. 2023-2028 Chronic immune-mediated diseases Horizon Europe DATA MANAGEMENT INFRASTRUCTURE EUCAIM | EUropean Federation for CAncer IMages is a project that will build a highly secure, federated and large-scale European cancer imaging platform, with capabilities that will greatly enhance the potential of Artificial Intelligence in oncology. 2023-2027 Cancer Digital Europe Programme (DIGITAL) DISCOVERY CONTAGIO | CONTAGIO (COhorts Network To be Activated Globally In Outbreaks) aims to create coordination mechanisms to rapidly react to infectious disease (re-)emergence in low- and middle-income countries (LMICs). 2023-2026 Infectious Diseases European Commission - Horizon Europe ACCESS DATA MANAGEMENT DISCOVERY Youth-GEMs | Youth-GEMS (Gene Environment Interactions in Mental Health TrajectorieS of Youth) will conduct research into the genetic and environmental factors of mental health in young European people. 2022-2027 Mental health European Commission - Horizon Europe DATA MANAGEMENT DISCOVERY GDI | The European Genomics Data Infrastructure project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. 2022-2026 Genomic and health data European Commission - Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution DISCOVERY DOCUMENTATION INFRASTRUCTURE EOSC4Cancer | EOSC4Cancer builds on existing projects, research outcomes and established community solutions to create the federated FAIR data, analysis and services infrastructure needed for European Cancer research programmes. 2022-2025 Cancer European Commission - Horizon Europe DISCOVERY IMPaCT-T2D | The IMPaCT-T2D project aims at studying the complete genomes of a large cohort of patients with Type 2 Diabetes mellitus (T2D), using modern sequencing technologies and artificial intelligence (AI) in order to improve the stratification and pharmacological treatment in the context of precision medicine. 2022-2025 Cardiovascular and Complex Diseases Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE EuCanImage | A European Cancer Image Platform Linked to Biological and Health Data for Next-Generation Artificial Intelligence and Precision Medicine in Oncology. 2020-2025 AI Solutions in Oncology European Commission - H2020 Programme; "La Caixa" Foundation cofunds CRG's contribution DATA MANAGEMENT METADATA STANDARDS GenoMed4ALL | A consortium built to empower personalised medicine in the field of haematological diseases through the use of AI and the pooling of genomic and clinical data. 2020-2025 Hematological diseases European Commission - H2020 Programme DISCOVERY METADATA STANDARDS Completed projects Project Duration Domain Funder Tags BY-COVID | The BeYond-COVID project aims to make COVID-19 data accessible to scientists in laboratories but also to anyone who can use it, such as medical staff in hospitals or government officials. Going beyond SARS-CoV-2 data, the project will provide a framework for making data from other infectious diseases open and accessible to everyone. 2021-2024 Infectious diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE IMPaCT-Data | IMPaCT-Data aims to create the infrastructure for secondary use of data from Spanish healthcare systems - electronic health records, medical imaging and genomic repositories - and contribute with the knowledge and methodology produced to the healthcare system. 2021-2024 Large-scale genomics and health dataSpanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE LaMarató | It is a project aimed at creating and developing a catalan interhospitalary network to interrogate genetic variants from thousands of genetic tests carried out in patients with rare diseases from the main catalan hospitals. 2021-2024 Genomic and health data Fundació La Marató de TV3 (catalan foundation) DISCOVERY HealthyCloud | This consortium will contribute a Strategic Agenda towards the European Health Research and Innovation Cloud. The project will work in collaboration with a broad range of stakeholders to ensure that all voices are included and that the results are technically and ethically sound. 2021-2023 Not Applicable European Commission - H2020 Programme DOCUMENTATION B1MG | Beyond 1 Million Genomes aims to create a network of genetic and clinical data across Europe. The project provides coordination and support to the 1+ Million Genomes Initiative (1+MG). This initiative is a commitment of 24 EU countries, the UK and Norway to give cross-border access to one million sequenced genomes by 2022. 2020-2023 Not applicable European Commission - Horizon Europe DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS ELIXIR-CONVERGE | An alliance with the goal of Connecting and aligning ELIXIR Nodes to deliver sustainable FAIR life-science data management services. 2020-2023 Data Management and Infectious Diseases European Commission - H2020 Programme DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS IHCC | The International HundredK+ Cohorts Consortium aims to create a global platform for translational research – informing the biological and genetic basis for disease and improving clinical care and population health. 2020-2022 Translational research NIH; The Wellcome Trust; CZI INFRASTRUCTURE METADATA STANDARDS PPCG | The Pan Prostate Cancer Group aims to harmonise and interrogate Whole Genome DNA Sequence data generated around the world from over 2000 men with prostate cancer, with associated transcriptome and methylome data to include men from different clinical categories, and ethnicities. This project is about providing breakthrough advances through analysis of a very large series of Whole Genome DNA data from prostate cancer contributed by many of the leading scientists and clinicians working in prostate cancer genomics. 2019-2024 Cancer Cancer Research UK DATA MANAGEMENT CINECA | Consortium providing a Federated solution enabling population-scale genomic and biomolecular data accessible across international borders accelerating research and improving the health of individuals resident across continents. 2019-2023 Large-scale Genomics and Health Data European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE EASI-Genomics | A project designed to provide easy access to cutting-edge DNA sequencing technologies to researchers from academia and industry, within a framework that ensures compliance with ethical and legal requirements, as well as FAIR and secure data management. 2019-2023 Next Generation Sequencing European Commission - H2020 Programme ACCESS EJP-RD | An European consortium built to create a comprehensive, sustainable ecosystem allowing a virtuous circle between research, care, and medical innovation. 2019-2023 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DOCUMENTATION METADATA STANDARDS EOSC-Life | EOSC-Life brings together the 13 Life Science research infrastructures (LS RIs) to create an open, digital and collaborative space for biological and medical research. The project will publish 'FAIR' data and a catalogue of services provided by participating RIs for the management, storage and reuse of data in the European Open Science Cloud (EOSC). 2019-2023 Not applicable European Commission - H2020 Programme DOCUMENTATION EUCANCan | A federated network aiming at implementing a cultural, technological and legal integrated framework across Europe and Canada, to enable and facilitate the efficient sharing of cancer genomic data. 2019-2023 Cancer European Commission - H2020 Programme DATA MANAGEMENT METADATA STANDARDS The Federated EGA framework: supporting sensitive data management across the ELIXIR Nodes | This project is a direct continuation of the FHD IS with the goal to position the FEGA framework as the core infrastructure driver to support human data sharing for research. 2019-2023 Human genomic data ELIXIR INFRASTRUCTURE UK Biobank | UK Biobank is a large-scale biomedical database and research resource, containing in-depth genetic and health information from half a million UK participants. This project is to archive whole genome sequencing and other genetic data for UK Biobank participants. 2019-2023 Large-scale Genomics and Health Data The Wellcome Trust; UKRI; Amgen; AstraZeneca; GSK; Johnson & Johnson DATA MANAGEMENT INFRASTRUCTURE VEIS | The core mission of VEIS is to create an open ecosystem of technologies that will address and adapt to the requirements of the systems used to analyse and interpret -omics and clinical data in research and application environments in biomedicine. The aim of the project is to leverage the value of the EGA for both industry and society. 2019-2022 Oncology and Rare diseases Generalitat de Catalunya and European Regional Development Fund (ERDF) ACCESS DISCOVERY ELIXIR BEACON IS | This study follows on from a number of earlier activities that have established the ELIXIR Beacon Project. The main aim is to extend the Beacon protocol, developed at EGA, to become the reference ELIXIR Data Discovery product 2019-2021 Not applicable ELIXIR DISCOVERY ELIXIR FHD IS | This project coordinates the delivery of FAIR compliant metadata standards, interfaces, and reference implementation to support the federated ELIXIR network of human data resources. 2019-2021 Human genomic data ELIXIR INFRASTRUCTURE ELIXIR Rare Disease | The Rare Disease Community extends and generalises the system of access authorisation and high volume secure data transfer developed within the EGA. The goal of the Community is to create a federated infrastructure that will enable researchers to discover, access and analyse different rare disease repositories across Europe. It is doing this in partnership with other European infrastructure projects, namely RD-CONNECT, BBMRI-ERIC and E-Rare.2019-2021 Rare diseases ELIXIR INFRASTRUCTURE Solve-RD | Solve-RD - solving the unsolved rare diseases - is a research project funded by the European Commission. It echoes the ambitious goals set out by the International Rare Diseases Research Consortium (IRDiRC) to deliver diagnostic tests for most rare diseases by 2020. The current diagnostic and subsequent therapeutic management of rare diseases is still highly unsatisfactory for a large proportion of rare disease patients - the unsolved RD cases. For these unsolved rare diseases, we are unable to explain the etiology responsible for the disease phenotype, predict the individual disease risk and/or rate of disease progression, and/or quantitate the risk of relatives to develop the same disorder. 2018-2024 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT METADATA STANDARDS EuCanShare | An EU-Canada joint infrastructure for next-generation multi-Study Heart research. 2018-2022 Cardiovascular Diseases European Commission - H2020 Programme ACCESS METADATA STANDARDS

Documentation about/projects-and-funders/projects

Rare Disease Susceptibility Variant Study in Children with Crohn's Disease and Their Parents Using Targeted Gene Sequencing.

We performed targeted, massively-parallel sequencing of 101 genes in 205 children with Crohn's disease, including 179 parent-child trios and 200 controls, both of European ancestry. We identified three genes with nominally significant p-values: NOD2, RTKN2, and MGAT3. Only NOD2 was significant after correcting for multiple comparisons. We identified eight novel rare variants in NOD2 that are likely disease-associated. Incorporation of rare variation and compound heterozygosity nominally increased the proportion of variance explained from 0.074 to 0.089. We estimated the population attributable risk and total heritability of variation in NOD2 to be 32.9% and 3.4%, respectively, with 3.7% and 0.25% accounted for by rare putatively functional variants. Sequencing probands (as opposed to genotyping) to identify rare variants and incorporating phase by sequencing parents can recover a portion of the missing heritability of Crohn's disease. (Reprinted from G3 2018;8(9): 2881-2888; PMID: 30166421. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.)

Study phs001751

Analysis of IDHwt-glioblastoma samples from paired primary and recurrent tumor samples

IDHwt-glioblastomas rapidly recur after initial treatment. To study genetic evolution in glioblastoma, we analyzed whole genomes of 21 pairs of primary and recurrent tumor samples using next generation sequencing. In addition we sequenced RNA from 16 tumor pairs and a panel of 50 glioma-associated genes in tumor pairs from 43 patients (including 14 of the 21 patients included in the WGS discovery set). Glioblastoma subtypes were determined using 450k/EPIC methylation arrays. This study was supported within the e:med program of the German Ministry of Education and Research (BMBF) by the collaborative research project ‘SYS-GLIO - Systems-based prediction of the biological and clinical behavior of gliomas’ (https://www.sys-med.de/de/demonstratoren/sys-glio/) This study is part of the Heidelberg Center for Personalized Oncology - HIPO-043

Study EGAS00001003184

Dac for "ARHGAP11A Maintains Cortical Progenitor Identity Through RHOA–ROCK Signalling During Human Brain Development" with Julia.ladewig@zi-mannheim.de, Department of Translational Brain Research. Moritz Mall, m.mall@dkfz-heidelberg.de, German Cancer Research Center (DKFZ). Yannick Hass, yannick.hass@zi-mannheim.de, Department of Translational Brain Research. Anne Hoffrichter, anne.hoffrichter@zi-mannheim.de, Department of Translational Brain Research, Central Institute of Mental Health

Dac EGAC00001003603

Whole exome sequencing data of patients with resectable esophageal adenocarcinoma treated with neoadjuvant atezolizumab and chemoradiation (PERFECT)

Whole exome sequencing was performed on matched tumor and normal DNA of patients with resectable esophageal adenocarcinoma that particpated in the PERFECT trial. The PERFECT trial is an open-label, single-arm, multicenter, phase II feasibility study (NCT03087864) investigating the safety and efficacy of atezolizumab, combined with neoadjuvant chemoradiotherapy and subsequent esophagectomy.

Study EGAS00001006504

Submission FAQ

Submission FAQ Before Submission Is the EGA the right archive for my data? TThe most suitable archive for your data is dependent on the type of data you are wishing to submit and whether the data require public or controlled access. Public access is defined as complete and open access to all submitted data. On the contrary, controlled access, exerted by the EGA, requires formal applications to be made to access the submitted data files and metadata. EGA only accepts human-derived data subject to controlled access. If your submission contains other types of data, please choose the appropriate repository for it (see image below): ENA, EVA, ArrayExpress, BioSD and GWAS catalog. Should your submission be subjected to controlled access? Data access conditions are normally defined in the original informed consent agreements signed by the participants involved in your study. All data submitted to the EGA is subject to controlled access. These consents prevent the derived data files, potentially identifiable, from being dispersed by open and public access. Controlled access data often refers to human data derived from medical research and consortium projects. If in doubt, consult the informed consent agreements that apply to your study The EGA enables you to hold a submission before publication. What data types can be submitted to the EGA? Data types accepted by the EGA can be split into three categories: Sequences: both in generic and platform-specific formats. Array-based: from raw signal files to processed matrices. Phenotypes: all possible phenotype formats are accepted. All manufacturer-specific raw data formats derived from major next generation sequencing platforms are accepted. Also generic sequence formats: flat reads in a FASTQ file, aligned sequences (BAM or CRAM files) as well as sequence variation files in VCF format. All array-based technologies are accepted, including raw data, intensity and analysis files, without any restriction on data formats accepted. We also accept and distribute phenotype data (associated to the samples) in almost any format: from an image to a README file. How long does a submission take? Submissions to EGA come in a variety of formats and sizes, thus it is difficult for us to exactly predict how long a submission will take. We, therefore, advise all of our submitters to allow as much time as possible to make a submission. Based on previous records, we anticipate that the submission process may take at least one month. The submitter’s familiarity with the procedures, possible technical issues that may arise during submission and the amount of data that is being submitted are the main factors that will affect the length of the submission process. However, each step of a regular submission should be considered when estimating the time it would take: Encryption of the files Upload of the files Metadata submission Archival of the files Release of the study and datasets to EGA webpage For example, the upload of the files depends on the submission size, while metadata submission mainly relies on each submitter’s expertise. Further, some steps (e.g. answering to inquiries) depend on the EGA Helpdesk team, which may take some days to be processed during busy times Is data deposited in the EGA secure? The EGA set-up consists of a secure computing facility for data processing, a shared EBI set-up for data submissions and distribution of data via data requests made through the EGA website. Data is also copied in the Barcelona Supercomputing Center (BSC) infrastructure, where all stored and distributed data is encrypted Data is encrypted along the submission process and stored securely, granting its access to authorised users exclusively. During the download process, through our Python Client or Aspera, all requested data is downloaded over secure https connections. All data at the EGA is encrypted, and only accessible (for log-in and download) through secure protocols. For further information please, visit our security overview. What documentation do I need to provide? All submissions require policy’s documentation: 'Data Access Agreement (DAA)', 'Data Processing Agreement (DPA)' and 'Authorized Submitters Formulary'. The data processors (EGA) and the data owners will also sign the DPA. Will all metadata be public? Among the submitted metadata we need to make the distinction between identifiable and unidentifiable metadata: (1) the former may allow the identification of the human the sample derived from (e.g. detailed geographical providence, personal name, family ancestry…); (2) while the latter can be used to interpret the data without compromising the anonymity of the patients. The majority of the metadata submitted to the EGA corresponds to the unidentifiable category (e.g. sequencer's model). This type of metadata is publicly available on the EGA website and other EBI resources/partners’ websites. On the other hand, some parts samples’ metadata are subject to being identifiable, and thus only accessible by authorized data requesters, with the exception of: 5 submitter-defined attributes of the sample: alias, title, subject_id, gender and phenotype. It is the submitter’s responsibility not to submit sensitive metadata in these public fields. 3 anonymised fields that pinpoint the sample record in archivals: sample’s EGA stable ID (EGAN…), BioSample ID (SAMEA…) and submitter’s center name. During Submission Are there any sample specific requirements for EGA? All samples submitted to the EGA must include the attributes of biological sex, subject ID (anonymised individual identifier) and phenotype information. These are critical for data findability and its analysis, and we highly recommend using controlled ontology terms where applicable. For example: defining tumour and non-tumour samples and/or defining disease state. The EGA recommends using the Experimental Factor Ontology Database to find ontologized terms that describe your sample phenotypes. How do I get an accession number to use in my publication? You will receive your study accession number (EGAS…) upon complete your submission, either: Programmatically. As soon as the metadata is submitted and validated your study will be assigned an accession number that will be given in the submission’s response. Manually registering your study and relevant metadata using the online metadata submission tool: the EGA submitter Portal. How are files uploaded to the EGA? Data files are uploaded into private submission drop boxes (i.e. environments to which you are granted access and where you can transfer your files) using INBOX or FTP. These spaces are provided as part of the submission procedure. Before uploading any file, you must encrypt your files, . Only encrypted files shall be uploaded to the drop boxes. Why does data need to to encrypted for my submitted files? It is one of the security steps the EGA has implemented. In case of a security breach, people without the proper encryption key will not be able to read or use the information that could have been leaked. This measure is essential when working with sensitive data, such as controlled access human data. All submitters must use crypt4gh to create EGA compliant files prior to uploading them. This encryption is GPG-based, using EGA’s public key. Why are my files not available if I see them in the INBOX? There exists a time window between the data upload and the availability of such files via the Submitter Portal. For this reason, some metadata (run and analysis objects) cannot be registered until at least 24 hours after the files have been uploaded to your box. Why are MD5 sum values generated for my submitted files? We require pre- and post- encryption MD5 (message-digest) checksum values to be provided for all submitted files. These 128-bit values are computed using the content of each file, creating unique sequences that allow us to ensure that file integrity has been maintained during the transfer process. In other words, if the MD5 checksums we generate and those you generated match, we infer that the content of the transferred files is correct (i.e. files are not corrupted or truncated). MD5 checksums are computed automatically using the crypt4gh tool provided. Your submission will not be accepted and may be significantly delayed if you do not provide MD5 checksum values for all data files in the required format. How can I check if my files are correctly uploaded to the inbox? It is important to check the status pf your file so you know whether your files are in the inbox, being processed, or if there is any issue with one of them. In order to check this, you should: Look for the file locally. Drag and drop it to the file table. Then bars will appear on the table, which means that we are processing it. Green: The files checksum are correct and your file will move to “ingested files”. No further actions are needed from your end.. Red: The files checksum does not match and your file needs to be re-uploaded. Please re-upload relevant files to your inbox using the same path. After Submission How do I use my accession number in my publication? We suggest the use of the below template, using your study accession ID (EGAS…) : Data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX. Further information about EGA can be found at https://ega-archive.org and "The European Genome-phenome Archive of human data consented for biomedical research" Your study ID will be the one that groups your whole submission, and thus its usage is recommended as such. Nevertheless, all metadata submitted to EGA hold a unique and persistent identifier (starting with EGA…) that can be used to identify specific records. For example, you could reference a specific dataset (EGAD…) or sample (EGAN…) in your publications (see full list of identifiers). How do I make my data searchable? Once you have finalized your submission, you can schedule the data release. Please take into account that the release process needs time for the files to be archived in our system, and for the Helpdesk team to validate your submission. Can I withdraw (meta)data from the EGA? We have methods in place for the secure removal of deposited (meta)data. Contact EGA-helpdesk for further details. EGA complies with FAIRness of (meta)data, and thus, even when the data is removed we keep an entry for their identifiers in our system. In other words, we execute a soft delete on canceled objects (e.g. a study): metadata is still stored in our systems, but it loses all links, cannot be queried and data files cannot be retrieved anymore. The reason behind this behaviour is so that queries using withdrawn data properly respond back (see example of a canceled study). What happens to the data once it has been submitted to the EGA? When the data is submitted, the submitter can choose either keep their data private or schedule the release of their data.

Documentation submission/metadata/submission/FAQ

The whole blood of female volunteers and sperm from the male volunteer were used to extract genomic DNA to do whole genome sequencing. Distinguished SNPs between parental genomes were retained to analyze parental allele-specific DNA methylation and chromatin accessibility in scCOOL-seq data.

DNA methylation, chromatin states, and their interrelationships represent critical epigenetic information, but those are largely unknown in human early embryos. Here, we apply scCOOL-seq (Chromatin Overall Omic-scale Landscape Sequencing) to generate a genome-wide map of DNA methylation and chromatin accessibility at single-cell resolution during human preimplantation development. Unlike in mice, the chromatin of paternal genome is already more open than that of maternal genome at the mid-zygote stage in humans, and this state is maintained until the 4-cell stage. After fertilization, genes with high variations in DNA methylation and those with high variations in chromatin accessibility tend to be two different sets. Furthermore, 1,797 (35%) out of 5,155 widely open chromatin regions in promoters closed when transcription activity was inhibited, indicating a feedback mechanism between transcription and open chromatin maintenance. Our work paves the way for dissecting the complex, yet highly coordinated, epigenetic reprogramming during human preimplantation development.

Study EGAS00001002987

GA4GH

Standards The EGA is a long-standing supporter of the Global Alliance for Genomics & Health (GA4GH) to enhance responsible sharing of human genetic data through the development of interoperable global standards for human data access. The EGA is one of the founding GA4GH Driver Projects and has contributed to the development and implementation of several GA4GH standards and APIs. Below is a list of the GA4GH standards and APIs that are currently available or planned for implementation at EGA. TechnicalStandards Purpose SpecificationVersion SupportedVersion Implementation Large Scale Genomics htsget A protocol for secure, efficient, and reliable access to sequencing read and variation data. V1.3.0 V1.0.0 Specification Documentation Endpoint Read File Formats (SAM/BAM/CRAM) Specifications for storing next-generation sequencing read data. V3.0.0 V3.0.0 Implementation Example of Usage Variation File Formats (VCF/BCF) The specifications for Variant Call Format Files (VCF) and its binary counterpart BCF. V4.0.0 V2.0.0 V4.0.0 V2.0.0 Implementation Example of Usage Crypt4GH v1.0 Enables direct byte-level compatible random access to encrypted genetic data stored in community standards (e.g. CRAM, VCF) V1.0 V1.0 Specification Documentation Endpoint refget API Enables access to reference sequences using an identifier derived from the sequence itself. V1.2.6 NA Specification RNAget API v1 Provides a means of retrieving data from several types of RNA experiments including (i) feature-level expression data from RNA-seq type measurements and (ii) coordinate-based signal/intensity data similar to a bigwig representation via a client/server model. V1.0.0 NA Documentation Discovery Beacon v2 Supports discovery of genomic variants, phenotypes, and individuals V1.0.1 V0.3 Web UI API Source Code Service Info API v1 The Service Info API is an endpoint for describing GA4GH service metadata, designed for extension and inclusion in other APIs. Service info is used to describe a single service, while Service Registry is used to describe multiple services. V1.0.0 NA Documentation Service Registry API v1 provides information about other GA4GH services, primarily for the purpose of organizing services into networks or groups and service discovery across organizational boundaries. V1.0.0 NA Documentation Data Use Researcher Identities Data Use Ontology (DUO) Allow users to semantically tag genomic datasets with usage restrictions, allowing them to become automatically discoverable based on a health, clinical, or biomedical researcher’s authorisation level or intended use. 2021-02-23 2021-02-23 Specification Documentation Endpoint Authentication & Authorization Infrastructure (AAI) The GA4GH AAI specification leverages OpenID Connect (OIDC) Servers for use in authenticating the identity of researchers desiring to access clinical and genomic resources from data holders adhering to GA4GH standards, and to enable data holders to obtain security-related attributes of those researchers. V1.2.0 V1.2.0 API URI: ega.ebi.ac.uk:8443 Documentation Repository Researcher IDs (passport, visa) Specify the collection of researchers that may access a dataset at any given time, and the credentials they must supply. V1.0.1 V1.0.1 Specification Documentation Endpoint Cloud Tool Registry Service API TRS is a standard API for exchanging tools and workflows to analyze, read, and manipulate genomic data. V2.0.1 NA Documentation Repostiory Data Repository Service API DRS API is a standard for building data repositories and adapting access tools to work with those repositories, works with other approved APIs from the GA4GH Cloud Work Stream to allow researchers to discover algorithms across different cloud environments and send them to datasets they wish to analyse. V1.0.3 NA Documentation Repostiory Workflow Execution Service API This API lets users run a single workflow (defined using CWL or WDL) on multiple different platforms, clouds, and environments, and be confident that it will work the same way. The API provides methods to request that a workflow be run, pass parameters to that workflow, get information about running workflows, and cancel a running workflow. V1.0.1 NA Documentation Repostiory Genomic Knowledge Standards Variation Representation v1 Provides a flexible framework of computational models, schemas, and algorithms to precisely and consistently exchange genetic variation data across communities. V1.3.0 EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Clin/ Pheno Data Capture Phenopackets Provides information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged. V2.0.0 Included in Ongoing Submissions EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Driver Project The EGA, jointly coordinated by the EBI and the CRG, was announced, in 2017, to be one of the 15 Driver Projects for GA4GH. Driver Projects are international genomic data initiatives, focussed on real projects and challenges that will guide the development efforts in order to accelerate and enable completely responsible and standarised data sharing by 2022. All chosen Driver Projects make a cross-sectional effort by playing an important role across the different workstreams. Thomas Keane, Jordi Rambla, Mallory Freeberg, and Aina Jené have been named Driver Project Champions for the EGA. All Driver Project Champions will be leading this ambitious initiative for the following years.

Documentation about/projects-and-funders/ga4gh

NHLBI TOPMed - NHGRI CCDG: Early-onset Atrial Fibrillation in the CATHeterization GENetics (CATHGEN) Cohort

The CATHeterization GENetics (CATHGEN) biorepository collected biospecimens and clinical data on individuals age ≥18 undergoing cardiac catheterization for concern of ischemic heart disease at a single center (Duke University Medical Center) from 2000-2010; a total of N=9334 individuals were collected. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included subject demographics, cardiometabolic risk factors, cardiac history including symptoms, age-of-onset of cardiovascular diseases, coronary anatomy and cardiac function at catheterization, laboratory data, and yearly follow-up for hospitalizations, vital status, medication use and lifestyle factors. AF cases were defined as individuals who had ever had AF based on any ECG available at Duke University or ICD-9 code for AF used for inpatient or outpatient billing.

Study phs001600

The genetic history of the southern Andes from present-day Mapuche ancestry

We generate genome-wide data from 64 participants from three Mapuche populations in Southern Chile: Pehuenche, Lafkenche, and Huilliche. Broadly, we describe three main ancestry blocks with a common origin, which characterize the Southern Cone, the Central Andes, and Amazonia. Within the Southern Cone, ancestors of the Mapuche lineages differentiated from those of the Far South during the Middle Holocene, and did not experience further migration waves from the north. We find that the deep genetic split between the Central and Southern Andes is followed by instances of gene flow, which may have accompanied the southward spread of cultural traits from the Central Andes, including crops and loanwords from Quechua into Mapudungun (the language of the Mapuche). Our findings add new perspectives on the genetic (pre)history of South America, from first settlement through to the present-day indigenous presence. Follow-up fieldwork took these results back to the indigenous communities to contextualize the genetic narrative alongside indigenous knowledge and perspectives.

Study EGAS00001007200

Federated EGA

Federated EGA Federated EGA Index Overview Map of FEGA status across the world Current status of the FEGA Network Documentation Overview Federated EGA is a global network of repositories enabling secure discovery and access to sensitive human data. Our vision is to accelerate scientific discovery and healthcare breakthroughs by creating the go-to worldwide sensitive human data resource. Our values are: Privacy & Trust: Ensuring privacy of data subjects, security of services and acting with integrity to build community trust.FAIRness: Driving reuse of data through standardisation of metadata and clear access policies.Diversity: Expanding our network and representing global diversity in the data we host to bring benefits worldwide. Federated EGA - European by name, global by nature Federated EGA collaborates with European and global initiatives (GA4GH, ELIXIR, 1+ Million Genomes Framework, GDI), demonstrating that a network for transnational discovery of and access to human data is possible. By providing a solution to emerging challenges around secure and efficient management of human omics and associated data, the FEGA Network fosters data reuse, enables reproducibility, and accelerates biomedical research. For general enquiries or to request more information about Federated EGA, please reach out to us here. Read more about the Federated EGA in our commentary in Nature Genetics! Learn more about setting up a Federated EGA Node in our onboarding documentation. Map of FEGA status across the world Current status of the FEGA Network Node Description Joined CEGA Central EGA is managed by the Centre for Genomic Regulation (CRG) and EMBL-EBI. The EGA has been a trusted repository for sensitive data since 2008. CEGA coordinates the FEGA network, hosts central services and the EGA catalogue. 2022 Finland FEGA Finland is hosted by CSC - IT Center for Science Ltd., which is the national ELIXIR Node in Finland. CSC is a state-owned company specialising in providing high-quality IT infrastructure and services for Finnish higher education and research. 2022 Germany The German Human Genome-Phenome archive (GHGA) is part of the German National Research Data Infrastructure (NFDI). It is coordinated by the German Cancer Research Center (DKFZ) and includes over 20 academic partners. 2022 Norway FEGA Norway is a service by ELIXIR Norway, the Norwegian node of the European organisation ELIXIR. University of Oslo as a partner institution in ELIXIR Norway is hosting the service relying on the TSD infrastructure for sensitive data. ELIXIR Norway is a consortium of 5 Norwegian universities and is coordinated by University of Bergen. 2022 Spain FEGA Spain is co-hosted by the Barcelona Supercomputer Center (BSC) and the Centre for Genomic Regulation (CRG), both part of ELIXIR Spain and the Spanish National Infrastructure for Personalised Medicine associated with Science and Technology (IMPaCT). 2022 Sweden FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. 2022 Poland FEGA Poland is hosted by Biobank Lodz, which is part of University of Lodz. Biobank Lodz is an element of the infrastructure of the Regional Digital Medicine Centers established by the Medical Research Agency. 2022 Portugal FEGA Portugal is managed by BioData.pt, the distributed infrastructure for Life and Health data for Portugal. This entity is a non-profit association of 15 life sciences R&I organisations spread across the country, and the home of ELIXIR Node in Portugal. 2023 Canada Canadian Genome-phenome Archive is part of the Pan Canadian Genome Library, with the mandate to allow the secure and responsible sharing and analysis of Canadian genomic information. 2024 Switzerland Swiss FEGA is hosted by SIB Swiss Institute of Bioinformatics, which is the national ELIXIR Node in Switzerland, on behalf of the Swiss FEGA Partnership which includes 4 other key partners (ETH Zurich, Health 2030 Genome Center, Swiss Data Science Center and Switch). 2025 Documentation Title Version Description Mission, vision, values Federated EGA Mission, vision, values 1.0 The official Mission-Vision-Values statement for FEGA, produced and formally approved by the FEGA Strategic Committee in September 2025. Structure and Organisation Federated EGA Structure and Organisation 1.1 New version under review, coming January 2026. Strategic Committee Federated EGA Strategic Committee 1.1 Terms of reference for the FEGA Strategic Committee describe the purpose and objectives of the committee, which is to provide direction and strategic planning for the FEGA network. The committee receives input from, and provides feedback for the EGA Strategic Committee. Operations Committee Federated EGA Operations Committee 1.1 Terms of reference for the FEGA Operations Committee describe the purpose and objectives of the committee, which is to review operational performance and coordinate technical roadmaps of FEGA Nodes and Central EGA. The committee receives advice from, and provides operational reporting to the FEGA Strategic Committee. Guidelines Node Operations guidelines 2.1 An overview of the operational areas which require resources in order to create a FEGA Node. The document is based on more than 15 years' experience of EMBL-EBI and CRG operating the EGA and initial expericences of the inaugural FEGA Nodes. The operational areas of responsability are in line with the FEGA Maturity Model, which guides establishment and operation of FEGA Nodes. Collaboration Federated EGA Node Collaboration Agreement 1.3 Nodes are welcome to make a copy of this current version of the CA to start its review with their legal teams and understand the responsibilities of joining FEGA. Nevertheless, this version (the one with a watermark) shall not be signed: the official version needs to be obtained from FEGA prior signing through its official channels.

Documentation about/projects-and-funders/federated-ega

Ensemble learning for classifying single-cell data and projection across reference atlases

Single-cell data are being generated at an accelerating pace.How best to project data across single-cell atlases is an open problem. We developed a boosted learner that overcomes the greatest challenge with status quo classifiers: low sensitivity, especially when dealing with rare cell types.

Study EGAS00001004283

Stressors and Health Study

ObjectivesThe objectives of the Stressors and Health Study were to: (1) examine the prevalence of stressors and health outcomes and (2) assess differences in the associations between multi-level stressors and health outcomes, and (3) explore the protective and adaptive factors in the associations between multi-level stressors and health outcomes. Background Stressors have been posited to explain disparities in health. However, no surveys to our knowledge have simultaneously collected multiple stressors at various levels and the coping strategies used to deal with these stressors. Measuring these factors can provide a better understanding of the stressors experienced by specific groups and the impact that these experiences have on their health and health practices. In addition, exploring the various resilience and coping strategies employed to deal with stressors can help design appropriate interventions to reduce health disparities. Participants Participants included 1000 White, 1000 Black or African American, 1000 Latino or Hispanic, 1000 Asian, 500 American Indian or Alaska Native, 500 Native Hawaiian or Pacific Islander, and 500 mixed or multi-race adults (≥18 years) across the United States. Design The Stressors and Health Study is a cross-sectional online survey of adults across the US. A sampling frame (target population) of US residents based on the American Community Survey (ACS) was constructed using a rigorous two-step sampling matching approach to establish national representation.

Study phs004019

FFPE, buffycoat and cell free DNA from N. German esophagus cancer patients - 2021

28 patients. Cell-free DNA and leukocyte DNA, both from before any neoadjuvant treatment. Tumor FFPE tissue (plus metastasic tissue for some patients) from after any neoadjuvant treatment. Some cfDNA from follow-up time points (e.g. after neodj. treatment or in the clinical course). IDT xgen Pan-Cancer panel for hybridisation capture. Illumina TruSeq library prep for cfDNA and leukocyte DNA, Illumina DNA Prep for FFPE DNA. n=150 libraries in total.

Dataset EGAD00001010081

Age related Macular Degeneration (AMD)-- Michigan, Mayo, AREDS, Pennsylvania (MMAP) Cohort Study: A Joint Genome Wide Association Study

Age-related Macular Degeneration (AMD) is a leading cause of incurable blindness in people over the age of 65. AMD is a late-onset multi-factorial neurodegenerative disease and its pathogenesis involves interaction of genetic and environmental factors. Several chromosomal regions have been associated with AMD susceptibility through linkage analysis (Swaroop et al., 2009). More recent studies provide strong evidence that variants within the CFH gene cluster on chromosome 1 and at/near LOC387715/ARMS2 on chromosome 10 are strongly associated with disease. Variants at other genes including C2/BF, C3, CFI and APOE4, also contribute to AMD susceptibility. Our primary goals are to identify genetic variants and haplotypes that are associated with AMD. The underlying hypothesis is that DNA variation(s) in multiple genetic susceptibility loci will predispose individuals to AMD pathogenesis, and comparison of DNA of cases and controls should identify these susceptibility variants. Our studies are focused on the genetic analysis of advanced AMD and should provide novel insights into disease diagnosis, progression and pathology. We have assembled a collaborative group of researchers from the University of Michigan, Mayo Clinic, University of Pennsylvania, and the AREDS group including National Eye Institute intramural investigators, who collected clinical data and DNA from a large number of patients affected with AMD and from unaffected controls. The primary source of funding was National Eye Institute. Through this collaborative effort, we submitted and obtained usable genotyping data on 2184 patients and 1155 controls from the Center for Inherited Disease Research (CIDR).

Study phs000182

H3Africa - Deciphering Developmental Disorders in Africa

Developmental disorders are typically rare conditions, causing an impairment in physical, learning, language, or behavioural areas. Genetic heterogeneity and highly variable clinical manifestations make diagnosing developmental disorders particularly challenging. Developmental disorders are increasing in prevalence in low- and middle-income countries, partly due to effective prevention and treatment of infectious diseases leading to a decrease in childhood mortality. New sequencing technologies are used effectively in the diagnosis of rare diseases and results can impact clinical practice significantly. Despite this international trend, very little implementation of these new approaches has taken place in low-resource settings, especially in Africa. The Deciphering Developmental Disorders in Africa (DDD-Africa) study aims to take advantage of an unbiased genotype-driven approach to improve healthcare services for patients. The study aims to recruit and perform detailed clinical phenotyping and exome sequencing (ES) on 500 African patients with a developmental disorder in whom a genetic diagnosis has not been confirmed. Where available, parents are also included in sequencing efforts. The project has two active research sites in Johannesburg (South Africa) and Kinshasa (Democratic Republic of Congo) representing diversity in geography, clinical, socio-economic, genetic and environmental factors.

Study EGAS00001008319

Genome-wide mutation analysis of germinal-center B-cell derived lymphomas within the ICGC MMML-Seq Consortium

Germinal-center B-cell derived lymphomas (GCB-lymphomas) are the most common B-cell lymphomas in children and adults, with Burkitt Lymphomas (BL) predominating in childhood and follicular lymphoma (FL) and diffuse large B-cell lymphomas (DLBCL) predominating in older age groups. The cell-of-origin in all these lymphomas is supposed to be a germinal center B-cell and transformation of FL in DLBCL or intermediate DLBCL/BL (intL) can occur. In the framework of the German ICGC MMML-Seq we are currently exploring sequencing data of GCB-lymphomas and paired normal controls as well as normal B-cell subsets separated by FACS. This includes whole genome, transcriptome, miRNAome and whole methylome datasets.

Study EGAS00001000394

A Pilot Study of NKTR-214 and Nivolumab in Selected Patients with Locally Advanced/Metastatic Sarcoma

Study cohort comprises samples derived from patients that received treatment on an open-label, non-randomized, non-comparative pilot study of bempegaldesleukin, a CD122-preferential interleukin-2 pathway agonist, with nivolumab in refractory sarcoma at Memorial Sloan Kettering/MD Anderson Cancer Centers (NCT03282344). Patient tumors include a variety of sarcoma subtypes. Samples include whole exome sequencing of tumor/normal pairs, poly-A RNA and TCR sequencing of tumors.

Study phs002852

Carolina Breast Cancer Study (CBCS)

The Carolina Breast Cancer Study (CBCS), phase III, is a population-based study aiming to understand the social and molecular correlates of breast cancer outcomes, particularly among Black and young women. CBCS recruited first primary breast cancer cases from 44 North Carolina counties between 2008-2013. All cases were between age 20 and 74 and self-identified as female. Black women and young women were systematically oversampled by randomized recruitment such that the study includes approximately 50% Black women and approximately 50% women diagnosed before age 50. A total of 2,998 participants were enrolled. In the ten years following diagnosis, women completed surveys approximately every 1-2 years and diagnoses of subsequent distant local recurrence and second primary tumors were ascertained via linked medical records. We identified records of women who developed secondary breast tumors (including second primary tumors, contralateral breast cancers, and locoregional recurrences), and these participants were oversampled for targeted DNA sequencing using the UNCseq panel (~1200 genes).CBCS germline pathogenic mutations cannot be investigated because participants were consented between 2008 and 2013 with specific language prohibiting this. However, germline data can be used to call somatic mutations or to standardize somatic genomic data.For sharing of study data not included here, please visit unclineberger.org for instructions on submitting a data use agreement.

Study phs003725

Transdisciplinary Studies of Genetic Variation in Colorectal Cancer(CORECT): Meta-analysis

This study is part 2 of 2 for Schumacher et al, Nat Communication. 2015 Jul 7;6:7138. Part 2 is the pooled meta-analysis of 29 different studies of 37,955 European (18,299 Cases/19,656 Controls) participants using eight different genotyping platforms/variations. table, th, td { border: 1px solid black; border-collapse: collapse; } Study Name Participants Platform CFR-1 2976 Illumina 1M, 1M Duo, Omni1 CFR-2 3053 Affymetrix Axiom MECC 1 982 Illumina Omni 2.5 MECC2 1940 Affymetrix Axiom Kentucky 2172 Affymetrix Axiom ACS/CAPII 1086 Affymetrix Axiom Melbourne 1008 Affymetrix Axiom Newfoundland 672 Affymetrix Axiom ASTERKSI 1895 Illumina 300K COLO23 212 Illumina 300K DACHS1 3417 Illumina 300K DACHS2 1173 Illumina OmniExpress DALS1 1416 Illumina 550k/610K DALS2 874 Illumina 300K HPFS1 457 Illumina OmniExpress HPFS2 348 Illumina OmniExpress HPFS AA 658 Illumina OmniExpress MEC 674 Illumina 300K NHS1 1168 Illumina OmniExpress NHS2 340 Illumina OmniExpress NHSAA 1091 Illumina OmniExpress OFCCR 1172 Affymetrix 100k/500K PHS 771 Illumina OmniExpress PMH 402 Illumina 300K PLCO1 2509 Illumina 550k/610K PLCO2 901 Illumina 300K VITAL 573 Illumina 300K WHI1 1999 Illumina 550k/610K WHI2 573 Illumina 300K Since this study is a meta-analysis no corresponding phenotype, pedigree, sample, subjects, or primary molecular data are available. Each contributing study/platform will have fulfilled its own DBGAP submission commitment. This DBGAP entry is for European participants in the the pooled meta-analysis exclusively.

Study phs001499

ImmunAID Data Access Committee

The ImmunAID Data Access Committee (DAC) oversees controlled access to cohort data and samples generated within the project. Access requests must be submitted via a standardized form and are reviewed by a Steering Committee (SC), with potential input from the External Advisory Board (EAB). Requests must include detailed scientific, ethical, and regulatory information, including data protection measures in accordance with the GDPR and French legislation. The SC evaluates proposals based on scientific merit, methodological rigor, ethical considerations, and the availability of cohort resources. Decisions are communicated within 8 weeks. Opinions can be favorable, conditional (requiring modifications), or unfavorable (with one resubmission allowed). Only academic, industrial, or project-affiliated research teams are eligible to apply.

Dac EGAC50000000654

Targeted Validation Samples

The dataset consists of targeted sequencing data obtained from an independent cohort of 11 patients to validate discriminative DMRs (differentially methylated regions) for Acute coronary syndrome (ACS) subtypes. The cohort includes 2 healthy subjects, 4 STEMI (ST-segment elevation myocardial infarction), 3 NSTEMI (non-ST-segment elevation myocardial infarction), and 2 UA (unstable angina) patients. The sequencing panel targeted 18,831 CpGs for analysis, reaching at least 5 reads coverage for 75% of the targeted CpGs in each sample. The sequencing was performed using the NEBNext Enzymatic Methyl-seq Module and the Nonacus Cell3TMTarget: Library Preparation kit, followed by probe hybridization, capture enrichment, and sequencing on the Novaseq 6000 platform, generating 400 million reads. The dataset is in raw fastq format.

Dataset EGAD00001010934

ATAC_SEQ_MAIN___PHASE_1

This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001000947

A Chromatin Accessibility Atlas of the Developing Human Telencephalon

Gene expression differs between cell types and regions within complex tissues such as the developing brain. To discover regulatory elements underlying this specificity, we generated genome-wide maps of chromatin accessibility in nine anatomically-defined regions of the developing human telencephalon. Additionally, we defined the histone modification landscape of the prefrontal cortex and generated chromatin accessibility maps of its upper and deep layers. We predicted a subset of open chromatin regions (18%) that are most likely to be active enhancers, many of which are dynamic with 26% differing between early and late mid-gestation and 28% present in only one brain region. These predicted regulatory elements (pREs) are enriched proximal to genes with expression differences across developmental stages, regions, and cortical laminae; they harbor distinct sequence motifs that suggest potential upstream regulators. We leveraged this atlas to predict and validate novel regulatory elements of genes that control cortex laminar identity and genes associated with autism spectrum disorder (ASD). These include enhancers proximal to FEZF2 and BCL11A that were validated in mouse, and an enhancer of ASD gene SLC6A1 containing two functional de novo mutations in individuals with ASD whose enhancer function we validated via CRISPRa. We also include data for transcription factor binding in mid-fetal cortex tissues, using CUT&RUN methods.

Study phs002033

Polymorphisms in the Mitochondrial Genome associated with Bullous Pemphigoid in Germans

This study is the first to interrogate the whole mtDNA in BP patients and controls and to implicate multiple novel mtDNA variants in disease susceptibility. Whole mtDNA of German BP patients (n=180) and age- and sex-matched healthy controls (n=188) were sequenced using next generation sequencing (NGS) technology, followed by the replication study using Sanger sequencing of an additional independent BP (n=89) and control cohort (n=104). While the BP and control groups showed comparable mitochondrial haplogroup distributions, the haplogroup T exhibited a tendency of higher frequency in BP patients suffering from neurodegenerative diseases (ND) compared to BP patients without ND (p= 0.1448, Fisher’s exact test)

Dataset EGAD00001005379

Correlative Genomic Analysis of Durvalumab plus Pazopanib Combination in Patients with Advanced Soft Tissue Sarcomas

We conducted an open-label, phase 2 study to determine the activity of the anti-VEGF receptor tyrosine-kinase inhibitor, pazopanib, combined with the anti-PD-L1 immune checkpoint inhibitor, durvalumab, in unselected advanced sarcomas. In addition, we conducted whole exome and transcriptomic sequencing with pre-treatment tissue biopsy to correlate clinical outcomes with molecular and genomic biomarkers to identify patients who would most likely benefit from the combination treatment.

Study EGAS50000000082

A Prospective Natural History Study of Diagnosis, Treatment and Outcomes of Children with SCID Disorders

Individuals with a recent or new diagnosis of severe combined immune deficiency (including infants who were identified by newborn screening) may be eligible to be enrolled on the PIDTC research study 6901. Speak to your doctor to determine if you or your child may be eligible. Protocol 6901 follows patients with SCID prospectively, meaning the 6901 study enrolls participants where there is a plan to receive a blood and marrow transplant, enzyme therapy, or gene therapy in the future. Patients are then followed according to a schedule set out by the study protocol after the procedure. The times the study requests follow up will be the same as when your doctor would want to be seeing you or your child as part of their regular ongoing medical care. Patients with "leaky SCID", reticular dysgenesis, and Omenn syndrome may also be eligible to participate in 6901. The 6901 research study does NOT dictate how your or your child's doctors should treat you or your child, as the PIDTC recognizes that there are many complex factors that go into this decision. The decision about how you or your child with SCID will be treated is made by your doctor. The 6901 study simply follows how you or your child do over time. There are no experimental therapies on this study. The 6901 study has been open since August 2010, and continues to be open and enrolling patients to the present day. The study plans to enroll approximately 250 patients with SCID. By studying new patients undergoing treatment for SCID, the goal is to learn more about: (1) outcomes from the treatment of SCID in the modern era of medicine, (2) what factors lead to the best long-term outcomes, such as best donor, conditioning regimen, timing of transplant, etc. and (3) what impact newborn screening and the early diagnosis of SCID has had on the long-term outcomes following BMT or gene therapy. A significant amount of information is also being gathered on how and when the immune system recovers after BMT, quality of life for long-term survivors, and about whether children develop normally after treatment. The 6901 study is the largest coordinated prospective study of patients with SCID ever performed. Information that we will learn, both now and in the future, will help doctors and other health professionals to better treat children with SCID. All hospitals within the PIDTC are enrolling patients with SCID on 6901, ensuring that the outcomes are reflective of what happens in the "real world" as opposed to at just one or two large centers.

Study phs001392

Data Use Ontology (DUO)

Data Use Ontology Data Use Ontology at EGA The EGA is committed to its involvement in the work of GA4GH. In an effort to enhance data discoverability and streamline data access, EGA have implemented the use of the Data Use Ontology (DUO), based on consent codes as described in Dyke et al. 2017. The Data Use Ontology codes will be displayed on the live dataset page of your submission to advise any would be requestor on how the data can be used and also to enhance data discoverability as users will be able to search on these codes to find applicable datasets. DUO can be browsed online via the Ontology Lookup Service Learn more reading the Data Use Ontology publication and the GA4GH Machine-Readable Consent Guidance! Check our DAC Portal Take The Tour and learn how to add DUO codes to your policy! Term Shorthand Label Description DUO:0000004 NRES no restriction This data use permission indicates there is no restriction on use. DUO:0000042 GRU general research use This data use permission indicates that use is allowed for general research use for any research purpose. DUO:0000006 HMB health or medical or biomedical research This data use permission indicates that use is allowed for health/medical/biomedical purposes; does not include the study of population origins or ancestry. DUO:0000007 DS disease specific research This data use permission indicates that use is allowed provided it is related to the specified disease. DUO:0000011 POA population origins or ancestry research only This data use permission indicates that use of the data is limited to the study of population origins or ancestry. DUO:0000012 RS research specific restrictions This data use modifier indicates that use is limited to studies of a certain research type. DUO:0000015 NMDS no general methods research This data use modifier indicates that use does not allow methods development research (e.g., development of software or algorithms). DUO:0000016 GSO genetic studies only This data use modifier indicates that use is limited to genetic studies only (i.e., studies that include genotype research alone or both genotype and phenotype research, but not phenotype research exclusively) DUO:0000018 NPUNCU not for profit, non commercial use only This data use modifier indicates that use of the data is limited to not-for-profit organizations and not-for-profit use, non-commercial use. DUO:0000019 PUB publication required This data use modifier indicates that requestor agrees to make results of studies using the data available to the larger scientific community. DUO:0000020 COL collaboration required This data use modifier indicates that the requestor must agree to collaboration with the primary study investigator(s). DUO:0000021 IRB ethics approval required This data use modifier indicates that the requestor must provide documentation of local IRB/ERB approval. DUO:0000022 GS geographical restriction This data use modifier indicates that use is limited to within a specific geographic region. DUO:0000024 MOR publication moratorium This data use modifier indicates that requestor agrees not to publish results of studies until a specific date. DUO:0000025 TS time limit on use This data use modifier indicates that use is approved for a specific number of months. DUO:0000026 US user specific restriction This data use modifier indicates that use is limited to use by approved users. DUO:0000027 PS project specific restriction This data use modifier indicates that use is limited to use within an approved project. DUO:0000028 IS institution specific restriction This data use modifier indicates that use is limited to use within an approved institution. DUO:0000029 RTN return to database or resource This data use modifier indicates that the requestor must return derived/enriched data to the database/resource. DUO:0000043 CC clinical care use This data use modifier indicates that use is allowed for clinical use and care. DUO:0000044 NPOA population origins or ancestry research prohibited This data use modifier indicates use for purposes of population, origin, or ancestry research is prohibited. DUO:0000045 NPU not for profit organisation use only This data use modifier indicates that use of the data is limited to not-for-profit organisations. DUO:0000046 NCU non-commercial use only This data use modifier indicates that use of the data is limited to not-for-profit use. Point to Notice: For the consent code DUO:0000007 where data is restricted to use on a specific disease, please accompany it with an appropriate ontology from MONDO e.g., If the data is restricted to the use of research into juvenile idiopathic arthritis the code should be displayed as DUO:0000007; MONDO:0011429.

Documentation access/data-access-committee/data-use-ontology

Genes associated with pancreas development and function maintain open chromatin in iPSCs generated from human pancreatic beta cells

Current in-vitro islet differentiation protocols suffer from heterogeneity and low efficiency. Induced-pluripotent stem cells (iPSCs) derived from pancreatic beta-cells (BiPSCs) preferentially differentiate towards endocrine pancreas-like cells versus those from fibroblasts (FiPSCs). We interrogated genome-wide open chromatin in BiPSCs and FiPSCs via ATAC-seq, and identified ~8.3k significant, differential open chromatin sites (DOCS) between the two iPSC subtypes (FDR<0.05). DOCS where chromatin was more accessible in BiPSCs (Bi-DOCS) were significantly enriched for known regulators of endodermal development, including bivalent and weak enhancers, and FOXA2 binding sites (FDR<0.05). Bi-DOCS were associated with genes related to pancreas development and beta-cell function, including transcription factors mutated in monogenic diabetes (PDX1, NKX2-2, HNF1A; FDR<0.05). Moreover, Bi-DOCS correlated with enhanced gene expression in BiPSC-derived definitive endoderm and pancreatic progenitor cells. Bi-DOCS therefore highlight genes and pathways governing islet-lineage commitment, which can be exploited for differentiation protocol optimisation, diabetes disease modelling, and therapeutic purposes.

Study EGAS00001002591

Genotype data from 'Dense sampling of ethnic groups within African countries reveals fine-scale genetic structure and extensive historical admixture.'

Previous studies have highlighted how African genomes have been shaped by a complex series of historical events. Despite this, genome-wide data has only been obtained from a small proportion of present-day ethnolinguistic groups. By analysing new autosomal genetic variation data of 1333 individuals from over 150 ethnic groups from Cameroon, Republic of the Congo, Ghana, Nigeria and Sudan, we demonstrate a previously underappreciated fine-scale level of genetic structure within these countries, for example correlating with historical polities in western Cameroon. By comparing genetic variation patterns among populations, we infer that many northern Cameroonian and Sudanese groups share genetic links with multiple geographically disparate populations, likely resulting from long-distance migrations. In Ghana and Nigeria, we infer signatures of intermixing dated to over 2000 years ago, corresponding to reports of environmental transformations possibly related to climate change. We also infer recent intermixing signals in multiple African populations, including Congolese, that likely relates to the expansions of Bantu language-speaking peoples.

Study EGAS00001006944

Best Endovascular vs. Best Surgical Therapy in Patients With Critical Limb Ischemia (BEST CLI-BioLINCC)

Data Access NOTE Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives To compare the effectiveness of surgical treatment to the effectiveness of endovascular treatment in adults with chronic limb-threatening ischemia who are eligible for both treatment options. Background Peripheral artery disease (PAD) affects more than 200 million people worldwide. A portion of those individuals develop chronic limb-threatening ischemia (CLTI). CLTI is associated with severe health outcomes. CLTI is defined by ischemic foot pain at rest, ischemic ulcerations, or gangrene. Treatment for CLTI includes revascularization to improve limb perfusion and limit the risk of amputation. However, the choice of surgery or endovascular therapy for revascularization varies greatly. The extent to which this variability affects clinical outcomes in patients with CLTI is unknown. The BEST-CLI trial was initiated to determine whether endovascular revascularization was superior to surgical revascularization in patients with CLTI. Participants A total of 1434 participants with a single segment of great saphenous vein comprised cohort 1. Of these, 718 participants were randomly assigned to the surgical treatment group and 716 participants were randomly assigned to the endovascular therapy group. A total of 396 participants needing an alternative conduit comprised cohort 2. Of these, 197 participants were randomly assigned to the surgical treatment group and 199 participants were randomly assigned to the endovascular therapy group. Design BEST-CLI was an international, randomized, open-label trial. Participants were assigned to one of two cohorts based on the availability of a single segment of great saphenous vein. Participants in both cohorts were randomly assigned to either surgery or endovascular therapy. Follow-up was performed at 30 days after the procedure, 3 months, 6 months, and every 6 months thereafter up to 84 months after randomization. Telephone visits in lieu of clinic visits were planned at 30 months and every 12 months thereafter and at the end of the trial. Participants were followed for major adverse cardiovascular events (myocardial infarction, stroke, or death from any cause), quality of life, level of pain, and performance on the six-minute walk test. The primary outcome was a composite of major adverse limb events or death from any cause. A major adverse limb event was defined as above ankle amputation of the index limb or a major index-limb reintervention (new bypass, interposition graft revision, thrombectomy, or thrombolysis). Conclusions Among patients with CLTI who had an adequate great saphenous vein for surgical revascularization (cohort 1), the incidence of a major adverse limb event or death was significantly lower in the surgical group than in the endovascular group. Among the patients who lacked an adequate saphenous vein conduit (cohort 2), the outcomes in the two groups were similar. Farber A, Menard MT, Conte MS, et al. Surgery or Endovascular Therapy for Chronic Limb-Threatening Ischemia. N Engl J Med. 2022;387(25):2305-2316. PMID 36342173

Study phs003844

RNAseq samples of patients with anti-PD-1 resistant HNSCC from a non-randomized, open-label phase 1b clinical trial

Immune checkpoint blockade (ICB) is an effective treatment for a subset of patients with head and neck squamous cell carcinoma (HNSCC); however, the majority remain refractory. In a nonrandomized, open-label Phase 1b clinical trial, participants with recurrent and/or metastatic (R/M) HNSCC who had progressed on ICB were treated with low-dose 5-azacytidine (5-aza) daily for either 5 or 10 days, in combination with durvalumab and tremelimumab. The primary objective was to determine the biologically effective dose of 5-aza. In this study, RNA sequencing (RNA-seq) was performed on baseline and on-treatment samples from eight participants, and transcriptomic changes were analyzed to assess the impact of low-dose 5-aza treatment.

Study EGAS50000000728

Center for Common Disease Genomics (CCDG)-Cardiovascular: University of Pennsylvania Cohort

The National Human Genome Research Institute (NHGRI) has funded the Centers for Common Disease Genomics (CCDG), a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes and to better understand the general principles of genomic architecture underlying common, complex inherited diseases. This study of early onset cardiovascular disease and metabolic risk contains data derived from the whole genome sequence data of individuals participating in Penn Medicine's BioBank.

Study phs001502

EGA synthetic data

Synthetic Data One of the limitations in genomics research is that human genomics data is not openly available; access must be controlled according to participant consent agreements and data protection regulations such as GDPR. Obtaining authorization to access such data can sometimes take a long time, resulting in delays to important research work. In this context, synthetic genomic and phenotype data can be useful resources for researchers to avoid these delays. Synthetic data are artificially generated datasets, often created with algorithms, which can be used without the need for authorization to test new products and tools, build technical demonstrators, validate data models, and train AI models. The EGA provides access to synthetic cohort datasets augmented with rich synthetic metadata that overcomes these real data usage restrictions. Whilst synthetic datasets are not included in the general EGA mandate and services, we can consider such submissions and evaluate their acceptance on the basis of their unique use cases not already covered by existing synthetic datasets. Access to synthetic data studies is managed by the EGA Helpdesk Data Access Committee. Study ID Title Located in EGAS00001002472 CINECA synthetic cohort EUROPE UK1 referencing fake samples Central EGA EGAS00001005591 Synthetic data - Genome in a Bottle Central EGA EGAS00001005042 Test Study for EGA using data from 1000 Genomes Project - Phase 3 Central EGA EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Central EGA EGAS50000000190 EOSC4Cancer Synthetic Colorectal Cancer Genomic data Central EGA EGAS50000000086 Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023 Federated EGA Sweden EGAS50000000678 Synthetic - GDI synthetic data Federated EGA Spain

Documentation synthetic-data

Cardiogenics_Custom_Pools - Agilent SureSelect

The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

Dataset EGAD00001000397

Nimblegen

The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

Dataset EGAD00001000398

Gut microbiome dynamics unravelled with metagenomics sequencing

It has been already several years since we discovered that microbial therapeutics like Faecal Microbiota Transplantation can be used to treat Clostridium difficile infection (CDI) and Inflammatory bowel disease (IBD) with great success. The concept has challenged us to test the limits of our knowledge with the perspective to improve health in the most diverse conditions like Parkinson disease, depression, autism and obesity, just to mention a few. Note: the figure belongs to the original paper and is owned by the authors. Allyson L.Bird and colleagues from Genentech Inc. (San Francisco) recently published an interesting study building up on the key concept that “As microbial therapeutics are increasingly being tested in diverse patient populations, it is essential to understand the host and environmental factors influencing the microbiome.” The authors of this work analysed 1359 gut microbiome samples using shotgun metagenomics sequencing. The results of the comparison done between microbiota composition across the different groups showed that biological sex is the strongest driver of diversity, while aging (age range studied: 20–69) appears to be the second factor. As smartly outlined in the authors’ own graphical abstract (figure to the left), Bacteroidota species consistently increased with donors' age while Actinobacteriota species, including Bifidobacterium, decreased. This study also integrated data from oncological patients to draw cancer-related evidences. After correcting the biases for technical and geographic differences, they found that cancer patients show significantly altered gut bacterial communities compared with their healthy counterparts. Eg. E.coli was found to be increased in cancer patients together with Bacteroidota/Firmicutes ratios. By comparing sequential samples taken from the same donors (413) within short-distance time points, the authors found that in the short term, intra-individual differences were less than the inter-individual ones, indicating a certain community stability being the norm. One of the pivotal points from this interesting study is that the data proceeds from extremely well-defined and selected donors. Specifically, the data for 949 selected healthy donors came from the Milieu Intérieur (MI) Consortium and extensive metadata, including demographic variables, serological measures, dietary information, and systemic immune profiles, are available. This precise stratification allowed for the robust detection of smaller changes, compared to former works. All sequencing data has been deposited in the EGA archive under the accession number EGAS00001004437. Enjoy this amazing open access paper published in the Experimental Journal of Medicine on January 2021.

Blog gut-microbiome-dynamics-unravelled

Comprehensive Genomic and Transcriptomic Analysis of Rare Cancers for Guiding of Therapy (H021)

Here we analyzed the molecular profiles and clinical outcomes of 1,310 patients (proportion of rare cancers, 75%) enrolled in a prospective observational study by the German Cancer Consortium that applies whole-genome/exome and RNA sequencing to inform the care of adults with incurable cancers. Based on 472 single and six composite biomarkers, a cross-institutional molecular tumor board provided evidence-based management recommendations, including diagnostic reevaluation, genetic counseling, and experimental treatment, in 88% of cases. Recommended therapies were administered in 362 of 1,138 patients (31.8%) and resulted in significantly improved response and disease control rates (23.9% and 55.3%, respectively) compared to previous therapies, translating into a progression-free survival ratio >1.3 in 35.7% of patients.

Study EGAS00001004813

Genetic Causes of Congenital Anosmia

The Genetic Causes of Congenital Anosmia study was designed to provide a list of candidate genes that are potentially causal for isolated congenital anosmia (ICA), a rare inherited disorder where individuals lack a sense of smell from birth in the absence of a known genetic syndrome (i.e. Kallman's syndrome). This study includes 193 participants from 18-87 years of age, divided into two cohorts: family and non-family. Genetic data from the family cohort was analyzed in a case-control family design to generate a list of 162 candidate genes for ICA. A targeted search for variants in this list of genes was then conducted in the non-family cohort to create a prioritized list of genes for further study. Ten unrelated families were recruited for the family cohort for a total of 52 participants, 25 of which had anosmia. The non-family cohort consisted of 141 anosmic individuals. 3 additional normosmic participants from incomplete families were collected, one of whom has a participating family member in the non-family cohort, and so has data provided here. Data collection was conducted remotely, resulting in 146 participants recruited from the United States, and 48 recruited internationally from ten different countries. Participants were interviewed for their anosmia status and to confirm that they had no known genetic syndromes. Participants also completed the University of Pennsylvania Brief Smell Identification Test (BSIT; Doty et al., 1984) to confirm their anosmic/normosmic status and provided a saliva sample for whole exome sequencing (WES). Participants who had family members with anosmia provided pedigree information via interview. Data submitted to dbGap include whole exome sequences from 194 individuals (163 anosmic) conducted with Illumina HiSeq2500 and Illumina NovaSeq next generation sequencing technologies. Family pedigree information for the 10 participating families and all participants in the non-family cohort who have non-participating anosmic family members was also included. Our goal was to provide a resource for further research into the genetics of isolated congenital anosmia and to aide in the understanding of this disorder, as well as human olfaction, in general. The WES data provided could be further analyzed for polygenic interactions, additional non-targeted analysis on the non-family cohort, or combined into databases of other anosmic populations for further gene targeting or selection.

Study phs003328

Chromatin Profiling in Twins (2019-08-21)

50 lymphoblastoid cell lines of adult female Twins which are part of the MuTHER study, processed with the FAIRE assay in order to generate maps of open chromatin. . This dataset contains all the data available for this study on 2019-08-21.

Dataset EGAD00001005273

The National Heart, Lung, and Blood Institute (NHLBI)-funded Next Generation Genetic Association Studies (NextGen) Consortium: Phenotyping Lipid traits in iPS derived hepatocytes Study (PhLiPS Study)

The goal of the PhLiPS study is to create a library of induced pluripotent stem cell (iPSC) lines and iPSC-derived hepatocytes of diverse genotypes for use in metabolic profiling and interrogating lipid phenotypes. These cell lines were created as a part of the Next Generation Genetic Association Studies (Next Gen) Program, which was a five-year, $80 million program to investigate functional genetic variation in humans by assessing cellular profiles that are surrogates for disease phenotypes. To achieve this, researchers from multiple institutions across the U.S. were awarded grants to derive iPSC lines from more than 1,500 individuals representing various conditions as well as healthy controls for use in functional genomic ("disease in a dish") research. This extensive panel includes a diverse set of age, gender, and ethnic backgrounds, and therefore will be an invaluable tool for evaluations across demographics. Further enhancing the utility of these cell lines are data sets such as phenotyping, GWAS, genome sequencing, gene expression and -omics analyses (e.g., lipidomic, proteomic, methylomic) that can be matched to the cell lines. The PhLiPS Study focuses on individuals free of cardiovascular disease or with lipoprotein metabolism disorders in the community served by the Hospital of the University of Pennsylvania.

Study phs001341

SDR-seq_06_BCL

SDR-seq_BCL data access. Two follicular lymphoma (FL) primary patient samples and one germinal center subtype diffuse large B-cell lymphoma (GCB) primary patient sample. FL1 and GCB1 are sequenced in Run1. FL2 is sequenced in Run2.

Dataset EGAD50000000551

Mapping Genes for Mammographic Density

We recruited 1,521 women from the Old Order Amish (OOA) population of Lancaster County, Pennsylvania, with the primary goal of identifying genetic factors that influence mammographic density. All women were between the ages of 40 and 88 years, with a mean of 54 years. Additional study design details, including eligibility criteria, are described elsewhere (Douglas et al., 2008). The present-day OOA of Lancaster County are the descendants of approximately 550 individuals from central Western Europe who immigrated to the U.S. in the early eighteenth century. All living individuals derive from a single, 14-generation pedigree (Lee et al., 2010). Although the OOA are a genetically closed founder population, allele frequencies and LD profiles are remarkably similar between the OOA and U.S. participants in the International HapMap project (HapMap CEU) for common SNPs (MAF>/=5%) (Van Hout et al., 2010). We recently completed genome-wide linkage and association analyses of mammographic density, including dense and non-dense areas of the breast and the ratio of dense to total area of the breast. Summary-level data from our GWAS are available here and through the Marker of DEnsity (MODE) Consortium.

Study phs000604

Rapid Early Action for Coronary Treatment (REACT-BioLINCC)

Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: This multicenter controlled community study developed and evaluated the impact of a community educational intervention program on participant delay time from onset of symptoms of an acute myocardial infarction (AMI) to arrival at a hospital emergency department.Background: Although early reperfusion or thrombolytic therapy can reduce morbidity and mortality following an AMI, delayed access to medical care in participants is relatively common. Mean delay times from symptom onset to hospital arrival range from more than 4 hours to 24 hours, and the largest component of prolonged delay is participant recognition and action.Participants: A total of 20 communities from 5 field centers in the U.S. were pair-matched (10 pairs) according to geographic proximity and demographic characteristics. After initiation of a 4 month baseline surveillance period, one community in each pair was randomly selected to receive the intervention. The baseline surveillance period was followed by an 18 month community intervention and surveillance period. The community surveillance captured a total of 59,944 adults aged 30 years or older presenting to hospital emergency departments with chest pain, of whom 20,364 met study criteria for suspected acute coronary heart disease (CHD) at admission and discharged with a CHD diagnosis.Conclusions: Delay times were decreased in the intervention and reference communities. The results showed that the multicomponent community intervention program did not differentially reduce delay time from onset of AMI symptoms to arrival at a hospital, but did significantly increase the use of Emergency Medical Services by these participants in the intervention communities. (PMID:10872014).

Study phs003885

Transcriptomic and epigentic analysis of human peripheral blood NK cell subsets revealing role of Bcl11b in differentiation

Transcriptomic analysis of seven human peripheral blood NK cell subsets and three T cell subsets purified from healthy cytomeglovirus seropositive donors. Epigenetic analysis including identification of open chromatin and active enhancer elements confirms key regulatory factors defining an NK cell differentiation axis. Chromatin-immunoprecipitation sequencing reveals contribution of key transcription factors associated with NK cell differentiation including Bcl11b.

Study EGAS00001005025

Ribosome profiling shows variable sensitivity to detect open reading frames for conventional and different types of cryptic T cell antigens

The aim of the study was to explore the sensitivity of ribosomal profiling to detect ORFs for cryptic antigens targeted by T cells in immune responses. Ribosomal profiling was performed for six EBV-LCLs. Detection of conventional and cryptic MiHA-encoding ORFs was compared. The data showed that open reading frames (ORFs) for conventional MiHAs as well as cryptic MiHAs in upstream ORFs were frequently detected with similar sensitivity. However, only a limited number of MiHAs in in reading frames alternative to protein-coding sequences and no ORFs derived from long non-coding RNAs were detected. In conclusion, Ribo-seq for identification of antigen-encoding ORFs is useful to screen for cryptic antigens in upstream ORFs as potential targets for immunotherapy.

Study EGAS50000000322

Development and Validation of a Prognostic and Predictive 32-Gene Signature for Gastric Cancer

We applied this signature to a 567-patient GC cohort to establish genomic-based molecular subtypes and then used a support vector machine to build a molecular subtype-based risk-scoring model. Both source code and supplementary datasets for risk score prediction are available at https://github.com/hwanglab/Yonsei_gastric_cancer_32genes.

Dataset EGAD00001008091

CTSP: Clinical Trial Sequencing Project

For the Clinical Trials Sequencing Project (CTSP), National Cancer Institute (NCI) will utilize whole genome sequencing and/or whole exome sequencing in conjunction with transcriptome sequencing to try to identify recurrent genetic alterations (mutations, deletions, amplifications, rearrangements) and/or gene expression signatures that would be important to the hypothesis(es) submitted by the investigators. The samples will be processed and submitted for genomic characterization using pipelines and procedures established within The Cancer Genome Analysis (TCGA) project. Data analysis will be performed as a collaboration between the National Clinical Trials Network (NCTN) Group and its investigators submitting the proposal. The investigators at the NCI-sponsored Genomic Data Analysis Center (GDAC) will characterize the samples. The NCTN Group will be responsible for providing the clinical data needed for the proposal to the open clinical system maintained by NCI CCG's Biospecimen Core Resource (BCR) at Nationwide Children's Hospital in Columbus, Ohio. The project team (Network Group/investigators and GDAC) will analyze the data together. Additionally, clinical and genomic data related to the analyses will also need to be registered by NCI and will be made available to qualified researchers via a controlled-access database (e.g., dbGaP) upon publication of the primary analysis described in the study proposal. A substudy description and its molecular data information are provided under its own page: phs001184 CTSP Diffuse Large B-Cell Lymphoma (DLBCL) CALGB 50303

Study phs001175

Study of Controlled Human Malaria Infections to Evaluate Protection After Intravenous or Intramuscular Administration of PfSPZ Vaccine in Malaria-Naive Adults

The study was performed to evaluate whole-blood transcriptomic profiles via RNA-seq before, during, and after immunization with the PfSPZ Vaccine in malaria-naïve, health adults enrolled in VRC 314 (NCT02015091). VRC 314 was designed as an open-label evaluation of the safety, tolerability, immunogenicity, and protective efficacy of the PfSPZ Vaccine. This study was designed to substantiate the initial results with the IV vaccination route for protection against CHMI that was observed in VRC 312 (NCT01441167). Based on the potential importance of dose and schedule in optimizing sustained immunity with this vaccine, an increase in PfSPZ IV dosage on schedules of 3 to 5 vaccinations was evaluated for protection against CHMI conducted early (about 3 weeks) and late (about 24 weeks) after completion of vaccinations. To assess if a higher dose given by another route confers protection, one group received PfSPZ IM, with half of the amount administered in each arm on a schedule with 4 vaccination. The primary objectives of the study were related to the safety and tolerability of vaccinations by the IV and IM routes of administration and protection against Plasmodium falciparum (Pf) challenge performed via a well-established CHMI procedure early (2-4 weeks) after completing schedules of 3 to 5 vaccinations. The secondary objective was related to the durability of protection at 20-26 weeks after the last vaccination, and exploratory objectives were related to the immunogenicity of the PfSPZ Vaccine and identifying potential immune correlates of protection. To further determine potential molecular correlates of immunogenicity and/or protection, RNA-seq was performed on whole blood collected from subjects in all dose groups at time points before, during, and after immunization.

Study phs002423

A Phase I Study with a Personalized Neoantigen Cancer Vaccine in Melanoma

Effective anti-tumor immunity in humans has been associated with presence of T cells targeting neoantigens that arise from non-silent tumor-specific mutations. Here we conducted whole-exome sequencing of tumor and normal cells from individual patients to identify mutations. We assessed the expression of mutated alleles by RNA-sequencing of tumor. We demonstrated the feasibility, safety and immunogenicity of a vaccine that targets up to 20 personal neoantigens predicted to be presented by the autologous patient tumor.Antigen-specific CD8+ T cells that can recognize and eliminate cancer cells play a crucial role in anti-tumor immune responses. Here we conducted single-cell sequencing of cells infiltrating melanoma specimens originating from 4 patients and determine the TCR clonality of the CD8+ tumor infiltrating cells. We investigated the relationship between T cell clonality and phenotypic cell states coupling single-cell transcriptome to single-cell TCR seq. The surface expression of a panel of protein was detected in parallel using CITE-Seq antibodies. Sorted tumor and peripheral blood specimens were processed in parallel.In order to discover cancer antigens derived from annotated and unannotated protein-coding regions of the genome, we carried out matched ribosome profiling (Ribo-seq), RNA-sequencing, and whole genome sequencing on one of the patients, as well as Ribo-seq on an additional patient. We used it to discover novel or unannotated open reading frames (nuORFs), their expression levels, as well as somatic mutations within them to predict potential neoantigens.

Study phs001451

Age related Macular Degeneration (AMD) - Michigan, Mayo, AREDS, Pennsylvania (MMAP) Cohort Study: Association and Sequencing Studies

Age-related Macular Degeneration (AMD) is a leading cause of incurable blindness in people over the age of 65. AMD is a late-onset multi-factorial neurodegenerative disease and its pathogenesis involves interaction of genetic and environmental factors. Several chromosomal regions have been associated with AMD susceptibility through linkage analysis (Swaroop et al., 2009). More recent studies provide strong evidence that variants within the CFH gene cluster on chromosome 1 and at/near LOC387715/ARMS2 on chromosome 10 are strongly associated with the disease. Variants at other genes including C2/BF, C3, CFI and APOE4, also contribute to AMD susceptibility. Our primary goals are to identify genetic variants and haplotypes that are associated with AMD. The underlying hypothesis is that DNA variation(s) in multiple genetic susceptibility loci will predispose individuals to AMD pathogenesis, and comparison of DNA of cases and controls should identify these susceptibility variants. Our studies are focused on the genetic analysis of advanced AMD and should provide novel insights into disease diagnosis, progression and pathology. We have assembled a collaborative group of researchers from the University of Michigan, Mayo Clinic, University of Pennsylvania, and the AREDS group including National Eye Institute intramural investigators, who collected clinical data and DNA from a large number of patients affected with AMD and from unaffected controls. The primary source of funding was National Eye Institute. Study 1: To identify genetic variants and haplotypes that are associated with AMD, we submitted and obtained usable genotyping data on 2185 patients and 1155 controls from the Center for Inherited Disease Research (CIDR). Study 2: To identify rare coding variants associated with a large increase in risk of AMD, 10 candidate loci spanning 57 genes were sequenced in 2,335 cases and 789 controls. Probes were designed to capture 96.5% of the coding sequence and 35% of total locus sequence, generating an average 123Mb of on-target sequence per individual at 127x average depth. Substudies: phs000182 AMD-MMAP Cohort Study: A Joint Genome-Wide Asscociation Study phs000246 Fuchs' Corneal Dystrophy GWAS phs000457 MMAP Methylation in AMD phs000685 Age-Related Macular Degeneration Targeted Sequencing Study

Study phs000684

Germline variants in patients with rare cancers and their implications for precision cancer medicine: experiences from the Multicenter MASTER Trial by the German Cancer Consortium (HIPO_021)

The era of precision oncology entails an increasing amount of molecular data from tumor sequencing in research and diagnostics. In this setting, germline variant analysis may add clinical benefits for patients and family members. In this study, we evaluated germline variants from genome/exome matched tumor-blood sequencing in 1.485 advanced cancer patients within a prospective observational study carried out by the German Cancer Consortium. Included patients had cancers of rare entities (79.2%) or were under the age of 51 at first diagnosis (76.6%). Ten percent of the patients harbored pathogenic germline variants in 35 tumor predisposition genes with autosomal-dominant inheritance such as BRCA1, BRCA2, TP53, RB1, CHEK2, ATM, PALB2, SDHB etc., while 4.6% of the patients were carriers of pathogenic germline variants in 18 genes with autosomal-recessive inheritance of tumor predisposition. Based on pathogenic germline variants, 14% of the patients received genetic counselling recommendations in the molecular tumor board report. Forty five percent of pathogenic germline variants supported a molecular treatment recommendation, which was implemented for 28 patients. Furthermore, we compared our approach and results to previous studies, broadening the insight into pan cancer germline findings but also revealing differences between studies on various levels, such as cohort demographics, tumor entities, gene nominations, variant detection and variant interpretation. Our data support the importance of germline variant interpretation in precision oncology studies for patients and their families, if applicable. However, guidelines for evaluation and reporting of germline variants in the context of genetic tumor profiling need to be established and further research on the relevance of germline mutations as biomarkers for treatment recommendations is needed.

Study EGAS00001005537

PAGE: Global Reference Panel

Stanford contributed samples to the PAGE study that can act as a population reference dataset across the globe. Therefore this dataset includes reference individuals, without phenotypes, chosen to help infer ancestry that will help us understand the diverse samples available in PAGE. The complete dataset comprises individuals of European, African, Asian, Oceanian, and Native American descent, from a total of over 50 populations. A subset of these individuals from Puno, Peru and Easter Island (Rapa Nui), Chile, are included in the PAGE samples that were whole genome sequenced in 2015. Additional details are available in the Study Acknowledgments. The Global Reference Panel comprises 6 sample sets: A population sample of Andean individuals primarily of Quechuan/Aymaran ancestry from Puno, Peru A population sample of Easter Island (Rapa Nui), Chile Individuals of indigenous origin from Oaxaca, Mexico Individuals of indigenous origin from Honduras Individuals of indigenous origin from Colombia Individuals of indigenous origin from the Nama and Khomani KhoeSan populations of the Northern Cape, South Africa In addition, we genotyped publicly available samples that will be hosted on the Bustamante lab website (https://bustamantelab.stanford.edu/). These comprise large public datasets to provide an open reference dataset for the world: The additional related individuals from the Americas in the Human Genome Diversity Panel (H952) plus all additional samples from the Americas A subset of the unrelated individuals from the Maasai in Kinyawa, Kenya (MKK) dataset from the International Hapmap Project hosted at Coriell Additional samples will be available for restricted use with a data access agreement with the Bustamante Lab. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study (phs000356).

Study phs001033

Beacon v2 and Federated EGA, part of the GDI project Starter Kit to enable access to genomic and phenotypic data across borders

The European Genomic Data Infrastructure project has released a ‘Starter Kit’ based on the rare disease and cancer proof-of-concepts from the Beyond 1 Million Genomes (B1MG) project. The Starter Kit, freely available to any interested parties, contains a set of software applications and components co-developed by the 20 GDI nodes and based on open community standards from the Global Alliance for Genomics and Health (GA4GH). Products in the Starter Kit give all countries the technical capability to access synthetic genomic and phenotypic data across borders. The image above shows the full workflow of the GDI Starter Kit user journey. The dotted circles are not included in the Starter Kit yet The EGA’s work is represented in the Starter Kit with Beacon v2 and Federated EGA among the software applications and components. About Beacon v2 Beacon is a protocol for data discovery. This API allows the search of genomic variants and associated information without breaching the datasets privacy. The European Genome-phenome Archive (EGA) is a key contributor to the Beacon v2 Protocol, the Beacon v2 Reference Implementation (B2RI) and the EGA Beacon(s). About Federated EGA The Federated EGA network offers a tool for data storage and sharing. Officially launched in 2022, this network of connected resources enables transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. The Federated EGA Onboarding Website contains all the information related to the establishment of a Federated Node.

Blog beacon-v2-and-federated-ega-part-of-the-gdi-project-starter-kit

What is a DAC?

What is a DAC? Given the complexity, scale, and diversity of global submitters and studies, the EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA. The European Commission defines a data controller, in the General Data Protection Regulation (GDPR), as the person that determines the purposes for which and the means by which personal data is processed. A Data Access Committees, commonly referred to as DACs, comprise on or more individuals (or data controllers) that review data access requests and make decisions on who can access personally identifiable genetic, phenotypic, and clinical data deposited at the EGA. Therefore, the members of a DAC should be individuals who have the authority to approve data access requests. The animation describes how you can authorise access to your sensitive data with the help of Data Access Committee and Authorisation tool. Acknowledgement to CSC - IT Center for Finland, Elixir Finland, Elixir Europe. Frequently Asked Questions How can I create a Data Access Committee? How can I create a Data Access Committee? The members of a DAC can come from different areas of expertise, such as data management, data analysis, information technology, legal and compliance, subject matter experts, privacy and security, and representatives from the organisations or individuals that provide data to the DAC. The specific members of a DAC can vary depending on the needs of the organisation and the type of data being managed. The EGA strongly suggests checking with your organisation to align with its regulations How should a DAC be named? The chosen name must be informative to the applicant. For example, internal identifiers, such as grant numbers, should not be used. Individual PI names should also not be used. DAC's are often named after the organisation or department of the data source. Browse the full list of DAC names currently in the EGA. How can I become an EGA DAC contact? To register a DAC at the EGA you must create first as an EGA user. Once your EGA user has been approved by the Helpdesk team, you will be able to log in to the DAC Portal. How can I register a DAC? To register a DAC, follow the DAC Portal instructions. You will be required to provide a DAC name, name of the individual(s) that make up your DAC and contact details for your DAC including your Institutional email(s). Wherever possible, the DAC should make sure that all points of contact are readily available and able to answer any initial data requests/queries in < 2 weeks. Once your DAC is registered, you will have to wait upon the validation from our Helpdesk team. As soon as all the validations have been completed, your DAC will be activated. Alternatively, you can also establish a DAC at the EGA during a programmatic submission through Webin API. Which are the possible roles of a DAC contact? There are two possible roles for DAC contacts: member and admin. An admin has additional privileges compared to a member: An “admin” can manage data requests, create and edit policies, edit the content of the DAC, add or remove contacts, and decide the role of each contact. A “member” can manage data requests and create policies. However, a member does not have permission to modify DAC details, edit information from policies where they are not admins, or add/remove contacts. There is no limit to the number of admins in a DAC, and each admin is responsible for deciding who should have editing privileges. This allows for a more decentralised and democratic approach to managing the DAC. How can I modify the information of a DAC? To modify a DAC, follow the instructions here. Keep in mind that only DAC contact with an admin role can modify the information of a DAC. If your DAC was registered before the lauch of the DAC Portal, and its ID is EGAC0 (not EGAC5), you must use the programmatic submission to modify it. Please, do not hesitate to contact our Helpdesk team if you need help with this! To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What’s the link between DAC, policy and dataset? A dataset is linked to one single policy. At the same time, one policy has a one to one relationship with a DAC. In this example, you can see that in this dataset page, we are only showing the information of one DAC (1 dataset - 1 DAC). However, the ratio of objects does not work the same in the other direction. One DAC can own multiple policy objects. And each policy object can be reused in several datasets. Thus, one DAC can manage one or more datasets. In this example, you can see that in this DAC page, we are showing all the datasets that are managed by one DAC (1 DAC - >400 datasets). EGA Data Access Committee Best Practices Which are the EGA DAC best practices? Refer to DAC Best Practices What happens if a DAC member changes institutions? EGA is committed to the protection and ownership of the data stored in our systems. We respect the institution's ownership of the data, and as such, if a DAC member changes institutions, the ownership of the data will not be transferred to the new institution. Therefore, before changing institutions, we request that the DAC contact add a new member who will replace them once they no longer work at the institution. This ensures that the data remains protected and is accessible to authorised personnel at the institution. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What happens if EGA detects an unresponsive DAC? EGA defines an unresponsive DAC as a DAC with one or more contacts who do not respond to data access requests. EGA has procedures in place to identify these types of DACs, escalate the issue, and attempt to reassign the DAC to a responsive contact. This is a crucial step in ensuring that data can be accessed and utilised by researchers. If EGA identifies an unresponsive DAC, the organisation will first try to resolve the issue by escalating it to the appropriate parties. This may involve attempting to reassign the DAC to a more responsive contact. Unfortunately, in situations where we cannot reassign the DAC, the dataset will be withdrawn from the public website and the files will be removed from our system. If an EGA ID is referenced in a publication, the EGA will take extra steps to ensure that the public is made aware of the data's unavailability. I don't want to receive an email notification for pending requests. How can I do that? If you are an EGA DAC with pending requests, you will always receive emails for new data access requests. However, the EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! How can I manage data access requests? What documentation does the DAC need to provide? Each dataset that is submitted to the EGA must be linked to a policy object. The policy is a Data Access Agreement (DAA), which defines the terms and conditions of using the dataset, such as how the data files should be stored once downloaded or details of publication embargoes that should be observed by the approved user. As part of the Data Access Agreement, information regarding the application can be captured to help inform the DAC when making its decision. For example, requestors could be asked to provide a proposed title for their research and a proposal of how the data will be used. By asking for provision of such information the DAC can be assured that the requestor fully understands any consents associated with the data. It is important that accounts created at the EGA, are created solely for those individuals that will be downloading the data from the EGA. As part of the data access request, we strongly encourage you to identify individuals that will need an account at the EGA in order to prevent sharing of login details, which is strictly prohibited under EGA user account policy. Such information can easily be captured in the DAA. NOTICE The data access agreement template below is provided for guidance only and should be adapted as you see fit to suit your own purpose. In the interest of promoting data sharing, we suggest that if an agreement cannot be met around clause 19 in this example that both parties should agree to remain silent, and that the clause should be removed from the agreement. Example DAA How can the DAC provide the DAA? The DAC should provide their own DAA when registering a policy. Data requestors will download this document and should fill it in and send it back to the DAC. Data access decisions should be based on such documentation. The DAA can be downloaded through the request data webpage. Once it has been filled in, the signed copy of the DAA can be uploaded back to the request data webpage and sent to the DAC for review. How can I grant access to the data? Once you receive a data access request, you can login to the DAC Portal. In this portal you will see all your pending requests and will be able to grant or decline access to the requestors. I am a member of the Data Access Committee. Could I approve somebody else to deal with the requests on my behalf? If you want to delegate data access decisions to someone else, make sure that the individual's account is officially registered as a member of the DAC. Remember that a DAC contact with an "admin" role can always add new members to an existing DAC, remove members, and modify contact details through the DAC Portal. Can I automatise the process of managing data access requests? The answer is yes! You can use a programmatic approach using our DAC API! Check out the DAC API specification! Data Breach What should a DAC do if they suspect a breach? If a DAC suspects a data breach of one or more of their datasets, they should immediately contact the EGA Helpdesk team at this link. The DAC must provide the following information when contacting the EGA Helpdesk team: A list of affected datasets An estimated date of the data breach (or interval of dates) A list of unauthorised users who accessed the data (if available). Otherwise, they can provide a list of authorised users for the affected datasets Any observations they would like to raise to the EGA team Once the DAC has contacted the EGA team, we will respond within 48 hours (please allow some leeway during peak times) and activate our data breach protocol. What can I expect from the EGA if they detect a breach? Once the EGA determines that a security incident has occurred, we will notify all DAC members that a data breach has been detected, and take steps to contain the incident. Containment approaches may include: Revoking a data provider's access to the EGA resources, such as by changing passwords. Removing affected EGA datasets from distribution, such as by withdrawing a dataset. Disabling certain functions or services, such as the EGA ingestion pipeline. Shutting down the system or disconnecting it from the network. After the incident has been contained, the EGA will determine whether it is necessary to eradicate components related to the incident. Finally, the EGA will enable recovery of the service to normal operation and confirm that all services are functioning normally.

Documentation access/data-access-committee/what-is-dac

National Institute of Dental and Craniofacial Research (NIDCR) Sjögren's International Collaborative Clinical Alliance (SICCA): Center for Inherited Disease Research (CIDR) Genome-Wide Genotyping

The Sjögren's International Collaborative Clinical Alliance (SICCA) is a multisite observational cohort study that recruited a large cohort of geographically diverse participants. Enrollment of participants began in late 2004 at five (one domestic and four international) sites, in which all groups used the same protocol-directed methods to provide uniform evaluations; collect oral, ocular, and rheumatologic data; and collect specimens. The sites were located at the University of Buenos Aires, Argentina; Peking Union Medical College, Beijing, China; Rigshopitalet (formerly at Glostrup Hospital), Copenhagen, Denmark; Kanazawa Medical University, Ishikawa, Japan; King's College, London, UK (joined in 2007); and the University of California, San Francisco (UCSF). In 2009, Aravind Eye Hospital, Madurai, India; Johns Hopkins University, Baltimore, MD; and University of Pennsylvania, Philadelphia, PA were added as additional SICCA sites. UCSF is the coordinating center for SICCA. All specimens and data collected for SICCA are housed at UCSF. To facilitate the research focused on understanding the genetics of Sjögren'sSjögren's syndrome, high-density SNP genotype data and SICCA clinical information are being made available to the research community. This includes participants recruited from all SICCA research groups (RG). These participants (3,382), blood relatives (439), and unrelated healthy controls (25) had their whole blood or saliva sample (Oragene) extracted for DNA for the GWAS at the UCSF DNA Bank. Eighty eight percent of the participants are women, most are of European or Asian ancestry and the median age is 55. To assess potential batch effects when doing case-control comparisons using planned external controls, 30 DNA samples from each of three studies were genotyped with SICCA DNA samples: The Genetic Architecture of Smoking and Smoking Cessation - Collaborative Genetic Study of Nicotine Dependence (COGEND) - PI: Laura Bierut. NEI-Age-related disease study (AREDS) - Genetic Variation in Refractive Error Substudy - PI: Dwight Stambolian. Controls from the National Institute of Mental Health's (NIMH's) Human Genetics Initiative. Genome-Wide Association Study of Schizophrenia - PI: Pablo V. Gejman. Molecular Genetics of Schizophrenia - nonGAIN Sample (MGS_nonGAIN) - PI: Pablo V. Gejman. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data quality control, dbGaP preparation and posting, and imputation to 1000 Genomes to increase SNP density was performed by the Center for Biomedical Statistics at the University of Washington. Data analysis was performed at UCSF using software PLINK, EIGENSOFT, and SNPTEST.

Study phs000672

Bulk RNA-sequencing datasets from Caco-2 cells under normal or inflamed conditions treated with 4HTBZ or vehicle.

This dataset contains 4 bulk RNA sequencing files (.fastq.gz) and a metadata file (.csv) from Caco-2/TC7 intestinal epithelial cells under normal or inflamed conditions, followed by treatment with 4HTBZ or vehicle. The cDNA libraries were prepared with the QuantSeq 3′ mRNA-Seq Kit (Lexogen, Inc.) and sequenced on an Illumina HiSeq4000 system. The metadata file provides sample information (experimental condition and code identifier). Raw sequencing reads were quality-checked with FastQC, trimmed with Trimmomatic, and aligned to the human reference genome (GRCh38) using HISAT2.

Dataset EGAD50000001759

Genotype data for The admixture histories of Cabo Verde - genotype data

Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) As per Materials and Methods herein, the genotype data corresponds to 2,118,722 autosomal SNPs genotyped from the IlluminaOmni 2.5 Million BeadChip for 233 Cabo Verdean volunteer participants, family unrelated at the 2nd degree based on population genetics analyses (see Material and Methods). SNP rsID, Chromosome position and genetic position in (bp) are in Build GRCh38. Cabo Verdean individuals are designated with an alphanumeric unique code

Dataset EGAD00001008979

14341 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

in 79.38 milliseconds.

The Genomic Map of Poland in Open Access

Center for Common Disease Genomics [CCDG] - Cardiovascular: TexGen

AACR Project Genomics, Evidence, Neoplasia, Information, Exchange (GENIE)

NEI CIDR Methylation Profiling of Primary Open Angle Glaucoma in GLAUGEN Samples

A phase II trial of the aurora kinase A inhibitor alisertib for patients with castration resistant and neuroendocrine prostate cancer: efficacy and biomarker evaluation

High-Risk Breast Cancer GWAS

An atlas of the developing human fetal spine

Chromatin_Profiling_in_Twins

Spatial Dynamics of the Developing Human Heart

Spatial Dynamics of the Developing Heart (single-cell)

MARS-seq dataset of five obese human subjects and a lean human subject

The genetic structure of Norway

The Genomic Map of Poland in Open Access

dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

International Verapamil SR/Trandolapril [INVEST] Genes Study

Metastatic Adult Pancreatoblastoma: Multimodal Treatment and Molecular Characterization of a Very Rare Disease (NCT MASTER)

Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

Next Generation Mendelian Genetics: Auriculocondylar syndrome (ACS)

Investigating_low_frequency_variants_in_CAD_MI_cases__controls_and_pedigrees_using_whole_exome_sequencing_and_custom_pulldowns

Investigating_low_frequency_variants_in_CAD_MI_cases__controls_and_pedigrees_using_whole_exome_sequencing_and_custom_pulldowns

Cardiogenics_re_sequencing

Metadata Public API

National Eye Institute (NEI) Exfoliation Genotyping Study

Multiple migrations to the Philippines during the last 50,000 years

99 Cases of Small Cell Lung Cancer Study

Clinical Outcomes of 344 Diffuse Large B-Cell Lymphoma patients

CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

HeLa Cell Genome Sequencing Studies

eIMPACT Trial: Modernized Collaborative Care to Reduce the Excess CVD Risk of Older Depressed Patients

Distribution of data using Live Distribution

Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - Ribo-Seq

Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - Genome-Wide Association Study Meta-Analysis

COVID-19 ACTIV-4 ACUTE: A Multicenter, Adaptive, Randomized Controlled Platform Trial of the Safety and Efficacy of Antithrombotic Strategies in Hospitalized Adults with COVID-19 (ACTIV4A)

INDIA

DEEP-IHEC-release-2017

HipSci - Human Induced Pluripotent Stem Cells Initiative

Pancreatic islets PISA RNA-seq samples

NEI CIDR Methylation Profiling of Primary Open Angle Glaucoma in NEIGHBOR Samples

Parkinson's Disease Cognitive Genetics Consortium (PDCGC) Stage I, NeuroX Dataset

Khoe-San genome Project (KSGP)

CIDR: NCI Genome Wide Predictors of Survival in Colorectal Cancer

Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - RNA-Seq

Projects

Rare Disease Susceptibility Variant Study in Children with Crohn's Disease and Their Parents Using Targeted Gene Sequencing.

Analysis of IDHwt-glioblastoma samples from paired primary and recurrent tumor samples

Whole exome sequencing data of patients with resectable esophageal adenocarcinoma treated with neoadjuvant atezolizumab and chemoradiation (PERFECT)

Submission FAQ

The whole blood of female volunteers and sperm from the male volunteer were used to extract genomic DNA to do whole genome sequencing. Distinguished SNPs between parental genomes were retained to analyze parental allele-specific DNA methylation and chromatin accessibility in scCOOL-seq data.

GA4GH

NHLBI TOPMed - NHGRI CCDG: Early-onset Atrial Fibrillation in the CATHeterization GENetics (CATHGEN) Cohort

The genetic history of the southern Andes from present-day Mapuche ancestry

Federated EGA

Ensemble learning for classifying single-cell data and projection across reference atlases

Stressors and Health Study

FFPE, buffycoat and cell free DNA from N. German esophagus cancer patients - 2021

Age related Macular Degeneration (AMD)-- Michigan, Mayo, AREDS, Pennsylvania (MMAP) Cohort Study: A Joint Genome Wide Association Study

H3Africa - Deciphering Developmental Disorders in Africa

Genome-wide mutation analysis of germinal-center B-cell derived lymphomas within the ICGC MMML-Seq Consortium

A Pilot Study of NKTR-214 and Nivolumab in Selected Patients with Locally Advanced/Metastatic Sarcoma

Carolina Breast Cancer Study (CBCS)

Transdisciplinary Studies of Genetic Variation in Colorectal Cancer(CORECT): Meta-analysis

ImmunAID Data Access Committee

Targeted Validation Samples

ATAC_SEQ_MAIN___PHASE_1

A Chromatin Accessibility Atlas of the Developing Human Telencephalon

Polymorphisms in the Mitochondrial Genome associated with Bullous Pemphigoid in Germans

Correlative Genomic Analysis of Durvalumab plus Pazopanib Combination in Patients with Advanced Soft Tissue Sarcomas

A Prospective Natural History Study of Diagnosis, Treatment and Outcomes of Children with SCID Disorders

Data Use Ontology (DUO)

Genes associated with pancreas development and function maintain open chromatin in iPSCs generated from human pancreatic beta cells

Genotype data from 'Dense sampling of ethnic groups within African countries reveals fine-scale genetic structure and extensive historical admixture.'

Best Endovascular vs. Best Surgical Therapy in Patients With Critical Limb Ischemia (BEST CLI-BioLINCC)

RNAseq samples of patients with anti-PD-1 resistant HNSCC from a non-randomized, open-label phase 1b clinical trial

Center for Common Disease Genomics (CCDG)-Cardiovascular: University of Pennsylvania Cohort

EGA synthetic data

Cardiogenics_Custom_Pools - Agilent SureSelect

Nimblegen

Gut microbiome dynamics unravelled with metagenomics sequencing