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• A New Pipeline to Predict and Confirm Tumor Neoantigens Predicts Better Response to Checkpoint Blockade

  Mutations that drive oncogenesis in cancer can generate neoantigens that may be recognized by the immune system. Identification of these neoantigens remains challenging due to the complexity of the major histocompatibility complex (MHC) antigen and T-cell receptor interaction. Here we describe the development of a systematic approach to efficiently identify and validate immunogenic neoantigens. Whole exome sequencing of tissue from a melanoma patient was used to identify nonsynonymous mutations, followed by MHC binding prediction and identification of tumor clonal architecture. The top 18 putative class I neoantigens were selected for immunogenicity testing via a novel in vitro pipeline in HLA-A201 healthy donor blood. Naive CD8 T cells from donors were stimulated with allogeneic dendritic cells pulsed with peptide pools and then with individual peptides. The presence of antigen-specific T cells was determined via functional assays. We identified one putative neoantigen that expanded T cells specific to the mutant form of the peptide and validated this pipeline in a subset of patients with bladder tumors treated with durvalumab (N = 5). Within this cohort, the top predicted neoantigens from all patients were immunogenic in vitro. Finally, we looked at overall survival in the whole durvalumab-treated bladder cohort (N = 37) by stratifying patients by tertile measure of tumor mutation burden (TMB) or neoantigen load. Patients with higher neoantigen and TMB load tended to show better overall survival.

  Study phs002269

• PARK7/DJ-1 deficiency modulates microglial activation in response to LPS-induced inflammation

  Starting point is one patient from which iPSC cells are created, some received a genome correction to be called iCtrl from those two batches (DJ1 and iCtrl). 3 independent differentiation to Microglia cells were done, named R1, R2 and R3. On top, growing conditions were either untreated or LPS, leading to the 12 samples.

  Dataset EGAD50000000291

• Feasibility Study to Identify the Optimal Adjuvant Combination Scheme of Ipilimumab and Nivolumab (OpACIN) in resectable stage III melanoma patients

  OpACIN is a feasibility study including 20 patients with palpable stage III melanoma that were 1:1 randomized to receive ipilimumab 3mg/kg and nivolumab 1mg/kg, either 4 courses after surgery (adjuvant arm), or 2 courses prior to surgery and 2 courses post-surgery (neoadjuvant arm). WES and RNA-seq was performed on baseline biopsy material and correlated with outcome of the patients (relapse free survival). TCRseq from baseline tumor samples was used to analyse the top 100 tumor resident clones and analyse their change in PBMC comparing baseline versus week 6 of immunotherapy.

  Study EGAS00001003099

• UK Biobank whole cohort directly genotyped and imputed data (~500,000 participants)

  Genotype data is available for all 500,000 participants in the UK Biobank cohort. Genotyping has been performed using the Affymetrix UK BiLEVE Axiom array on an initial 50,000 participants and the remaining 450,000 participants have been genotyped using the Affymetrix UK Biobank Axiom® array. The two arrays are extremely similar (with over 95% common content).Quality control and imputation (to over 90 million SNPs, indels and large structural variants) has been performed by a collaborative group headed by the Wellcome Trust Centre for Human Genetics.The following data are available:* A clean set of QC’ed genotype calls* Confidence values that a genotype call is correct* Intensity data to generate cluster plots* Extensive QC information regarding SNPs and samples including SNP metrics, batch effects, population structure and relatedness* Imputed dataFor further information, please refer to the UK Biobank website

  Study EGAS00001002399

• RNAseq SCLC Cell lines MYC

  RNAseq data set (Mollaoglu et al., MYC drives progression of small cell lung cancer to a variant neuroendocrine subtype with vulnerability to Aurora kinase inhibition) RNA isolation from primary tumors and healthy lungs was performed using RNeasy Mini Kit (Qiagen) with the standard protocol. RNA was subjected to library construction with the Illumina TruSeq Stranded mRNA Sample Preparation Kit (cat# RS-122-2101, RS-122-2102) according to manufacturer’s protocol. Chemically denatured sequencing libraries (25 pM) are applied to an Illumina HiSeq v4 single read flow cell using an Illumina cBot. Hybridized molecules were clonally amplified and annealed to sequencing primers with reagents from an Illumina HiSeq SR Cluster Kit v4-cBot (GD-401-4001). Following transfer of the flowcell to an Illumina HiSeq 2500 instrument (HCSv2.2.38 and RTA v1.18.61), a 50 cycle single-read sequence run was performed using HiSeq SBS Kit v4 sequencing reagents (FC-401-4002).

  Dataset EGAD00001003099

• Somatic point mutation data from microsatellite unstable colorectal cancers

  Microsatellite instability (MSI) leads to accumulation of an excessive number of mutations in the genome, mostly small insertions and deletions. MSI CRCs, however, also contain more point mutations than microsatellite stable (MSS) tumors, yet they have not been as comprehensively studied. To identify candidate driver genes affected by point mutations in MSI CRC, we ranked genes based on mutation significance while correcting for replication timing and gene expression utilizing an algorithm, MutSigCV. Somatic point mutation data from the exome kit-targeted area from 24 exome sequenced sporadic MSI CRCs and respective normals, and 12 whole genome sequenced sporadic MSI CRCs and respective normals were utilized. The top 73 genes were validated in 93 additional MSI CRCs.

  Study EGAS00001003101

• Mechanisms of Therapy Driven Clonal Evolution in Oncogenic RAS Mutant Relapsed Acute Lymphoblastic Leukemia

  Although multi-agent combination chemotherapy is curative in a significant fraction of childhood acute lymphoblastic leukemia (ALL) patients, 20% of cases relapse and most die due to chemo-refractory disease. Here we used whole-exome and whole-genome sequencing to analyze the mutational landscape and pattern of clonal evolution at relapse in pediatric ALL cases. These analyses showed that ALL relapses originate from a common ancestral precursor clone of the diagnosis and relapsed populations and frequently harbor mutations implicated in chemotherapy resistance. RAS-MAPK pathway activating mutations in NRAS, KRAS and PTPN11 were present in 24/55 (44%) cases in our series. Notably, while some cases showed emergence of RAS mutant clones at relapse, in others, RAS mutant clones present at diagnosis were replaced by RAS wild type populations. Mechanistically, functional dissection of mouse and human wild type Kras and mutant Kras (Kras G12D) isogenic leukemia cells demonstrated induction of methotrexate resistance, but also improved response to vincristine, in mutant Kras- expressing lymphoblasts. These results identify chemotherapy driven selection as a central mechanism of leukemia clonal evolution and pave the road for the development of tailored personalized therapies for the treatment of relapsed ALL.

  Study phs001072

• Genetic Studies of Homologous Recombination Deficiency in Hispanic Gastric Cancer

  Approximately 10% of gastric cancer cases show familial clustering and a hereditary cause is likely, however, only 1-3% cases result from known hereditary syndromes – which are predominantly associated with CDH1 and CTNNA1 genes. Hispanics are > 2 times more likely to be diagnosed and to die from gastric cancer compared to non-Hispanic whites. Not only does gastric cancer precision medicine lag behind other cancers – there is an urgent need to understand its etiology. Germline mutations in homologous recombination genes have been implicated as important risk factors for gastric cancer. The purpose of this study is to continue to generate knowledge to improve gastric cancer outcomes and disparities by 1) characterizing prevalence of germline mutations in homologous recombination genes and identify new genes associated with gastric cancer 2) perform molecular characterization of gastric tumors in Hispanic patients. Participants for germline analysis were enrolled from Chile, Colombia, Mexico, Portugal, Spain, Uruguay.Whole exome sequence capture was performed for all germline and somatic samples using Agilent SureSelect Human All Exon v7 Kit. All sequencing was performed on an Illumina NovaSeq 6000. Germline Analysis: Whole exome sequencing was performed on 536 Hispanic patients (290 males, 246 female)

  Study phs003251

• Widespread DNA hypomethylation and differential gene expression in Turner syndrome

  Adults with 45,X monosomy (Turner syndrome) reflect a surviving minority since more than 99% of fetuses with 45,X monosomy die in utero. In adulthood 45,X monosomy is associated with increased morbidity and mortality, although strikingly heterogeneous with some individuals left untouched while others suffer from cardiovascular disease, autoimmune disease and infertility. The present study investigates the leukocyte DNAmethylation profile by using the 450K-Illumina Infinium assay and the leukocyte RNA-expression profile in 45,X monosomy compared with karyotypically normal female and male controls. We present results illustrating that genome wide X-chromosome RNA-expression profile, autosomal DNA-methylation profile, and the X-chromosome methylation profile clearly distinguish Turner syndrome from controls. Our results reveal genome wide hypomethylation with most differentially methylated positions showing a medium level of methylation. Contrary to previous studies, applying a single loci specific analysis at well-defined DNA loci, our results indicate that the hypomethylation extend to repetitive elements. We describe novel candidate genes that could be involved in comorbidity in TS and explain congenital urinary malformations (PRKX), premature ovarian failure (KDM6A), and aortic aneurysm formation (ZFYVE9 and TIMP1)

  Study EGAS00001002190

• A Population Genomics Study Using a Disease-Targeted Cell model: Integration of

  The common genetic variants associated with complex traits typically lie in non-coding DNA and may alter gene regulation in a cell type-specific manner. Consequently, the choice of tissue or cell model in the dissection of disease associations is important. We carried out an expression quantitative trait loci (eQTL) study of primary human osteoblasts (HOb) derived from 95 unrelated donors of Swedish origin, each represented by two independently derived primary lines to provide biological replication. We combined our data with publicly available information from a genome-wide association study (GWAS) of bone mineral density (BMD). The top 2000 BMD-associated SNPs were tested for cis-association of gene expression in HObs and in lymphoblastoid cell lines (LCLs) using publicly available data and showed that HObs have a significantly greater enrichment (threefold) of converging cis-eQTLs as compared to LCLs. The top 10 BMD loci with SNPs showing strong cis-effects on gene expression in HObs were selected for further validation using a staged design in two cohorts of Caucasian male subjects. All 10 variants were tested in the Swedish MrOS Cohort (n = 3014), providing evidence for two novel BMD loci (SRR and MSH3). These variants were then tested in the Rotterdam Study (n = 2090), yielding converging evidence for BMD association at the 17p13.3 SRR locus. The cis-regulatory effect was further fine-mapped to the proximal promoter of the SRR gene (rs3744270). Our results suggest that primary cells relevant to disease phenotypes complement traditional approaches for prioritization and validation of GWAS hits for follow-up studies. Reprinted from Grundberg E, Kwan T, Ge B et al., Genome Res Nov 2009, with permission from Genome Research, Cold Spring Harbor Press, PMID:19654370.

  Study phs000225

• Ischemic stroke in a Swedish case-control study.

  Background. Genetic risk scores (GRS), summing up the total effect of several single nucleotide polymorphisms (SNPs) in genes associated with either coronary risk or cardiovascular risk factors, have been tested for association with ischemic stroke with conflicting results. Recently an association was found between a GRS, based on 29 SNPs discovered by genome-wide association studies (GWAS) and hypertension. The aim of our study was to investigate the possible association of the same GRS with ischemic stroke on top of other “traditional risk factors”, also testing its potential improvement in indices of discrimination and reclassification, in a Swedish case-control study. Methods and results. Twenty-nine SNPs were genotyped in 3,677 stroke cases and 2,415 controls included in the Lund Stroke Register (LSR), the Malmö Diet and Cancer (MDC) study and the Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS). The analysis was conducted in the entire material, and separately for the three samples. After adjustment for hypertension, diabetes mellitus and smoking habits, the GRS was associated with ischemic stroke in the entire material [OR (95% CI) 1.086 (1.029-1.147) per SD increase in the GRS p=0.003] with similar trends in all three samples; LSR [1.050 (0.967-1.140)]; p=0.25], MDC [1.168 (1.060-1.288); p=0.002] and SAHLSIS [1.124 (0.997-1.267); P=0.055]. Measures of discrimination and reclassification improved marginally using the GRS. Conclusions. A blood pressure GRS is independently associated with ischemic stroke risk in three Swedish case-control studies, however, the effect size is low and adds marginally to prediction of stroke on top of traditional risk factors including hypertension.

  Study EGAS00001000936

• RNAseq in pleural mesothelioma primary cell lines

  Pleural mesothelioma (PM) requires new treatments. Drug repurposing offers a potential approach to finding effective therapies. This study aimed to explore new therapeutic options for PM using RNA sequencing. RNA sequencing was performed on 58 patient-derived PM cell lines. Drug screening of over 1300 compounds was conducted on 11 lines, with further testing of selected drugs on 48 lines. Top candidates were validated in 3D culture and mouse models.

  Dataset EGAD00001015408

• CIDR Estrogen Receptor Negative Breast Cancer in African American Women: DNA Methylation, Reproductive Events, and Mammary Epithelial Cell Populations

  We conducted methylation profiling of breast tumor DNA from Formalin-Fixed Paraffin-Embedded (FFPE) samples for 1,550 cases from a cohort of Black women from the Black Women’s Health Study (BWHS), the Women’s Circle of Health Study (WCHS), and from the Pathways Study using the Illumina MethylationEPIC array. We will examine differentially methylated loci (DML) between ER+ and ER- tumors, and by age at onset of breast cancer. Combining these data with previously analyzed samples (n=385), we will consider associations between reproductive risk factors and top DML by age at diagnosis and ER status, examining the complex relationships between methylation, tumor and patient characteristics, and reproductive risk factors using structural equation modeling.

  Study phs002688

• Spatial map of microglia states across CNS diseases

  Microglia are the key immune cells involved in virtually all diseases of the central nervous system (CNS). Here, we generated a novel large-scale single-cell RNA-sequencing-derived taxonomy through the analysis of > 1 million CNS cells enriched for myeloid cells across > 15 different pathologies and conditions. Disease-associated human microglia, together with CNS-associated macrophages and monocytes, were differentiated iteratively into 27 superclusters and 192 clusters. This top-down approach, in combination with targeted and genome-wide subcellular spatial transcriptomics, enabled us to examine and compare the spatial interactome of the identified superclusters and clusters within and across pathologies. Our data provide new insights into the spatial dynamics of the endogenous CNS immune system during development, health and disease in humans.

  Study EGAS50000001289

• High-coverage whole exome sequence in non-TRU-type lung adenocarcinomas

  In order to elucidate the key genetic events in non-TRU-type lung cancer, we selected 43 non-TRU-type lung adenocarcinomas and performed a whole exome sequence and RNA-seq analysis using a next-generation sequencer. The results of the analysis identified mutations in TP53, KRAS and NKX2-1 as the top three significantly mutated genes, while the EGFR mutation was rare in this cohort. Eight NKX2-1 mutations (5 frameshift, 2 nonsense, and one missense) were identified, with one case harboring two distinct NKX2-1 mutations (missense and frameshift). All NKX2-1 mutants were transcriptionally inactive in reporter assays. Histologically, invasive mucinous adenocarcinomas accounted for most of the NKX2-1 mutations (5 cases), while 1 enteric and 1 acinar adenocarcinoma harbored the NKX2-1 mutation.

  Study JGAS000105

• Cardiovascular disease biomarkers derived from circulating cell-free DNA methylation

  Acute coronary syndrome (ACS) remains a major cause of worldwide mortality. The syndrome occurs when blood flow to the heart muscle is decreased or blocked, causing muscle tissues to die or malfunction. There are three main types of ACS: Non-ST-elevation myocardial infarction, ST-elevation myocardial infarction, and unstable angina. The treatment depends on the type of ACS, and this is decided by a combination of clinical findings, such as electrocardiogram and plasma biomarkers. Circulating cell-free DNA (ccfDNA) is proposed as an additional marker for ACS since the damaged tissues can release DNA to the bloodstream. We used ccfDNA methylation profiles for differentiating between the ACS types and provided computational tools to repeat similar analysis for other diseases. We leveraged cell type specificity of DNA methylation to deconvolute the ccfDNA cell types of origin and to find methylation-based biomarkers that stratify patients. We identified hundreds of methylation markers associated with ACS types and validated them in an independent cohort. Many such markers were associated with genes involved in cardiovascular conditions and inflammation. ccfDNA methylation showed promise as a non-invasive diagnostic for acute coronary events. These methods are not limited to acute events, and may be used for chronic cardiovascular diseases as well.

  Study EGAS00001007263

• All you need to know about the new Submitter Portal

  In September we launched new services for all EGA users, including a new version of the former Submitter Portal. Our main objective with this Portal is to transform the metadata submission in a simplified and user-friendly method. Although it is possible to find documentation about the Submitter Portal on our website, we wanted to highlight the new features in this article. Enjoy! Credentials: who needs to create a new user to access the Submitter Portal and who doesn't? Users with an old submission account (ega-box) can already access the new Submitter Portal. If it is the first time that you want to access, it is time to request a submitter role linked to the EGA User. In the form, it is mandatory to explain which type of data you want to deposit, the size of your submission, add any comment you’d like us to read, and manage the EGA Data Processing Agreement (DPA) document. This document should be checked by the legal department of your institution and signed by a person with authority to sign contracts on behalf of the institution. Note that we provide a DPA template for new Users; it can be found and downloaded in the Submitter Request section. With the DPA signed and the Submitter Request sent, it is time to wait for our Helpdesk team to validate the request. Metadata submission now can be collaborative It is possible to add collaborator(s) to your submissions. Only registered EGA Users will appear on the search bar. When adding a collaborator, it is mandatory to define the permission granted: Read only: collaborators with this permission can check if the information of the submission is correct but cannot modify anything. Read & write: collaborators with this label can register new objects and modify the registered ones. We wanted to save time for submitters that usually rely on the same collaborators. For that, we have implemented the possibility of adding the same collaborators from previous submissions; all you need to do is to search the submission, and the exact set of EGA users will have access to your submission. You can check the collaborators and their permissions at any point of the submission by going to the collaborators section. Even adding more people to complete the submission is allowed by following the same steps: looking for the EGA User and defining the permission granted (please, note that during the submission it is not possible to add collaborators from previous submissions). Use external links to complement the study information When filling the information about the study we recommend users to enrich the submission with complementary fields such as PubMeds IDs, custom tags and external links. External links are used to connect a study to an external repository. We have implemented an external link to Euro-Bioimaging for a European Project (EuCanImage). Now, we are looking forward to keeping increasing the list of external repositories! Choose the expected release date for your metadata to be searchable on our website Once all the metadata objects are registered it is time to finalise the submission so that the Helpdesk team can approve it. In the new version of the Submitter Portal users can choose the expected release date for the metadata to be searchable on the EGA website. Please, note that the selected date will have a minimum of one week margin from the day of finalisation. This time is necessary for your files to be archived and for the submission to be validated by the Helpdesk Team. Are you looking for the Array submission within the Submitter Portal? Our Submitter Portal does not support array submissions. The submission of Array-based metadata must be done using the EGA programmatic submission. You will find our Array-based format template and all the necessary information on our website, and you can find all the steps in our submission quickguide! More information about the submission process at the EGA Our Team has developed an extended documentation related to metadata submission. A good first step is to take a closer look at the Submission FAQ. To have a general overview of all the metadata submission process we recommend taking a glimpse of our take-the-tour or watching the tutorial available on our YouTube Channel. Don't miss our section on EGA Schemas, to learn more about how the EGA is built. It can be useful to fully ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource.

  Blog new-submitter-portal

• First genome-wide association study in an Australian Aboriginal population provides insights into genetic risk factors for Body Mass Index and Type 2 Diabetes

  A body mass index (BMI) >22kg/m2 is a risk factor for type 2 diabetes (T2D) in Aboriginal Australians. To identify loci associated with BMI and T2D we undertook a genome-wide association study using 1,355,133 quality-controlled single nucleotide polymorphisms (SNPs) genotyped (Illumina 2.5M Duo Beadchip) in 402 individuals in extended pedigrees from a Western Australian Aboriginal community. Imputation using the thousand genomes (1000G) reference panel extended the analysis to 6,724,284 post quality-control autosomal SNPs. No associations achieved genome-wide significance, commonly accepted as P<5x10-8. Nevertheless, genes/pathways in common with other ethnicities were identified despite the arrival of Aboriginal people in Australia >45,000 years ago. The top hit (rs10868204 Pgenotyped=1.50x10-6; rs11140653 Pimputed_1000G=2.90x10-7) for BMI lies 5’ of NTRK2, the type 2 neurotrophic tyrosine kinase receptor for brain-derived neurotrophic factor (BDNF) that regulates energy balance downstream of melanocortin-4 receptor (MC4R). PIK3C2G (rs12816270 Pgenotyped=8.06x10-6; rs10841048 Pimputed_1000G=6.28x10-7) was associated with BMI, but not with T2D as reported elsewhere. BMI also associated with CNTNAP2 (rs6960319 Pgenotyped=4.65x10-5; rs13225016 Pimputed_1000G=6.57x10-5), previously identified as the strongest gene-by-environment interaction for BMI in African-Americans. The top hit (rs11240074 Pgenotyped=5.59x10-6, Pimputed_1000G=5.73x10-6) for T2D lies 5’ of BCL9 that, along with TCFL2, promotes beta-catenin’s transcriptional activity in the WNT signaling pathway. Additional hits occurred in genes affecting pancreatic (KCNJ6, KCNA1) and/or GABA (GABRR1, KCNA1) functions. Notable associations observed for genes previously identified at genome-wide significance in other populations included MC4R (Pgenotyped=4.49x10-4) for BMI and IGF2BP2 Pimputed_1000G=2.55x10-6) for T2D. Our results may provide novel functional leads in understanding disease pathogenesis in this Australian Aboriginal population.

  Study EGAS00001001004

• Massachusetts General Hospital (MGH) Atrial Fibrillation Study

  The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" box located on the right hand side of this top-level study page phs001001 Massachusetts General Hospital (MGH) Atrial Fibrillation Study. phs001116 MGH AF CHARGE-S phs001117 MGH AF Exome Sequencing phs001118 MGH AF Medical Resequencing

  Study phs001001

• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination.

  Dataset EGAD00001008696

• scRNAseq of distal colon biopsies from patients with ulcerative colitis and healthy controls

  scRNAseq dataset of colonic epithelium from distal colon biopsies from 4 patients with ulcerative colitis and 4 healthy individuals. Includes 11 samples split into three conditions: healthy, healthy margin and ulcerated. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into 4 lanes and into index (I1) and read (R1, R2) files. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Cell Ranger (v3.0.1) software from 10x Genomics was used to process the output and align the reads. The refdata-cellranger-GRCh38-3.0.0 reference was downloaded from the 10x Genomics website. First, cellranger mkfastq function was used to demultiplex raw base call files into FASTQ files. Then, the FASTQ files were aligned and filtered with cellranger count function.

  Dataset EGAD00001010167

• NIH RECOVER: A Multi-Site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection

  The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in decedents who die more than 60 days after initial onset or after hospital discharge, whether in-hospital or out-of-hospital at time of death, and who meet the working definition of PASC as defined by the recent World Health Organization publication given in Section 5.4. The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of decedents who died between15-60 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium.

  Study phs003768

• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination. Biological Materials were provided by the Ontario Tumour Bank, which is funded by the Ontario Institute for Cancer Research Reference for citation: Ling Liu, Jinghua Feng, Julian Polimeni, Manli Zhang, Hai Nguyen, Urmi Das, Xu Zhang, Harminder Singh, Xiao-Jian Yao, Etienne Leygue, Sam K.P. Kung, and Xie J. Characterization of cell free plasma methyl-DNA from xenografted tumours to guide the selection of diagnostic markers for early-stage cancers. Frontiers in Oncology, 2021 Feb. 5. DOI: 10.3389/fonc.2021.615821.

  Study EGAS00001006175

• What is the cBio Portal

  EGA cBioPortal What is the EGA cBioPortal? EGA hosts a dedicated cBioPortal instance that enables authorized researchers to explore and visualize selected cancer datasets archived at EGA. Data submitters can also contribute cancer datasets to be made available through the portal. The platform provides interactive tools to analyse genomic and clinical data once access has been granted by the relevant Data Access Committee (DAC). How to find and access an EGA cBioPortal Dataset 1. Register as an EGA user 2. Go to the dataset page of interest. You can use the Search function to find datasets available in cBioPortal. If the dataset is available on the EGA cBioPortal Instance, the cBioPortal icon will be displayed on the dataset page, as shown below: On the dataset page, you will find information about access requirements. For more details, please visit how to request access. 3. Once access has been granted Go to the EGA cBioPortal instance and log in with your EGA user accountThe approved dataset will be listed in cBioPortalSelect the dataset to start exploring the data What you can do in cBioPortal The EGA cBioPortal is designed for interactive exploration and visualization of controlled-access cancer datasets, including: Visualising genomic alterationsAnalysing mutation patternsFiltering by clinical attributesComparing molecular profilesGenerating plots and summaries Important Notes Datasets are only visible in cBioPortal after DAC approvalAccess requests must always be submitted through the EGA website If you encounter any issues gaining access to a dataset, please contact EGA Support.If your question is related to the cBioPortal features, please reach out to: cbioportal@googlegroups.com. The EGA Helpdesk does not support this platform. How to link a dataset to the EGA cBioPortal instance during a submission STEP 1 – cBioPortal File Upload to EGA Files must be uploaded to the SFTP INBOX. The supported cBioPortal file types are: Raw data (e.g., VCF files)cBioPortal-specific formats (e.g., MAF files) STEP 2 – Register the cBioPortal dataset in the Submitter Portal Register the cBioPortal files in an analysis objectRegister a dataset with the title “cBioPortal Metadata” and include the analysis and nothing else Please note that cBioPortal is not directly supported by the EGA Helpdesk. For questions about the platform, please visit the cBioPortal website or contact the cBioPortal support team at cbioportal@googlegroups.com. The EGA does not support this platform.

  Documentation submission/metadata/submission/cbioportal

• Common Variant GWAS, Genetics & Epidemiology of Colorectal Cancer Consortium (GECCO)

  Genetics & Epidemiology of Colorectal Cancer Consortium (GECCO) is a collaborative effort which aims to accelerate the discovery of colorectal cancer-related variants by discovering, replicating and fine-mapping Genome Wide Association Study (GWAS) findings, conducting a meta-analysis of GWAS data, and investigating how genetic variants are modified by environmental risk factors. The coordinating center for this consortium is based at the Fred Hutchinson Cancer Research Center (Principal investigator: Ulrike Peters). The GECCO Consortium is utilized in the following dbGaP individual studies. To view genotypes, and derived variables collected in these individual studies, please click on the following individual studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001078 GECCO Consortium. phs000965 VITAL phs001056 DALS phs001077 WHI Colorectal Cancer phs001092 PMH CCFR phs001094 PLCO phs001104 ASTERISK phs001113 DACHS phs001114 HPFS phs001128 PHS phs001129 NHS phs001170 Colo2and3 phs001171MEC Colorectal Cancer

  Study phs001078

• Variation in the Glucose Transporter gene SLC2A2 is associated with glycaemic response to metformin

  Metformin is the first-line antidiabetic drug with over 100 million users worldwide, yet its mechanism of action remains unclear1. Here the Metformin Genetics (MetGen) Consortium reports a three-stage genome wide association study (GWAS), consisting of 13,123 participants of different ancestries. The C-allele of rs8192675 in the intron of SLC2A2, which encodes the facilitated glucose transporter GLUT2, was associated with a 0.17% (p=6.6x10-14) greater metformin induced HbA1c reduction in 10,577 participants of European ancestry. rs8192675 is the top cis-eQTL for SLC2A2 in 1,226 human liver samples, suggesting a key role for hepatic GLUT2 in regulation of metformin action. In obese individuals C-allele homozygotes at rs8192675 had a 0.33% (3.6mmol/mol) greater absolute HbA1c reduction than T-allele homozygotes.This is about half the effect seen with the addition of a DPP-4 inhibitor, and equates to a dose difference of 550mg of metformin, suggesting rs8192675 as a potential biomarker for stratified medicine.

  Study EGAS00001001875

• Genomic and Phenotypic Profile of Sickle Cell Disease in Human Population in Cameroon

  Sickle cell disease (SCD) is caused by a biallelic single nucleotide substitution in the beta-globin gene (HBB), resulting in an amino acid substitution, Glu7Val, formerly known as Glu6Val. An estimated 300,000 babies with SCD are born worldwide each year, with nearly 75% of these births being in sub-Saharan Africa. In Africa, at least 30-50% of children with untreated SCD die before the age of 5 years. Therefore, accelerating the path for novel therapies for SCD through genomics research on fetal hemoglobin (HbF) is critical. Variants in the currently known HbF‐modulating genes/loci, i.e., BCL11A, HBS1L-MYB, and XmnI-HBG2, explain only 10-20% of the variation of HbF levels in African individuals with SCD, compared with nearly 50% of the variation in HbF levels among Europeans. Expanding genomic research in populations of African ancestry could uncover the missing heritability of HbF-promoting loci. This study used the Human Heredity and Health (H3Africa) consortium SNP genotyping array developed from whole genome enriched for common variants in sub-Saharan Africans to investigate genomic variations associated with HbF levels in individuals with sickle cell anemia of the HbSS genotype from Cameroon. Two of the previously described loci, BCL11A and HBS1L-MYB were replicated, while a novel locus on chromosome 13 mapping to FLT1 was uncovered. The study therefore opens up a novel avenue for exploring SCD gene therapy.

  Study phs003748

• scRNA-Seq & scATAC-Seq Feature-counting Results Derived from 10X Cellrange-arc-count pipeline

  The feature-counting outputs from Cellrange-arc-count pipeline contain information at the single cell level, jointly for both scRNA-Seq and scATAT-Seq on 103 DLBCL samples and 3 normal controls (Please note that sc-40 only has scRNA-Seq data without scATAC-Seq). These files can be used as the input files for further downstream analysis software (e.g. Seurat Package). Moreover, a matrix of single-cell barcodes and associated cell biological types (used in the study) is also provided for users’ reference. This dataset is large and split into two parts to facilitate downloads. This dataset is large and split into two parts to facilitate downloads. The Linux command line of "tar -xvf xxxx_PART1.gz" should be used to extract the individual files. For additional information regarding the genomic data associated with the study, please also see the paper companion website at https://llmpp.ccr.cancer.gov/local/DLBCL_singlecell/

  Dataset EGAD50000002490

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004041

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004042

• Genetic analysis of Hirschsprung disease

  Hirschsprung disease (HSCR) is a birth defect resulting from the absence of nerve (ganglion) cells in the gastrointestinal tract. Hirschsprung disease has a population incidence of 1/5,000 live births and most often occurs as an isolated condition. However, approximately 30% of HSCR cases are associated with other birth defects such as Down syndrome, deafness, hypopigmentation, and Congenital Central Hypoventilation syndrome (CCHS). Hirschsprung disease is a genetic condition with autosomal dominant, autosomal recessive, and multigenic patterns of inheritance described. The goal of the research study is to identify genes harboring causative HSCR mutations and to better understand the complex inheritance of HSCR in families using whole genome mapping and sequencing studies with functional follow-up of candidate genes and variants. We intend to ascertain the frequency with which mutations in any human gene lead to familial and isolated forms of HSCR. Clinical information is collected to allow investigation of possible genotype - phenotype correlations. The subject population consists of individuals diagnosed with HSCR and their unaffected relatives. Individuals/families are ascertained through support groups, web-based listings of research studies and genetic testing services, an educational study website, and referrals from genetic counselors and physicians. Blood, or tissue, samples are requested from affected individuals and their unaffected relatives.

  Study phs000497

• Count Me In (CMI): The Metastatic Prostate Cancer (MPC) Project (CMI-MPCproject)

  Count Me In - The Metastatic Prostate Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Prostate Cancer Research The Metastatic Prostate Cancer Project (MPCproject; http://mpcproject.org/) is a research study that empowers men with metastatic and advanced prostate cancer to partner directly with researchers by sharing their samples and clinical information, with the ultimate goal of accelerating scientific discoveries that have clinical impact. The MPCproject enables any man with metastatic or advanced prostate cancer in the US and Canada to participate in cutting-edge genomic and molecular research, regardless of where they live. Metastatic or advanced prostate cancer patients visit the project website and complete an online questionnaire of basic information about themselves and their cancer. Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA, and transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided with updates on the study.

  Study phs001939

• Rare germline sequence variants, copy number variations, expression alterations, methylation variations and disease susceptibility in familial melanoma

  Although a number of high-risk melanoma genes have been identified, they account for melanoma risk in less than 40% of melanoma-prone families. The major goals of our research are to identify novel high-penetrance genes for familial melanoma in melanoma-prone families without known mutations and to identify modifier factors, including genetic and epigenetic, in melanoma-prone families with and without known major mutations. We are using whole exome sequencing to identify additional high-risk susceptibility genes and using targeted sequencing to follow up on the top genes in additional family members and in population-based melanoma cases and controls. We are also using RNASeq to investigate genome-wide allele-specific expression and eQTLs in these families to identify genes with expression alteration, which will provide additional information for gene discovery. In addition, we also conducted genome-wide copy number variation (CNV), methylation, and miRNA expression profiling analyses in our melanoma families with the goal of identifying genetic and epigenetic factors as disease modifiers.

  Study phs001177

• Genes-Environments and Admixture in Latino Asthmatics (GALA II) Study

  A case-control pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. The GALAII Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" box located on the right hand side of this top-level study page phs001180 GALAII Study. phs001274phs001274 GALAII GWAS

  Study phs001180

• Single-Cell RNA-Sequencing of Human Prostatectomy Tissue

  The tissue microenvironment in prostate cancer is profoundly altered. How prostate cancer cells and their precursors mediate those changes is unclear, in part due to the inability to longitudinally study the disease evolution in human tissues. To overcome this limitation, we performed extensive single-cell RNA-sequencing (scRNA-seq) to assess the transcriptional profiles of the tissue microenvironment in prostate tissues from prostatectomies from men diagnosed with prostate cancer. For each subject, benign-enriched and tumor-enriched tissues were collected from the peripheral zone of the prostate. Our studies of human tissues revealed that cancer cell-intrinsic activation of MYC signaling was the top up-regulated pathway in human cancers, representing a common denominator across the well-known molecular and pathological heterogeneity of human prostate cancer. Numerous non-malignant cell states in the tumor microenvironment (TME), including non-cancerous epithelial, immune, and fibroblast cell compartments, were conserved across individuals, suggesting that these cell types may be a sequelae of the convergent MYC activation in the cancer cells.

  Study phs003480

• Epigenome and transcriptome profiling of chronic lymphocytic leukemia patients

  Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

  Study EGAS00001001821

• early-stage ESCC sequencing study

  We performed a comprehensive multi-omics analysis of 786 trace-tumor-samples from 154 esophageal squamous cell carcinoma phase (ESCC) patients, covering 9 histopathological stages in 3 phases as nontumor phase (NT phase), intraepithelial neoplasia phase (IEN phase), and ESCC phase. Proteogenomics elucidated the stage-specific molecular characterization and defined the cancer-driving waves along with the mutation accumulation in EC progression. The integrated multi-omics uncovered the chromosome 3q gain was the key event in the transmit from the NT to IEN phase, disclosed the top mutation of TP53 enhanced cell cycle and DNA replication in the IEN phase, and revealed the ESCC phase mutations of AKAP9 and MCAF1 elevated glycolysis and Wnt signaling, respectively. Furthermore, the trajectory analysis identified 6 major tracks related to different clinical features during ESCC progression. Growingly enhanced and hyperphosphorylated phosphoglycerate kinase 1 (PGK1, S203) was detected and considered as a drug target in ESCC progression. Collectively, this study provides insight into the understanding of ESCC molecular mechanism and a valuable resource for the development of therapeutic targets.

  Study EGAS00001006126

• National Cancer Institute (NCI) TARGET: Therapeutically Applicable Research to Generate Effective Treatments

  The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Initiative seeks to accelerate research in novel marker and drug development, along with understanding the molecular basis of pediatric malignancy, through identification of genomic changes associated with the following childhood cancers: Acute Lymphoblastic Leukemia (ALL) - A fast-growing type of blood cancer in which too many immature white blood cells are found in the blood and bone marrow. Acute Myeloid Leukemia (AML), including AML Induction Failure cases (AML-IF) - Another type of blood cancer marked by too many myeloblasts, an alternate type of immature white blood cell, are found in the blood and bone marrow. Upon diagnosis, AML patients without high-risk genetic markers undergo standard chemotherapy regimen, called the primary induction phase, to eliminate most cancer cells and induce a remission state. Clear Cell Sarcoma of the Kidney (CCSK) - A rare type of kidney cancer, in which the inside of the cells looks clear when viewed under a microscope. Clear cell sarcoma can spread from the kidney to other organs, most commonly the bone, but also including the lungs, brain, and soft tissues of the body. Neuroblastoma (NBL) - Cancer of cells of the sympathetic nervous system. Cancer Model Systems (MDLS), including PPTP - MDLS includes acute leukemia cell lines and xenografts with matched primary and/or relapsed tumor information, NBL cell lines and xenografts with matched controls, kidney tumor cell lines, normal brain tissues, and embryonic stem cell lines that were sequenced for some TARGET disease projects. Osteosarcoma (OS) - A cancer of the bone that primarily affects children and adolescents. Rhabdoid Tumor (RT) - A rare, fast-growing cancer that usually forms in the kidney or central nervous system (the brain and spinal cord) but can also form in soft tissues in other areas of the body. Rhabdoid tumors tend to spread quickly, are hard to treat, and have a poor prognosis. Wilms' Tumor (WT) - A cancer of cells in the kidney that can spread to the liver, lung and lymph nodes. More information can be found about each TARGET subproject by following the links on the top of this page. Together these cancers account for the majority of the more than 10,000 childhood cancer cases diagnosed in the United States each year. TARGET has employed a set of advanced and complementary genome analysis technologies, including large scale 2nd and 3rd generation genome sequencing, to strategically characterize alterations in both gene expression and in genomic structure (such as deletions and amplification) that are involved in childhood cancers. The goal of this coordinated effort has been to create a comprehensive genomic and transcriptomic profile of each cancer. Integrated analysis of the TARGET data has identified those genes that are either altered in their expression level or mapped to the chromosome regions of deletion/amplification/translocation, as these genes represent strong candidates for therapeutic targeting. To learn more about the TARGET project, which is now completed, visit the website at https://www.cancer.gov/ccg/research/genome-sequencing/target. TARGET data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the TARGET Publication Pages at the GDC (Please see the "Supplemental Links" section of any TARGET publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original TARGET research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data - gene expression, copy number variation, epigenetics, targeted sequencing), as well as higher level data generated by the GDC. Please see the TARGET Use and Publication Guidelines for updated details on the sharing of any TARGET substudy data, including how to cite TARGET.

  Study phs000218

• Download Metadata

  Metadata Distribution Welcome to the realm of Metadata Distribution within the EGA ecosystem! Our Metadata REST API empowers you to effortlessly retrieve metadata from the expansive landscape of EGA. By utilising this API, you gain access to publicly available insights across various EGA domains, including studies, samples, experiments, runs, analyses, policies, DACs, and datasets. Furthermore, this API facilitates cross-referencing of objects, enabling you to gather, for example, all the datasets associated with a specific DAC, seamlessly. In addition, we have added the ability to query private data using the metadata API. If you possess the necessary permissions, you can access behind-the-login private data for a specified list of datasets. Metadata Distribution Index Identifiers Dataset Mappings Website Download Metadata API - Private Identifiers At the core of EGA's organisational structure are unique accessions that serve as essential tags for our diverse objects. Here's a quick overview of the accessions and their corresponding object types: 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 For further information check our metadata schema documentation. Dataset Mappings For authorised datasets, comprehensive mappings reveal meaningful connections: Sample_file: This file presents information about the linkage between samples and files available in the dataset. Study_experiment_run_sample: This file presents information about the linkage between studies, experiments, runs, and samples within the dataset. Study_analysis_sample: This file presents information about the linkage between studies, analyses, and samples contained within the dataset. Run_sample: This file presents information about the linkage between runs and samples within the dataset. Analysis_sample: This file presents information about the linkage between analyses and samples within the dataset. An empty file indicates the absence of corresponding information. Website Download Our website serves as your gateway to downloading metadata. Simply navigate to the dataset page, and you'll find a blue Metadata button. Once authenticated, you can click this button for authorised datasets. If you lack permissions for a particular dataset, request access by clicking the 'Request Access' button. For authorised datasets, choose your preferred metadata format: CSV, TSV, or JSON. Metadata API - Private Leverage the power of programmatic metadata downloads! Start by authenticating yourself with your credentials to obtain an access token. With this token, programmatically query private information. Queries mirror the structure of the Public Metadata API. However, behind the login, you can delve into specific mapping information (as mentioned above in dataset mappings) alongside object-level exploration. Authentication An active session is required to work with the API. Each time you log in with your credentials a new session is started, which is identified by an access_token. Below an example on how to obtain one using curl: curl https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token \ -d 'client_id=metadata-api' \ -d 'username=...' \ --data-urlencode 'password=...' \ -d 'grant_type=password' All responses from the API are in JSON format. A successful response should include a new token to be used for the session: {"access_token":"eyJhbGciOiJSUzI1NiIsInR5cCIgOiA...TNw", "expires_in":300, "refresh_expires_in":1800, "refresh_token":"eyJhbGciOiJIUzI1NiIsInR5cCIgOiA...pTX10", "token_type":"Bearer", ... } Save the access_token value and include it in the API call headers. Example query usage Below you can find some example of queries available behing authentication and authorisation. Querying study-experiment-run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_experiment_run_sample \ -H 'Authorization: Bearer access_token' Querying run-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/run_sample \ -H 'Authorization: Bearer access_token' Querying study-analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/study_analysis_sample \ -H 'Authorization: Bearer access_token' Querying analysis-sample mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/analysis_sample \ -H 'Authorization: Bearer access_token' Querying sample-file mappings: curl https://metadata.ega-archive.org/datasets/{datasetID}/mappings/sample_file \ -H 'Authorization: Bearer access_token' You can get a different output format by adding one of these options to the curl command: -H 'Accept: text/tsv' -H 'Accept: application/json' -H 'Accept: text/csv' For more detailed information, refer to the Metadata API Specification.

  Documentation access/download/metadata

• Framingham Heart Study-Cohort (FHS-Cohort) - Imaging

  The Framingham Heart Study (FHS) is a population-based, observational cohort study initiated in 1948 to prospectively investigate the determinants of cardiovascular disease to guide public health prevention. The FHS began by recruiting an Original Cohort of 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, who had not yet developed overt symptoms of cardiovascular disease or suffered a heart attack or stroke. The Original cohort Exam 1 took place between 1948 and 1953. Since that time the cohort has had a total of 32 biennial exams (ending in 2014) and event follow-up through 2022. In 1971, the FHS added the Offspring cohort, comprising 5124 children whose parents were enrolled in the Original cohort and the spouses of the children. This cohort on average has been examined every three to four years. However, there was an eight year gap between Exam 1 and Exam 2 and a seven year gap between Exam 7 and Exam 8. The latest exam (10) was completed in 2022. In 2002, the transgenerational FHS design was facilitated with the recruitment of 4095 children of the Offspring cohort (Third Generation), and 103 spouses of the Offspring who were not previously enrolled in the study (New Offspring Spouses, NOS). These cohorts have completed 3 exams through 2019. To reflect the changing demographic characteristics of the greater Framingham community, the FHS additionally recruited and enrolled 2 cohorts comprising racial and ethnic minority groups, termed Omni-1 and Omni-2, (n = 506 and 410, respectively) in 1995 and 2002, respectively. These cohorts included individuals of African American, Hispanic, Asian, Indian, Native American, and Pacific Islander descent. The OMNI-1 cohort have completed 5 exams through 2022. The OMNI-2 cohort have completed 3 exams through 2019. Data available for request include Echocardiogram images, available from the following exams in each cohort. Original Cohort: exams 18-32; Offspring cohort: exams 3-10; Third Generation, NOS and OMNI-2 cohorts: exams 1-3; OMNI-1 cohort: exams 1-5.CT image data at one or two timepoints were added for 4427 participants in the offspring, third generation, and OMNI1 and OMNI2 cohorts.Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007.

  Study phs003593

• GEnetics of Nephropathy - an International Effort (GENIE) GWAS of Diabetic Nephropathy in the UK GoKinD and All-Ireland Cohorts

  Diabetic kidney disease, or diabetic nephropathy (DN), is one of the leading causes of end-stage renal disease in the United States and worldwide. DN is a common complication of long-standing type 1 and type 2 diabetes. The clinical course is characterized by development of proteinuria and gradual loss of kidney function. Although existing treatments that decrease proteinuria have been shown to moderately abate progression of diabetic kidney disease, many affected patients, who do not die from cardiovascular disease, go on to develop terminal renal failure, necessitating costly renal replacement therapies, such as dialysis and renal transplantation. Type 1 diabetes (T1D) can have its onset in childhood and affected individuals often develop end-stage renal disease in early adulthood, leading to further loss of quality of life. The genetic basis of the disease is not well understood. The GENIE (GEnetics of Nephropathy an International Effort) consortium was initiated to perform the most comprehensive and well powered DN susceptibility genome wide association study (GWAS) analysis to date, using the largest collection of type 1 diabetics with and without kidney disease across four study cohorts. The UK-ROI samples were genotyped as part of this project. UK-ROI Sample Description The UK-ROI collection consists of samples derived from the Republic of Ireland (Dr. Catherine Godson, PI, at University College, Dublin, Ireland) and the United Kingdom (Warren 3 and Genetics of Kidneys in Diabetes UK, UK GoKinD, Dr. Alexander P. Maxwell, PI, at Queen's University of Belfast, UK). All study subjects met the inclusion criteria: white individuals with T1D, diagnosed before 31 years of age, whose parents and grandparents were born in the British Isles.

  Study phs000389

• NIH Roadmap Epigenomics Program - Broad Institute

  For the NIH Roadmap Epigenomics project, we applied ChlP-Seq, HTBS and WGBS pipelines to generate comprehensive high-resolution maps of chromatin state and DNA methylation for 100 diverse cell types. Cell types were selected for their biological and medical importance, and for their potential to maximize the comprehensiveness of acquired epigenomic data. They include human ES cells, ES-derived cells, mesenchymal stem cells, reprogrammed stem cells and primary tissues. Comprehensive characterization of epigenetic marks ("the epigenome") is a critical step towards a global understanding of the human genome in health and disease. In this study we provide unprecedented views of the human epigenetic landscape and its variation across cell states, which offer fundamental insight into the functions and interrelationships of epigenetic marks, and provide a framework for future studies of normal and diseased epigenomes. The Roadmap Epigenomics Broad cohort is utilized in the following dbGaP sub-study. To view molecular data and derived variables collected in this sub-study, please click on the following sub-study below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000700 the Roadmap Epigenomics Broad cohort. phs000610 RM_Epigenomics_Broad_Alz

  Study phs000700

• Resequencing (MIPS) of candidate genes for Keratoconus (2020)

  In this study, we selected 34 candidate genes for KC based on previous Whole Exome Sequencing (WES) and the literature, and resequenced them in 745 KC patients and 810 ethnically matched controls. Data analysis was performed using the single variant association test as well as gene-based mutation burden and variance components tests. In our study, we detected enrichment of genetic variation across multiple gene-based tests for the genes COL2A1, COL5A1, TNXB, ZEB1 and ZNF469. The top hit in the Fisher’s exact test was obtained for a common variant in the COL12A1 gene. Interestingly, COL5A1, TNXB, ZNF469 and COL12A1 are all known Ehlers-Danlos Syndrome (EDS) genes. Though the co-occurrence of KC and EDS has been reported previously, this study is the first to demonstrate a consistent role of genetic variants in EDS genes in the etiology of KC. In conclusion, our data show a shared genetic etiology between KC and EDS, and clearly confirm the currently disputed role of ZNF469 in disease susceptibility for KC. Besides the role for EDS genes, we also confirm the previously reported involvement of genetic variation in ZEB1 in KC.

  Study EGAS00001004267

• Whole exome sequencing (WES) of EBV- primary central nervous system lymphoma (PCNSL)

  This dataset contains whole exome sequencing (WES) of 29 HIV- EBV- primary central nervous system lymphoma (PCNSL) tumors and 5 activated B-cell-like PCNSL (ABC-PCNSL) and activated B-cell-like diffuse large B-cell lymphoma (ABC-DLBCL) cell lines (TK, HKBML, OCI-Ly3, HBL-1, TMD-8). Cases with secondary involvement of the CNS were excluded. DNA was extracted with AllPrep DNA/RNA FFPE kit and libraries were prepared using the Agilent SureSelect Human All Exon v6 + UTR kit. Paired end reads were aligned to GRCh37 using bwa mem v.0.7.17, and reads were sorted and duplicated were marked in the final BAM files. Access to this data is controlled. There are a number of steps that a researcher must take to obtain access to this data, including execution of a Data Access Agreement between the institutions. The process is overseen by the Technology Development Office; please contact our general email address TDOadmin@phsa.ca. Please only click the "request data" button on the EGA website after a Data Access Agreement is fully executed.

  Dataset EGAD50000000451

• Highlights from 2025: Our top 10 requested studies

  In 2025, as in previous years, EGA has facilitated the reuse of numerous datasets spanning a broad range of research and healthcare topics. To reflect on this activity, we would like to highlight the top 10 studies behind the most requested datasets of last year. Notably, the vast majority of these highly requested datasets are cancer-focused, particularly involving the study of immune checkpoint inhibitor therapies. Immune checkpoint inhibitors (ICIs) have become one of the most transformative advances in modern cancer therapy. These monoclonal antibodies enhance antitumor immune responses by targeting inhibitory immune checkpoint molecules. While ICIs have led to remarkably favorable and durable responses in some patients, treatment outcomes vary widely. This variability has fueled intense research efforts aimed at understanding resistance mechanisms, exploring combination therapies, and discovering predictive biomarkers to better stratify patients and guide treatment decisions. Study Title Disease 1 EGAS00001005503 Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma Liver Cancer 2 EGAS00001005013 Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer Lung Cancer 3 EGAS00001004809 BIOKEY: A single-cell catalogue of the dynamic changes underlying Checkpoint Immunotherapy response in Early Breast Cancer Breast Cancer 4 EGAS50000000138 BIOKEY: Immune heterogeneity in small cell lung cancer and vulnerability to immune checkpoint blockade Lung Cancer 5 EGAS50000000497 Bladder cancer subtyping study across 4 atezo clinical trials Bladder Cancer 6 EGAS50000000689 MOSAIC - Multi-Omics Spatial Atlas In Cancer Cancer Atlas 7 EGAS00000000083 METABRIC (Breast cancer - genome and transcriptome) Breast Cancer 8 EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Synthetic data 9 EGAS00001002556 TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells Bladder Cancer 10 EGAS00001004353 Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade Renal Cancer The most requested dataset of the year was EGAD00001008128. It belongs to a study that analyzed 358 liver cancer patients enrolled in clinical trials and treated with the combination of atezolizumab (anti–PD-L1) and bevacizumab (anti-VEGF), atezolizumab alone, or sorafenib. The study highlights how bevacizumab enhances anti-PD-L1 effect and identifies candidate biomarkers to predict treatment response. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the third leading cause of cancer-related death worldwide [1]. Because symptoms often appear late, many patients are diagnosed at advanced stages, when curative options are no longer viable. For many years, sorafenib—a multikinase inhibitor approved in 2007—was the only systemic treatment available. Although numerous clinical trials followed, it was not until a decade later that additional therapies showed meaningful clinical benefit. Among these advances, immunotherapy emerged as a promising first-line option [2]. In particular, the combination of atezolizumab and bevacizumab demonstrated improved survival in patients with advanced HCC, reshaping the treatment landscape. However, treatment efficacy remains limited by the complex and diverse hepatic microenvironments that influence immune responses, as well as by high intratumoral heterogeneity. Identifying robust predictors of treatment response is critical to enable effective patient stratification and maximize the benefits of these therapies [2]. The continued demand for these datasets highlights the interest and critical role of data reuse in deepening our understanding of cancer, accelerating the development of more effective therapies, and improving patient outcomes. By providing secure access to high-quality genomic and clinical data, EGA acts as a catalyst for biomedical progress. References Sung, Hyuna, et al. "Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries."CA: a cancer journal for clinicians 71.3 (2021): 209-249. Ladd, Alexandra D, et al.“Mechanisms of drug resistance in HCC.” Hepatology 79(4) (2024): 926-940

  Blog top-10-studies-2025

• BAM files of total RNA-Seq data of POPS control samples (GRCh37)

  Placental biopsies (n = 64 female placentas, n = 67 male placentas) were selected from healthy pregnancies from the POPs cohort. A quality control process was also applied for the RNA-Seq datasets: reads were trimmed with Trim Galore!, which uses cutadapt internally and were mapped to the same version of human genome reference (hg19). TopHat2, a splice-aware mapper built on top of Bowtie2 short-read aligner, was used in the mapping process in which so-called two-pass (or two-scan) alignment protocol was applied to rescue unmapped reads from the initial mapping step. In the second mapping, previously unmapped reads were re-aligned to the exon-intron junctions detected in the first-mapping by TopHat2 and were combined across all 131 placenta samples. The initial and second mapped reads were merged by samtools

  Dataset EGAD00001003462

• Integrating molecular imaging and transcriptomic profiling in advanced HER2-positive breast cancer receiving trastuzumab emtansine (T-DM1): an analysis of the ZEPHIR clinical trial

  Purpose: The ZEPHIR clinical trial evaluated the role of [89Zr]trastuzumab-PET/CT (HER2-PET/CT) and 2-[18F]fluoro-2-deoxy-D-glucose PET/CT ([18F]FDG-PET/CT) in predicting outcomes in patients with advanced HER2-positive breast cancer treated with trastuzumab emtansine (T-DM1). Here, we combined molecular/metabolic imaging and transcriptomic data to investigate the biological processes associated with [89Zr]trastuzumab and [18F]FDG uptake, and to dissect the mechanisms involved in T-DM1 resistance. Experimental design: RNA was extracted from metastasis biopsies obtained at study inclusion in the ZEPHIR trial. HER2-PET/CT and [18F]FDG-PET/CT imaging data of biopsied lesions were integrated with RNA sequencing data. Lesions were compared based on the level of [89Zr]trastuzumab uptake (dichotomized into high/low classes) as well as on the presence/absence of metabolic response, defined comparing baseline and on-treatment [18F]FDG-PET/CT. Results: We analyzed matched transcriptomic and molecular/metabolic imaging data for 24 metastases (one lesion/patient). Pathways involved in extracellular matrix (ECM) organization, glycosylphosphatidylinositol synthesis, and collagen formation were enriched in lesions presenting low [89Zr]trastuzumab uptake. [18F]FDG uptake at baseline correlated with proliferation and immune-related processes. Hypoxia and ECM-related processes were enriched in lesions that showed no metabolic response to T-DM1. Interestingly, immune-related processes (e.g., Fc gamma receptor activation, complement cascade) were associated with high [89Zr]trastuzumab uptake and metabolic response. Conclusions: To our knowledge, this study represents the first correlative analysis between [89Zr]trastuzumab tumor uptake and gene expression profiling in humans. Our findings point toward a role of ECM in impairing [89Zr]trastuzumab tumor uptake and T-DM1 metabolic response in advanced HER2-positive breast cancer, and highlight the potential of molecular imaging to depict tumor microenvironment features.

  Study EGAS50000000470

• Rapid Evolution of a Skin Lightening Allele in Southern African KhoeSan

  The genetic architecture and polygenicity of skin pigmentation is explored in KhoeSan communities, including Nama individuals whose phenotype and genotype data are provided in this dataset. By pairing genotypes and quantitative spectrophotometric skin pigmentation phenotypes, we show that skin pigmentation is highly heritable in KhoeSan, yet known pigmentation loci only explains a small fraction of the phenotypic variance. Using genome-wide association analyses, we identified both canonical and non-canonical skin pigmentation loci. We show that this phenotype is more polygenic and complex than previously characterized. (Martin et al., Cell 2017. PMID: 29195075) Following up on the top associated signal with large effect size in the gene SLC24A5, we demonstrate that the canonical Eurasian nonsynonymous allele was introduced into KhoeSan via a recent migration ~2 kya and was under extremely strong selection. The derived allele was present at high frequency despite controlling for gene flow. With high-throughput sequences in the captured SLC24A5 region, we show that the most common derived haplotype is identical amongst Europeans, eastern African and KhoeSan. Using 4-population demographic simulations with selection, we show that the allele was introduced into the KhoeSan only 2,000 ya via a back-to-Africa migration and then experienced a selective sweep.

  Study phs001753

• Integrative Gene Regulatory Network Analysis Discloses Key Driver Genes of Fibromuscular Dysplasia

  Fibromuscular dysplasia (FMD) is a poorly understood vascular disease that can lead to hypertension, stroke, myocardial infarction and even death. In 2013 we initiated the DEFINE study (ClinicalTrials.gov Identifier: NCT01967511), which has now recruited > 440 subjects and which aims to unravel the pathobiological mechanisms of this disease. Here, by integrating DNA genotype and RNA sequence data from primary fibroblasts of 83 FMD patients and 71 matched healthy controls from the DEFINE study, and its precursor the CAUSE study, we inferred 18 gene regulatory co-expression networks, four of which were found to act together as an FMD-associated super network in the arterial wall. Molecular studies indicated that this super network, termed SN-A and with the top key driver gene UBR4, governs multiple aspects of vascular cell physiology and functionality, including collagen/matrix production. The effects of UBR4 knockdown were also investigated in commercially available aortic smooth muscle and fibroblast cell lines by RNA sequencing, and these results are included in these datasets.Note, that of the 154 subjects in this analysis, 62 did not provide consent to have their genomic data made publicly available. Therefore the human subject data available here is from the 92 study participants who provided written informed consent to share their deidentified genomic data publicly.

  Study phs003674

• National Cancer Institute Cancer Genome Characterization Initiative (CGCI)

  The Office of Cancer Genomics at the National Cancer Institute sponsored a series of studies as part of the Cancer Genome Characterization Initiative (CGCI) to assess novel emerging sequencing technologies in cancer. The CGCI program included comprehensive characterization of the genetic aberrations found in different pediatric and/or adult tumors. CGCI characterized a number of B-cell non-Hodgkin lymphomas (including diffuse large B-cell lymphoma (DLBCL) from patients with and without HIV+ infection, follicular lymphoma (FL), as well as adult and pediatric Burkitt lymphomas), and additional HIV-associated tumors (including DLBCL, lung, and cervical cancers). All data from these projects is available at the NCI Genomic Data Commons. Individual project descriptions are available by disease on the substudy pages (links are included at the top of this page). Brief summaries are as follows: Non-Hodgkin Lymphoma (NHL) - CGCI investigators probed genomic alterations more deeply than had previously been possible by using state-of-the-art RNA sequencing (mRNA-seq) and whole genome shotgun sequencing (WGS) coupled with leading edge bioinformatics, data management and analysis approaches. The project sequenced tumor DNA and/or RNA from 117 NHL tumor samples and 10 cell lines. This included the genomes or exomes of 1 Follicular Lymphoma (FL) and 13 diffuse large B-cell lymphoma (DLBCL) cases, all with matched constitutional DNA sequenced to comparable depths, RNA-sequencing (mRNA-seq) of 92 DLBCL, 12 FL and 8 B-cell NHL cases with other histologies and 10 DLBCL-derived cell lines. The DLBCL cases and cell-lines are from the two major subtypes of DLBCL: germinal center B-cell (GCB) and activated B-cell (ABC). HIV+ Tumor Molecular Characterization Project (HTMCP) - This project was a joint effort of the Office of Cancer Genomics (OCG) and the Office of HIV and AIDS Malignancy (OHAM). Its goals were to characterize HIV-associated cancers (obtained from HIV-infected patients) and compare them to the same types of cancers from patients without HIV infection. Investigators performed 30X genome sequencing of 100 cases of paired tumor and germline DNA, along with transcriptome sequencing in each of 3 types of HIV+ tumors (DLBCL, lung and cervical cancers). These platforms allow discovery of mutations both in coding and non-coding genomic regions, gene expression and genomic alterations (including translocations, insertions and deletions). Comparing tumors of cancer patients both with and without HIV-infection provides insight into the potential function of this virus in certain cancers. Burkitt Lymphoma Genome Sequencing Project (BLGSP) - This project was a collaborative effort between the National Cancer Institute and the Foundation for Burkitt Lymphoma Research to develop a databank of the many alterations found in Burkitt lymphoma (BL), an uncommon type of Non-Hodgkin lymphoma that occurs most often in children and young adults. The goal of the BLGSP was to explore potential genetic changes in patients with BL that could lead to better prevention, detection and treatment of the cancer. The project characterized the alterations of the tumors' genomes (with matched normal as control) and transcriptomes by sequencing the DNA and RNA of each case. Using the data generated, the ultimate goals of the project was to discover the molecular changes that are present in BL patients and then determine how those changes correlate with treatment regimen and outcome. CGCI data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the CGCI Publication Pages at the GDC (Please see the "Supplemental Links" section of any CGCI publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original CGCI research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data), as well as higher level data generated by the GDC. Please see the CGCI Use and Publication Guidelines for updated details on the sharing of any CGCI substudy data, including how to cite CGCI.To learn more about the CGCI studies, please visit the CGCI Program website.

  Study phs000235