Search Results - EGA European Genome-Phenome Archive

Meta-analysis of Genome-Wide-Association Sudies for plasma Factor XI

Coagulation factor XI (FXI) has become increasingly interesting for its role in pathogenesis of thrombosis. We performed a genome-wide association study (GWAS) for plasma FXI levels, using novel data imputed to the 1000 Genomes reference panel. Individual GWAS analyses, including a total of 16,169 European individuals from the ARIC, GHS, MARTHA and PROCARDIS studies, were meta-analyzed, and results are presented here.

Study EGAS00001002123

Immunological hallmarks for clinical response to BCG in bladder cancer

Intravesical Bacillus Calmette-Guerin (BCG) is an effective immunotherapy for non-muscle invasive bladder cancer (NMIBC). However, recurrence and progression remain frequent warranting deeper insights into its mechanism. We herein comprehensively profiled blood and tissues obtained from NMIBC patients before, during and after BCG treatment using cytometry by time-of-flight (CyTOF) and RNA sequencing to identify the key immune subsets crucial for anti-tumour activity.

Study EGAS00001004764

Metagenomic Deep Sequencing in Meningitis and Encephalitis

This is a prospective observational study seeking to identify pathogens in cases of unexplained neurological disease, particularly those in which there is a presumed infectious cause. This next generation analytical approach will hopefully allow for rapid identification of foreign genomic material, and through a sophisticated bioinformatics pipeline developed in the DeRisi lab, these foreign genomic sequences can be aligned to all known sequences in publicly available databases (i.e. GenBank) which may allow for identification of novel pathogens or known pathogens that are not frequently tested for as part of standard diagnostic work-ups.

Study phs001067

Molecular Biomarkers of Obesity and Metformin Response in Endometrial Cancer: Analysis of GOG-0286B

The primary endpoint for the phase 2 study was progression free survival (PFS), and the primary endpoint for the phase 3 study was overall survival (OS). Data from phase 2 were included in the phase 3 analysis. Tissue was collected from patients with endometrial cancer who participated in the study (NCT02065687). The tissue will be analyzed for genetic data and combined with the clinical data to see if some gene variants are associated with longer PFS or OS, particularly on the metformin arm of the study.

Study phs002934

Whole Exome Sequencing in Familial Parkinson Disease

We have an ongoing study that has recruited families having at least a sibling pair with Parkinson disease (PD). Families have been screened for mutations in known PD causative genes (LRRK2, parkin, etc). Following review of families without a causative mutation, we selected families for whole exome sequencing that had the strongest history of PD and with the most definitive diagnosis. All families have at least 3 affected family members who were evaluated as part of this study. Only affected family members were included for whole exome sequencing.

Study phs000376

Deep Sequencing of 3 Cancer Cell Lines on 2 Sequencing Platforms (Illumina HiSeqX and NovaSeq)

To test the performance of a new sequencing platform, develop an updated somatic calling pipeline and establish a reference for future benchmarking experiments, we performed whole-genome sequencing of 3 common cancer cell lines (COLO-829, HCC-1143 and HCC-1187) along with their matched normal cell lines to great sequencing depths (up to 278X coverage) on both Illumina HiSeqX and NovaSeq sequencing instruments. This dataset can be used for benchmarking purposes by the genomic community and as a reference call set for scientists using these 3 cell lines.

Study phs001839

Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure (InterGEN Study)

This research study focuses on the genomic and psychological environmental effects on blood pressure among mothers and their children. The study includes 250 mothers who self-identify as AA/black, and 250 children between the ages of 3 and 5 years old at the time of enrollment. The study is longitudinal and data collection interviews are scheduled every six months for two years after enrollment, for a total of four participant interviews. Assessment is as follows: genetic (time 1 only) and psychological factors (every six months for two years).

Study phs001792

NHLBI TOPMed: Severe Asthma Research Program (SARP)

The overall goal of the Severe Asthma Research Program (SARP) is to identify and characterize subjects with severe asthma to understand pathophysiologic mechanisms in severe asthma. Subjects with mild and moderate asthma were recruited for comparison but the program was enriched for subjects with severe asthma from multiple centers. Subjects were comprehensively phenotyped for asthma related traits including lung function, atopy, questionnaires on medical and family history, exhaled nitric oxide and health care utilization including exacerbations and symptoms. Asthma is a heterogenous disease. Cluster analysis in SARP has shown multiple subphenotypes and endotypes.

Study phs001446

Coeliac Disease Immunochip dataset

Illumina Immunochip genotype data for coeliac disease and control samples. Data is in PLINK binary format. Calling algorithm for genotypes is based on GenomeStudio (GenTrain), with manual clustering of selected variants (please see published manuscript). Genotypes called in this way may not be exactly identical to those generated by other algorithms - this is particularly relevant for groups wishing to utilise the control data (e.g. 1958 Birth Cohort). Please contact the investigators if you wish to discuss access to other data formats (e.g. .idat).

Study EGAS00000000053

Discordant_Monozygotic_Twins_ALS(Genetics)

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. Regarding genetic factors, pathogenetic mutations in more than 35 genes have been identified as playing a role in disease pathogenesis. However, a substantial portion of ALS heritability remains unaccounted for, pointing to the potential involvement of additional genetic and epigenetic factors. For this reason, we conducted a multi-omics study on a monozygotic twin pair discordant for amyotrophic lateral sclerosis, performing whole exome sequencing, transcriptomic and epigenetic analyses to gain crucial insights into underlying pathogenetic disease mechanisms. Here, we share genetic data.

Study EGAS50000000908

ctDNA Quantification in Blood Plasma Using Deep Learning Based Fragle Tool

The project aims to develop an easy to use software named Fragle that can quantify ctDNA in blood plasma. This can help in cancer screening and progress monitoring from simple blood test without any need for tumor biopsy. We aim to make Fragle usable for both low pass whole genome sequencing and targeted sequencing data of cell free DNA. Fragle can work directly on the raw bam files mapped to hg19/GRCh37. We are uploading the bam files used in this study for Fragle evaluation.

Study EGAS50000000122

Reconstitution of Human Brain Cell Diversity in Organoids via Four Protocols [time-course bulkRNAseq]

Time-course bulk-RNA sequencing of brain organoids grown in four distinct growth protocols designed to generate dorsal (D) and ventral (V) forebrain, midbrain (M) and striatum (S) tissue at days 13 (for dorsal and ventral)/16 (for midbrain and striatum), 25, 40, 80 and 120. Per per cell line-protocol-timepoint combination three organoids (biological replicates) were grown. For reference, also three samples of the pluripotent stem cells across cell lines, not yet exposed to any protocol, were sequenced (day 0, pluripotent).

Study EGAS50000000663

The_Causes_of_Clonal_Blood_Cell_Disorders_Study___SCOR_Custom

We took a bone marrow aspirate and peripheral blood samples from a healthy patient aged around 60, and use flow cytometry to isolate 100 HSCs, 50 MEPs, and 50 GMPs. We grew these up into colonies, then whole genome sequenced each colony. Somatic mutations act as a unique barcode for each clone. We have designed a panel for targeted resequencing of the mutations that we find. We are now looking for these mutations in the peripheral blood, to see the dynamics of how HSCs contribute to the peripheral blood in health.

Study EGAS00001002257

Osteosarcoma mate-pair and RNA-sequencing

DNA mate pair and RNA sequencing data of conventional osteosarcomas. Mate pair libraries, with average insert sizes of 2-4 kb, were prepared for sequencing using the Nextera Mate Pair Library Preparation Kit. Paired-end 76 base pair reads were generated using an Illumina NextSeq 500 sequencing instrument. Total RNA was enriched for polyadenylated RNA using magnetic oligo(dT) beads. Enriched RNA was prepared for sequencing using the TruSeq RNA Sample Preparation Kit v2 and paired-end 151 base pair reads were generated from the cDNA libraries using an Illumina NextSeq 500 instrument.

Study EGAS00001003842

KIR gene content imputation from single-nucleotide polymorphisms in the Finnish population

The killer cell immunoglobulin-like receptor (KIR) gene cluster on chromosome 19 encodes cell surface glycoproteins that bind class I human leukocyte antigen (HLA) molecules as well as some other ligands. KIR gene gene copy number variation associates with the outcome of transplantations and susceptibility to immune-mediated diseases. Here we describe a stand-alone and freely available gene content imputation for 12 KIR genes. The models were trained using 818 Finnish biobank samples genotyped for 5774 KIR-region SNPs and analysed for KIR gene content with targeted sequencing.

Study EGAS00001005457

Genome-Wide Association Study of Amyotrophic Lateral Sclerosis in Finland

The genetic etiology of amyotrophic lateral sclerosis (ALS) is not well understood. Finland has one of the highest incidence of ALS in the world, making it an ideal population for study. To identify genetic risk factors for this fatal neurodegenerative disease, we undertook a genome-wide association study of 405 Finnish patients diagnosed with ALS and 497 Finnish controls. Two loci that exceeded the Bonferroni threshold for genome-wide significance were identified. One was located on chromosome 21q22, corresponding to the known autosomal recessive D90A allele of the SOD1 gene. The other was detected on the short arm of chromosome 9, which had been previously identified in linkage studies of families with ALS. Together, these two loci account for most of the increased incidence of ALS observed in this population.

Study phs000344

Identifying autosomal recessive mutations causing neurological disorders

The objective of this study is to resequence of targeted intervals containing autosomal recessive variants causing neurological disorders in consanguineous pedigrees. Using homozygosity mapping, three intervals of very different sizes have previously been unambiguously mapped for three different neurological diseases: 2.4Mb, 8Mb and 14.3Mb in size, for Microlissencephaly, Severe Mental Retardation and Complicated hereditary spastic paraplegia respectively. This study is a pilot to assess how well custom targeted resequencing performs across a broad size range of intervals. The study design is to use a different custom capture probe set for each interval, pulldown from a single patient from each family, and sequence 1 lane using Illumina paired-reads for each sample. Candidate variants will be followed up in the families themselves, and in patients with similar phenotypes from outbred populations.

Study EGAS00001000023

Evolutionary Origins of Recurrent Pancreatic Cancer

Surgery is the only curative option for patients with Stage I/II pancreatic cancer, nonetheless most patients will recur after surgery and die of their disease. To identify novel opportunities for management of recurrent pancreatic cancer we performed whole exome or targeted sequencing of 10 resected primary cancers and their matched intrapancreatic recurrences or distant metastases. We identified that recurrent disease develops from a monophyletic or polyphyletic origin, and this distinction has potential clinical relevance. In all patients, treatment induced genetic bottlenecks led to a modified genetic landscape and subclonal heterogeneity for driver gene alterations in part due to intermetastatic seeding. In one patient what was believed to be recurrent disease was an independent (second) primary tumor. These findings strongly advocate for routine post-treatment sampling in the management of recurrent pancreatic cancer.

Study EGAS00001004097

Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia

In this study we generated single-cell whole transcriptome and surface marker expression data for 24 samples of 19 AML patients as well as one healthy donor. We followed the CITEseq protocol with the 3' 10x Genomics scRNAseq kit version 3.1 To increase the coverage of the mitochondrial genome we generated mitochondrial libraries following a protocol termed Optimized 10x. Based on TAPseq, we generated libraries to increase the coverage of selected nuclear SNVs. Exome sequencing was generated for 15 patients to identify nuclear variants. Bulk ATAC was obtained for 9 samples to facilitate the discovery of mitochondrial SNVs. MutaSeq (modified version of SmartsSeq2) was performed on cells from 3 patients. Targeted DNAseq from single-cell derived colonies was generated for 1 patient.

Study EGAS00001007078

Longitudinal genome-wide analysis of progressive chronic lymphocytic leukemia under uniform front-line therapy of pentostatin, cyclophosphamide, and rituximab

Samples from two-center prospective phase 2 clinical trail conducted at Ohio State University (Columbus, OH) and Mayo Clinic (Rochester, MN) were analyzed in 12 cases. All patients had progressive CLL as defined by National Cancer Institute (NCI) Working Group criteria. Patients provided written informed consent for correlative studies according to the Declaration of Helsinki on an institutional review board approved protocol for the collection and use of samples for research purposes from both participating institutions. Eligible patients received a regimen consisting of pentostatin (2 mg/m2), cyclophosphamide (600 mg/m2), and rituximab (375 mg/m2) provided intravenously on day 1 of a 21-day cycle for a maximum of 6 cycles. Responses were assessed by NCI Working Group criteria and included a bone marrow evaluation and two-color flow cytometry 2 months after completion of therapy. Peripheral blood samples from these patients collected longitudinally before (Pre-Baseline), at (Baseline) and after therapy (Relapse) were analyzed for genomic heterogeneity and clonal complexity by high throughput Exome sequencing.

Study phs000794

POISED (Peanut Oral Immunotherapy: Safety, Efficacy, and Discovery)

Phase 2 POISED (Peanut Oral Immunotherapy: Safety, Efficacy, Discovery) Study In this randomized, double-blind, placebo-controlled (DBPC) clinical trial, blinded placebo group received oat flour, whereas in active participants, dosage was built-up for over ~ 52 weeks and subsequently maintained on 4000 mg peanut protein, daily for next 52 weeks. 80 (98.77%) per-protocol active participants passed the food challenge at week 104. Subsequently, for 12 weeks, peanut ingestion was avoided in a randomized group of 51 blinded active participants (i.e., peanut avoidance group). 21 (41.2%) participants in the peanut avoidance group passed the 4000 mg double-blind, placebo-controlled food challenge (DBPCFC) without any allergic reaction at week 117, thus demonstrating sustained unresponsiveness. These 21 participants continued oral immunotherapy (OIT) for every three months and afterwards were allowed to continue peanut OIT discontinuation if they passed. 8 participants passed the DBPCFCs, 12 months after peanut discontinuation (week 156), i.e. they achieved long-term sustained unresponsiveness with no allergic reaction in response to food challenge. For detailed description, please refer to Chinthrajah et al., PMID: 31522849.

Study phs003071

NHLBI TOPMed: Whole Genome Sequencing of Venous Thromboembolism (WGS of VTE)

This study consists of 338 VTE cases from an inception cohort of Olmsted County, MN residents (OC) with a first lifetime objectively-diagnosed idiopathic VTE during the 40-year study period, 1966-2005. All living study subjects were invited to provide a whole blood sample at the Mayo Clinical Research Unit for leukocyte genomic DNA and plasma collection. For living study subjects who did not provide a blood sample, we retrieved any leftover blood ("waste" blood) from samples collected as part of routine clinical diagnostic testing and used this to extract DNA after obtaining patient consent. For deceased cases, with IRB approval, we extracted DNA from any available stored tissue within the Mayo Tissue Archive. This "tissue" DNA has been successfully genotyped in prior studies. Three trained and experienced study nurse abstractors reviewed the complete medical records in the community of all potential cases. Note: WGS sample IDs for the previous GENEVA study cases (phs000289) are included in this dataset. The phenotypes for the GENEVA study are located under the above phs number.

Study phs001402

DCIS fresh frozen fragmentomics dataset

Ductal carcinoma in situ (DCIS) is a non-obligate precursor lesion of breast cancer (BC). Often detected by mammography, most cases are managed through surgical and/or radiotherapy approaches. Today, it is not possible to predict which patients will progress to invasive disease. Here, we evaluated high-depth whole-genome sequenced (WGS) DCIS, enriched for highgrade clinical lesions, to understand whether deep WGS could reveal biological insights and/or personalized therapeutic vulnerabilities that may be targetable. We find genomic locations that are likely susceptible to producing the initiating lesion for structural variations (SVs) prone to subsequent evolution, termed SHOREs (Susceptibility HOtspots for Rearrangements and ongoing Evolution). We additionally highlight individualized therapeutic potential that would otherwise not be appreciable without WGS. We posit that holistic WGS profiling could offer a more precise stratification approach, discerning higher-risk cases for prospective clinical studies on personalized therapies, from truly low-risk cases suitable for active monitoring. To substantiate our WGS findings, we also performed RNAseq on the same samples, this EGA study contains the RNAseq data.

Study EGAS50000001475

In vitro modeling of renal injury-induced cardiac effects using human iPSC-derived organoids

The bidirectional communication between the heart and kidney essential for physiological homeostasis, with injury in one organ often impairing in the other. Although cardiorenal crosstalk is clinically relevant in conditions such as cardiorenal syndrome (CRS), the underlying molecular and cellular mechanisms remain poorly understood, and in vitro models are lacking. Here, we developed a co-culture system using human induced pluripotent stem cell (hiPSC)-derived kidney organoids (kOs) and cardiac microtissues (cMTs) to model the cardiorenal axis. kOs exposed to nephrotoxic compounds for 72 hours displayed glomerular and tubular damage, reduced cell viability, and altered gene expression. When subsequently co-cultured with cMTs for 72 hours, injured kOs induced secondary cardiac dysfunction characterized by reduced cell viability, impaired contractility, and endothelial cell loss. These findings demonstrate that kidney injury can elicit detrimental effects on cardiac tissues in vitro. This organoid-based platform offers a valuable tool for studying cardiorenal interactions and underlines the potential of multi-organ models for investigating mechanisms of interdependent organ dysfunction.

Study EGAS50000001300

Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer

No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing.

Study EGAS50000000211

RNA sequencing data of pediatric B-other acute lymphoblastic leukemia

For a long time, approximately 70% of childhood B-ALL cases could be classified routinely, and the remaining 30% were classified into the “B-other” group lacking the known genetic features. However, more recently, new genomic tools have uncovered new subtypes among the B-other groups. Approximately 10% of B-ALL cases lack the recurrent genetic abnormalities, and are referred as "B-other". They are typically more heterogeneous than other subtypes of B-ALL, and their prognoses are more variable. In a more recent update of the B-ALL classification, 27 subtypes were identified (Arber et al., 2022). The identification of some of these subtypes is dependent on NGS methods, such as RNA sequencing, which are not routinely used in all clinical laboratories. For example, ETV6::RUNX1-like and DUX4-rearranged subtypes have been identified using RNA sequencing. For this study, subtype predictions for some of the cases were acquired by using the ALLIUM (Krali et al., NPJ Precis Oncol., 2023) and ALLCatchR (Beder et al., Blood, 2022) tools for the RNA sequencing data.

Study EGAS50000001803

Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection

Deregulation of transcription factors (TFs) is an important driver of tumorigenesis, but non-invasive assays for assessing transcription factor activity are lacking. We Here we developed and validated a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyzed whole genome sequencing data for >1,000 cell-free DNA samples from cancer patients and healthy controls using a newly developed bioinformatics pipeline developed by us that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observe patient-specific as well as tumor-specific patterns, including accurate prediction of tumor subtypes in prostate cancer, with important clinical implications for the management of patients. Furthermore, we show that cell-free DNA TF profiling is capable of detection of early-stage colorectal carcinomas. Our approach for mapping tumor-specific transcription factor binding in vivo based on blood samples makes a key part of the noncoding genome amenable to clinical analysis.

Study EGAS00001003206

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

DNA methylation atlas of normal human cell types

DNA methylation is a fundamental epigenetic mark that governs chromatin organization, cell identity, and gene expression. Here we describe a human methylome atlas, based on deep whole-genome bisulfite sequencing allowing fragment-level analysis across thousands of unique markers for 39 cell types sorted from 205 healthy tissue samples. Replicates of the same cell-type are >99.5% identical, demonstrating robustness of cell identity programs to genetic variation and environmental perturbation. Unsupervised clustering of the atlas recapitulates key elements of tissue ontogeny, and identifies methylation patterns retained since gastrulation. Loci uniquely unmethylated in an individual cell type often reside in transcriptional enhancers and contain DNA binding sites for tissue-specific transcriptional regulators. Uniquely hyper-methylated loci are rare and are enriched for CpG islands, polycomb targets, and CTCF binding sites, suggesting a novel role in shaping cell type-specific chromatin looping. The atlas provides an essential resource for interpretation of disease-associated genetic variants, and a wealth of potential tissue-specific biomarkers for use in liquid biopsies.

Study EGAS00001006791

Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations

It is well established that autism spectrum disorders (ASD) have a strong genetic component; however, for at least 70% of cases, the underlying genetic cause is unknown. Under the hypothesis that de novo mutations underlie a substantial fraction of the risk for developing ASD in families with no previous history of ASD or related phenotypes-so-called sporadic or simplex families-we sequenced all coding regions of the genome (the exome) for parent-child trios exhibiting sporadic ASD, including 189 new trios and 20 that were previously reported. Additionally, we also sequenced the exomes of 50 unaffected siblings corresponding to these new (n = 31) and previously reported trios (n = 19), for a total of 617 individual exomes from 209 families deposited in dbGaP. Here we show that de novo point mutations are overwhelmingly paternal in origin (4:1 bias) and positively correlated with paternal age, consistent with the modest increased risk for children of older fathers to develop ASD. Moreover, 39% (49 of 126) of the most severe or disruptive de novo mutations map to a highly interconnected beta-catenin/chromatin remodelling protein network ranked significantly for autism candidate genes. In proband exomes, recurrent protein-altering mutations were observed in two genes: CHD8 and NTNG1. Mutation screening of six candidate genes in 1,703 ASD probands identified additional de novo, protein-altering mutations in GRIN2B, LAMC3 and SCN1A. Combined with copy number variant (CNV) data, these results indicate extreme locus heterogeneity but also provide a target for future discovery, diagnostics and therapeutics.

Study phs000482

NHLBI TOPMed: Genetic Epidemiology of COPD (COPDGene)

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States, and the only leading cause of death that is steadily increasing in frequency. This project established a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,720 subjects were recruited, including control smokers and nonsmokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 and PRISm). This cohort is being used for cross-sectional analysis, and long-term longitudinal follow-up visits after five years and after ten years are also being performed. The primary focus of the study is to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The aims for this study are: Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, that will provide data to enable the broad COPD syndrome to be decomposed into clinically significant subtype; Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes; Distinct genetic determinants influence the development of emphysema and airway disease. The TOPMed analysis will include approximately 10,500 subjects with whole genome sequencing after quality control is completed. Comprehensive phenotypic data for COPDGene subjects is available through dbGaP study phs000179.

Study phs000951

NIDDK IBD Genetics Consortium Ulcerative Colitis Genome-Wide Association Study

This dataset contains data for 1,028 white, non-Hispanic, European ancestry individuals with ulcerative colitis who were included in a genome-wide association study published by Silverberg et al. (2009). These individuals were ascertained in North America and selected to have either left-sided or extensive disease (i.e., individuals with proctitis only were excluded). Genotyping was performed using the Illumina HumanHap300v2 (n = 540) and HumanHap550v3 (n = 488) Genotyping BeadChips at the Feinstein Institute for Medical Research. Control data (not included) were obtained from the NIDDK IBD Genetics Consortium's Crohn's Disease GWAS (available from dbGaP) and from studies 64 and 65 deposited in the Illumina iControlDB. Seven hundred eighty individuals in this dataset were taken from the NIDDK IBD Genetics Consortium cell line repository (http://www.niddkrepository.org). These individuals are identified in the file dbGaP_SubjectDS.txt. The subject IDs for these individuals may be used to request corresponding samples for follow-up research through the repository. In addition, complete phenotype data for these individuals are included, collected using the Consortium's forms and phenotyping manual (both included). The remaining 248 individuals were identified from pre-existing collections ascertained by members of the Consortium or their collaborators. For these samples, several of the items in the phenotype file are incomplete. Those who wish to replicate the results in Silverberg et al. should note that 6 individuals with missing genotype rates > 0.07 were excluded from that analysis (leaving 1,022 affected samples total). In addition, the minor allele frequencies (MAFs) reported in the publication were calculated using only those individuals who were included in the allelic association tests (n = 977 for SNPs included in the HumanHap300 and n = 476 for SNPs included only in the HumanHap550). These tests were performed using conditional logistic regression on gender-ancestry strata; individuals who were not placed in a stratum (using the procedure described in the supplementary information for Silverberg et al.) were excluded. The indicator variables hh300 and hh550 in the file dbGaP_PhenotypeDS.txt identify the samples included in the allelic association tests, and may be used to replicate the published MAFs among affected individuals.

Study phs000345

Data access committee for white blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer

Dac EGAC00001001435

CGMH data access committee for the CGMH-OCCC-WES data

Dac EGAC50000000028

The data access committee for Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

Dac EGAC50000000588

DAC for pediatric AML genomic sequences

DAC for dataset containing matched tumor-healthy genomic sequences from patients with pediatric AML

Dac EGAC50000000666

DAC for DLBCL dataset

Data Access Committee for cfDNA sequencing dataset from 290 samples from patients with DLBCL and HGBL.

Dac EGAC50000000257

DAC for the access to IMMUcan data

This DAC will assess the requests for the access to IMMUcan data

Dac EGAC50000000829

Nrf2 transcript alterations

WGS and RNA-seq data for Nrf2 study

Study EGAS00001001740

Metastatic_Prostate_Follow_Up_2

Validation/deeper sequencing for metastatic prostate cancer samples

Study EGAS00001000756

Metastatic_Prostate_Follow_Up

Validation/deeper sequencing for metastatic prostate cancer samples

Study EGAS00001000730

Targeted Gene Panel for 171 PTCLs

Dataset EGAD00001003967

WGS data for NRF2 study

WGS data for cell lines and clinical samples

Dataset EGAD00001002244

Phase II trial of targeted immune-depleting chemotherapy and reduced-intensity allogeneic hematopoietic stem cell transplantation using 8/8 and 7/8 HLA-matched unrelated donors and utilizing two graft-versus-host disease prophylaxis regimens for the treatment of leukemias, lymphomas, and pre-malignant blood disorders

Background: Major problems with stem cell transplantation (SCT) for cancer treatment are a lack of suitable donors for patients without an HLA tissue-matched sibling and graft-versus-host disease (GVHD), a serious side effects of immune-suppressing chemotherapy that is given to bring the cancer under control before SCT. In GVHD, the patient's immune system attacks the transplanted donor cells. This study will try to improve the results of SCT from unrelated HLA-matched donors using targeted immune-depleting chemotherapy to bring the cancer under control before transplantation and to lower the chance of graft rejection, followed by reduced-intensity transplant chemotherapy to make the procedure less toxic. Objectives: To evaluate the safety and effectiveness of targeted immune-depleting chemotherapy followed by reduced-intensity transplant chemotherapy in patients with advanced cancers of the blood and immune system. To evaluate the safety and effectiveness of two different drug combinations to prevent GVHD. Both regimens have been successful in preventing GVHD, but they work by different mechanisms and affect the rebuilding of the immune system after the transplant. Eligibility: People 18 to 74 years of age with advanced or high-risk cancers of the blood and immune system who do not have a suitable HLA-matched sibling. Design: All patients receive chemotherapy before transplant to treat the cancer and suppress immune function. All patients receive a conditioning regimen of cyclophosphamide for 4 days and fludarabine for 4 days before SCT to prepare for the transplant. Patients are randomly assigned to one of two combination drug treatments to prevent GHVD as follows: Group 1: Tacrolimus starting 3 days before SCT and continuing for 6 months, plus methotrexate on days 1, 3, 6, and 11 post-SCT, plus sirolimus starting 3 days before the SCT and continuing through day 14 following SCT. Group 2: Alemtuzumab for 4 days starting 8 days before SCT, plus cyclosporine starting 1 day before SCT and continuing for 6 months. Patients receive the donor's stem cells and immune cells 2 days after the conditioning regimen. Patients are followed at the clinic regularly for the first 6 months after SCT, and then less often for at least 5 years. Some visits may include bone marrow aspirates and biopsies, blood draws, and other tests to monitor disease status. A skin biopsy, oral mucosa biopsy, and saliva collection are done to study chronic GVHD.

Study phs002021

The data access committee for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

Dac EGAC00001003253

Engineering Immune Cells for Therapy, Institute for Medical Microbiology, Immunology and Hygiene, Technical University Munich

CRISPR engineering of human T cells

Dac EGAC50000000405

Fastq files for SAIF genome

This dataset contain the raw files generated for SAIF genome project

Dataset EGAD00001000254

Screening for human epigenetic variation at CpG islands

Dataset EGAD00001000059

SNP data for Ovarian cancer PRS

SNP data for Ovarian cancer PRS (cases)

Dataset EGAD00001008143

A Comprehensive Platform for Analyzing Longitudinal Multi-Omics Data

PALMO (Platform for Analyzing Longitudinal Multi-omics data) is a platform for analyzing longitudinal data from bulk as well as single cell. It allows to identify inter-, intra-donor variations in genes over longitudinal time points. The analysis can be done on bulk expression dataset without known cell type information or single cell with cell type or user defined groups. It allows to infer stable and variable features in a given donor and each cell type or a user defined group. The outlier analysis can be performed to identify technical/biological perturbed samples in a donor or a participant. Further, differential analysis can be performed to decipher time-wise changes in gene expression in a cell type. The data that is available in the dbGaP is the demo longitudinal samples used in the study, which includes hashed raw fastq files for single-cell RNA-sequencing (scRNA-seq) and non-hashed fastq files for single-cell ATAC-sequencing (scATAC) experiment.

Study phs003203

Resident memory CD8 T cells persist for years in human small intestine

Resident memory CD8 T cells (Trm) have been shown to provide effective protective responses in the small intestine (SI) in mice. A better understanding of the generation and persistence of SI CD8 Trm cells in humans may have implications for intestinal immune-mediated diseases and vaccine development. Analyzing normal and transplanted human SI we demonstrated that the majority of SI CD8 T cells were bona fide CD8 Trm cells that survived for over 1 year in the graft. Intraepithelial and lamina propria CD8 Trm cells showed a high clonal overlap and a repertoire dominated by expanded clones, conserved both spatially in the intestine and over time. Functionally, lamina propria CD8 Trm cells were potent cytokine-producers, exhibiting a polyfunctional (IFN-γ+ IL-2+ TNF-α+) profile, and efficiently expressed cytotoxic mediators after stimulation. These results suggest that SI CD8 Trm cells could be relevant targets for future oral vaccines and therapeutic strategies for gut disorders.

Study EGAS00001003676

Loss of Epigenetic Barrier is Required for Enhancer Hijacking-Mediated Oncogenic Transcription

Structural variants (SVs) involving enhancer hijacking can disrupt chromatin topologies to cause oncogene activation in cancer genomes, yet the molecular determinants for the transcriptional output of enhancer hijacking remain largely unknown. We developed a multimodal approach to integrate genome sequencing, chromosome conformation, and sequence-based deep learning for quantitative analysis of transcriptional effects and structural reorganization imposed by SVs in leukemic genomes. We identified candidate pathogenic SVs including recurrent t(5;14) translocations that cause the hijacking of BCL11B enhancers for oncogenic activation of TLX3-dependent transcriptional programs. By engineering patient-associated t(5;14) in isogenic leukemia cells, we uncovered an uncharacterized mechanism whereby DNA methylation serves as an epigenetic barrier to enhancer hijacking and loss of epigenetic barrier is a molecular determinant for the transcriptional output of pathogenic SVs. Hence, leveraging the epigenetic barriers of SV-mediated oncogenic programs may provide new opportunities to reprogram gene regulation as epigenetic therapies in human disease.

Study EGAS00001006140

Northern Ireland COhort for the Longitudinal study of Ageing

The Northern Ireland COhort for the Longitudinal study of Ageing (NICOLA) is a representative sample of ~8,500 people from across Northern Ireland. The study, which was set up in 2012, aims to understand what it is like to grow older in Northern Ireland. • NICOLA has a strong focus on molecular biomarkers so there is complementary genetic, epigenetic and transcriptomic data available for a subset of individuals. • We inherit much of our DNA from our parents while a small amount of this material changes as we get older. In NICOLA we have 551,839 directly genotyped and 18,148,478 imputed Single Nucleotide Polymorphisms (SNPs) currently available for 2969 participants. • Summary statistics for the association of these gene polymorphisms with ~30 phenotypes were generated. • Epigenetics provides a link between our inherited DNA and environmental influences from a person’s diet, medication and lifestyle. NICOLA has the epigenetic quality controlled profiles of 1984 individuals arising from variations in DNA methylation at 862,927 genetic sites.

Study EGAS00001007915

NINDS-Genome-Wide Genotyping in Parkinson's Disease: First Stage Analysis and Public Release of Data

Epidemiological studies have estimated a cumulative prevalence of PD of greater than 1 per thousand. When prevalence is limited to senior populations, this proportion increases nearly 10-fold. The estimated genetic risk ratio for PD is approximately 1.7 (70% increased risk for PD if a sibling has PD) for all ages, and increases over 7-fold for those under age 66 years. The role for genes contributing to the risk of PD is therefore significant. This study utilized the well characterized collection of North American Caucasians with Parkinson's disease, and neurologically normal controls from the sample population which are banked in the National Institute of Neurological Disorders and Stroke (NINDS Repository) collection for a first stage whole genome analysis. Genome-wide, single nucleotide polymorphism (SNP) genotyping of these publicly available samples was originally done in 267 Parkinson's disease patients and 270 controls, and this has been extended to include genome wide genotyping in 939 Parkinson's disease cases and 802 controls. The NINDS repository was established in 10-2001 towards the goal of developing standardized, broadly useful diagnostic and other clinical data and a collection of DNA and cell line samples to further advances in gene discovery of neurological disorders. All samples, phenotypic, and genotypic data are available to the research community including to academics and industry scientists. In addition, well characterized neurologically normal control subjects are a part of the collection. This collection formed the basis of this first stage study by Fung et al., and the expanded study by Simon-Sanchez et al. The genotyping data was generated and provided by the laboratory of Dr. Andrew Singleton NIA, and Dr. John Hardy NIA (NIH Intramural, funding from NIA and NINDS). Important links to apply for individual-level data Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Participant Protection Policy FAQ

Study phs000089

Population Architecture using Genomics and Epidemiology (PAGE): Multiethnic Cohort (MEC)

The Multiethnic Cohort (MEC) has established a large biorepository of blood and urine (N=67,000) and cryopreserved lymphocytes (N=15,000) linked to extensive, prospectively collected risk factors (e.g., diet, smoking, physical activity), biomarkers and clinical data for five racial/ethnic groups. This cohort study of over 215,000 men and women in Hawaii and California is unique in that it is population-based and includes large representations of older adults (45-75 yrs at baseline) for five US racial/ethnic groups (Japanese Americans, African Americans, European Americans, Latinos and Native Hawaiians) at varying risks of chronic diseases. Within the PAGE investigation, the MEC proposes to study: 1) diseases for which we have DNA available for large numbers of cases and controls (breast, prostate, and colorectal cancer, diabetes, and obesity); 2) important cancers that are less common (e.g., lung, pancreas, endometrial cancers, NHL) but for which we propose to pool our data with other funded groups; 3) common traits that are risk factors for these diseases (e.g., body mass index/weight, waist-to-hip ratio, height) and 4) relevant disease-associated biomarkers (e.g., fasting insulin and lipids, steroid hormones). The specific aims are: 1) To determine the population-based epidemiologic profile (allele frequency, main effect, heterogeneity by disease characteristics) of putative causal variants in the five racial/ethnic groups in the MEC; 2) for variants displaying effect heterogeneity across ethnic/racial groups, we will utilize differences in LD to identify a more complete spectrum of associated variants at these loci; 3) investigate gene x gene and gene x environment interactions to identify modifiers; 4) examine the associations of putative causal variants with already measured intermediate phenotypes (e.g., plasma insulin, lipids, steroid hormones); and 5) for variants that do not fall within known genes, start to investigate their relationships with gene expression and epigenetic patterns in small genomic studies. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study phs000356.

Study phs000220

How to use EGA Webin?

EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence 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 on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.

Documentation submission/metadata/submission/EGA_webin

International Consortium for Blood Pressure (ICBP)

The ICBP consortium is an international effort to investigate blood-pressure genetics. The consortium was formed by two parent consortia, the CHARGE-BP consortium (Cohorts for Heart and Aging Research in Genomic Epidemiology - blood pressure) and the GBPGEN consortium (Global Blood Pressure Genetics Consortium). In 2011 we performed genome-wide association analyses based on genome-wide SNPs imputed to HapMap for systolic and diastolic blood pressure (SBP and DBP) and mean arterial pressure and pulse pressure (MAP and PP). In 2016 we performed an analysis based on the Cardio-MetaboChip for SBP and DBP. All these datasets are available here, however, full association statistics including effect size directions, only under controlled access by dbGaP.

Study phs000585

Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS)

Advances in antiretroviral therapies (ART) and patient management have improved survival of people living with HIV (PLWH). However, with exposure to ART and associated side effects and toxicities as well as to the virus itself, PLWH are at an increased risk of several chronic diseases. The Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS) research network integrates longitudinal clinical data and treatment management of PLWH and provides research infrastructure to support HIV-associated clinical, social, and behavioral outcomes and comparative effectiveness research using data collected from 8 Centers for AIDS Research clinical sites across United States. For detailed study description, see Kitahata et al. (2008, PMID:18263650).

Study phs001788

A comprehensive proteogenomic pipeline for neoantigen discovery to advance personalized cancer immunotherapy

The accurate identification and prioritization of antigenic peptides is crucial for the development of personalized cancer immunotherapies. Publicly available pipelines to predict clinical neoantigens do not allow direct integration of mass spectrometry immunopeptidomics data, which can uncover antigenic peptides derived from various canonical and non-canonical sources. To address this, we present an end-to-end clinical proteogenomic pipeline, called NeoDisc, that combines state-of-the-art publicly available and in-house software for immunopeptidomics, genomics and transcriptomics with in-silico tools for the identification, prediction, and prioritization of tumor-specific and immunogenic antigens from multiple sources, including neoantigens, viral antigens and high-confidence tumor-specific antigens.

Study EGAS50000000228

Star2xml: metadata converter into XML

Star2xml: metadata converter into XML Welcome to the landing page for star2xml - a tool developed by the European Genome-phenome Archive (EGA) that enables users to convert metadata into XML format that is compliant with EGA's programmatic submission system. For starters, if you are not sure what metadata is in this context, you may want to explore our brief metadata introduction. . Star2xml is useful for users who have already submitted their data to the EGA and want to also submit their metadata programmatically without having to create the XML files manually. The need for these XMLs containing metadata is explained in the EGA's metadata schemas and programmatic submission guidelines. In summary, star2xml allows for users to deposit metadata in a tabular format (e.g. excel spreadsheet) and transform it into a compliant XML format. This saves time in large submissions, where the sheer size of metadata makes it difficult to manage. For smaller submissions, it is recommended to use EGA's Submitter Portal (SP) instead. The installation of the tool is straightforward, and it contains detailed documentation on how to use it in its GitHub repository . While star2xml can help users convert metadata formats, it does not validate the resulting metadata against EGA's schemas. Therefore, after creating your XMLs, you should still validate your metadata before submitting it to EGA, as described in the documentation for programmatic metadata validation.

Documentation tools/star2xml

Identifying causative mutations for Thrombocytopenia with Absent Radii

Thrombocytopenia with Absent Radii is an inherited disorder that manifests itself with major limb skeletal abnormalities and low platelet count (and therefore a bleeding diathesis). The syndrome is well-characterised and defined phenotypically and there is a well-established database of UK-based families affected with ths disorder. The causative mutation for the disorder is yet to be identified. If known, it would allow for pre-natal screening and counselling avoiding life-long care for patients who are affected and are therefore severely disabled. We postulate that exon sequencing of 4 unrelated affected individuals would give enough power to narrow down potential candidate mutations which would thereafter be confirmed using DNA from other affected families.

Study EGAS00001000054

A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

Fragmentomic features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. However, a lack of systematic evaluation of biases in feature quantification has hindered the adoption of such applications. We compared features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes, and validated them in 1,182 plasma samples from published studies. Our results clarify the variations resulting from library preparation and feature quantification methods. We designed the Trim Align Pipeline and the cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualisation, aiming to standardise multimodal feature engineering and integration for machine learning.

Study EGAS00001008051

Next Generation Sequencing platform for targeted Personalized Therapy of Leukemia - Acute myeloid leukemia

The advent of high-throughput next generation sequencing (NGS) technologies that are revolutionizing genomics and transcriptomics by providing a single base resolution tool for a unified deep analysis of diseases complexity allows a fast and cost-efficient fine-scale assessment of the genetic variability hidden within cohorts of patients affected by the same leukemia. That being so, by potentially highlighting inter-individual differences that may play a role in the differential success of diverse therapeutic interventions, they promise to be crucial for selecting the most appropriate medical treatments. The project aims at the identification of novel prognostic biomarkers for acute myeloid leukemia (AML) and studied the molecular differences between aneuploid and euploid AML.

Study EGAS00001005464

Genome-wide analysis for non alcoholic fatty liver disease

Genome-wide association study for the 902 patients of non alcoholic fatty liver disease (NAFLD) including non alcoholic steato hepatitis (NASH) and hepatocellurar carcinoma and 7672 controls.

Study JGAS000126

Haukeland University Hospital Data Access Committee for ParkOme-1 datasets archvied in Federated EGA Norway

Data Access Committee appointed by Haukeland University Hospital for omics datasets for Parkinson's disease and related disorders, generated in studies under the ParkOme project. Omics datasets of different types are generated from fresh frozen brain tissue from individuals with neurodegenerative parkinsonisms and neurologically healthy controls.

Dac EGAC50000000193

WTCCC case-control study for Rheumatoid Arthritis

WTCCC genome-wide case-control association study for Rheumatoid Arthritis (RA) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

Study EGAS00000000011

WTCCC case-control study for Type 1 Diabetes

WTCCC genome-wide case-control association study for Type 1 Diabetes (T1D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

Study EGAS00000000014

WTCCC case-control study for Type 2 Diabetes

WTCCC genome-wide case-control association study for Type 2 Diabetes (T2D) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

Study EGAS00000000016

WTCCC case-control study for Coronary Artery Disease

WTCCC genome-wide case-control association study for Bipolar disorder (CAD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

Study EGAS00000000003

Long-read Nanopore and Ion Torrent sequencing data for BRCA1/2 variant detection

This dataset contains long-read sequencing (LRS) data generated using Oxford Nanopore Technologies (ONT) for the analysis of BRCA1 and BRCA2 variants in individuals referred for hereditary breast genetic testing. The study includes samples previously analyzed using Ion Torrent sequencing, enabling comparison between short-read and long-read sequencing approaches.

Dac EGAC50000000946

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002922

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for monocyte RPMI_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002921

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for monocyte RPMI_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002919

BLUEPRINT September 2016, ATAC-seq for germinal center B cell from tonsil, on Genome GRCh38

ATAC-seq data for 2 sample(s) for germinal center B cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002917

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=6days from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for monocyte RPMI_T=6days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002914

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002913

BLUEPRINT September 2016, ATAC-seq for germinal center B cell from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for germinal center B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002911

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002910

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002909

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002906

BLUEPRINT September 2016, ATAC-seq for unswitched memory B cell from venous blood, on Genome GRCh38

ATAC-seq data for 3 sample(s) for unswitched memory B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002905

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002904

BLUEPRINT September 2016, ATAC-seq for naive B cell from venous blood, on Genome GRCh38

ATAC-seq data for 3 sample(s) for naive B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002902

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

ATAC-seq data for 2 sample(s) for monocyte RPMI_LPS_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002901

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for monocyte RPMI_LPS_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002900

BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38

ATAC-seq data for 1 sample(s) for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

Dataset EGAD00001002899

GIS-LUNGTCR1-2016_WES-FASTQ

This dataset contains FASTQ files for multi-region exome-sequencing of EGFR-mutant lung adenocarcinomas from Asian patient. There are 16 patients and 95 samples in total, including 16 controls and 79 tumors. Multiple runs for each sample, and 368 fastq in total. Please refer to the sample-ID from filename for merging.

Dataset EGAD00001001978

GIS-LUNGTCR1-2016_VAL-FASTQ

This dataset contains FASTQ files of targeted Amplicon deep-sequencing data, for validation of the mutations found in WES. There are 16 patients and 95 samples in total, including 16 controls and 79 tumors. 140 fastq in total, multiple runs for some of the samples. Please refer to the sample-ID from filename for merging.

Dataset EGAD00001001981

ChIP-seq fastq and alignment files

ChIP-seq experiments: fastq files; both ChIP and Input for each sample. Illumina HiSeq 2500. ChIP-seq alignment files for trimmed, mapping q20 and nonredundant reads; both ChIP and Input for each sample. Software: Trim Galore v0.3.7; Bowtie 2 v2.1.0; samtools v1.7

Dataset EGAD00001006279

FASTQ file for paper titled "Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression"

This data set includes 27 full-length transcript sequence generated from PacBio IsoSeq that were used for verify the cancer-specific exons identified in three genes: FN1, COL6A3 and TNC. The data were generated from PDX models of osteosarcoma patients.

Dataset EGAD00001015356

DAC for hepatoblastoma sequencing data

Data Access Committee for sequencing data of hepatoblastoma PDX cell models sequenced under University of Helsinki.

Dac EGAC50000000548

RNA-seq data for NRF2 study

RNA-seq data for clinical samples

Dataset EGAD00001002243

TTN gene targeted sequencing for AMC cohort

TTN gene targeted sequencing for AMC cohort (n=24)

Dataset EGAD00001005497

National Cancer Institute (NCI) Prostate Cancer Genome-Wide Association Study for Uncommon Susceptibility Loci (PEGASUS)

This genome-wide association study was funded by the National Cancer Institute (NCI) to identify uncommon susceptibility loci for prostate cancer. A total of 4,600 prostate cancer cases and 2,840 controls of European ancestry from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial were genotyped using the Illumina HumanOmni2.5 and passed rigorous quality control filters. Additional genotype data (available in dbGap under other accession numbers) from 101 independent controls of European ancestry scanned with the HumanOmni2.5 were also included, resulting in a total of 4,600 cases and 2,941 controls for the published analysis. SNPs from the most promising regions, as determined by rank p-value, under multiple different models as well as select candidate genes were taken forward for replication using a custom Iselect chip in 6,575 cases and 6,392 controls of European ancestry. Results from the primary scan after imputation were then meta-analyzed with the Iselect results as well as results from previous GWAS. In a combined meta-analysis of the primary scan together with the custom Iselect replication and a previous GWAS, thirteen loci reached genome-wide significance (P < 5 x 10-8) for prostate cancer overall; however, each of them confirmed a previously reported locus. Although they did not reach genome-wide significance, we found evidence for two new suggestive loci at chromosome 16q22.2 (PKD1L3, rs12597458, P = 9.67 x 10-8) and 6p22.3 (CDKAL1, rs12198220, P = 2.13 x 10-7). In a combined case-only analysis of 12,518 prostate cancer cases, we identified two loci associated with Gleason score, a pathological measure of disease aggressiveness: rs35148638 at 5q14.3 (RASA1, P=6.49x10-9) and rs78943174 at 3q26.31 (NAALADL2, P=4.18x10-8). In a stratified case-control analysis, the SNP at 5q14.3 appears specific for aggressive prostate cancer (P=8.85x10-5) with no association for non-aggressive prostate cancer compared to controls (P=0.57). Only the cases and controls genotyped on the HumanOmni2.5 specifically for this study are included under this accession number. Controls (n=101) genotyped with the HumanOmni2.5 for another study are posted under a different accession number. Please note that the majority of prostate cancer cases and controls genotyped in CGEMS (and posted under a different accession number) are included in this study.

Study phs000882

Genetic Components of Knee Osteoarthritis (GeCKO) Study: The Osteoarthritis Initiative

The Osteoarthritis Initiative (OAI) is a publicly and privately funded prospective longitudinal cohort with a primary objective of identifying risk factors for incidence and progression of tibiofemoral knee OA. The OAI utilized a focused population-based recruitment to enroll 4,674 men and women between the ages of 45-79 years who either had radiographic symptomatic knee OA or who were without radiographic symptomatic OA in both knees but were considered high risk for OA because they had two or more known risk factors for knee OA. Subjects were recruited into the baseline phase of the OAI at multiple sites throughout the US between 2004 and 2006. All subjects were invited back for follow-up examinations to assess incidence or progression of OA annually, for up to 5 years. Phenotype data from the baseline and follow-up examinations are available for public access from the Osteoarthritis Initiative (OAI) database at http://www.oai.ucsf.edu/. The Genetic Components of Knee Osteoarthritis (GeCKO) Study was initiated in 2009 as a genetic ancillary study to perform a genome-wide association study to identify genetic variants associated with radiographic osteoarthritis. This study included 4,482 individuals participating in the parent OAI study. Following sample cleaning (e.g., removal of duplicates, sex mismatches, poor sample quality, etc.), the final sample set included 4,129 individuals.

Study phs000955

Symptom Clusters in Oncology Patients Receiving Chemotherapy

The parent longitudinal study evaluated the symptom experience of oncology outpatients receiving chemotherapy. Patients completed questionnaires in their homes a total of six times (assessments 1 through 6). The questionnaires were timed to evaluate symptoms associated with the receipt of two cycles of chemotherapy that were administered approximately a month apart. Assessments 1 and 4 evaluated symptoms prior to the receipt of chemotherapy. Assessments 2 and 5 evaluated symptoms in the week following the administration of chemotherapy. Assessments 3 and 6 evaluated symptoms two weeks following the administration of chemotherapy. For this analysis, morning and evening fatigue data from the enrollment assessment (i.e., prior to the second or third cycle of chemotherapy) and the assessment that was done approximately 1 week after administration of chemotherapy were evaluated. Patients completed the Lee Fatigue Scale to obtain information on morning and evening fatigue severity. For the morning fatigue assessment, patients were asked to describe how they “felt over the past week when they woke up in the morning”. For the evening fatigue assessment, they were asked to describe how they felt over the past week “before they went to bed at night”. Medical records were reviewed for disease and treatment information. Epigenome assays (microarray) were completed for 1170 patients. Whole transcriptome sequencing (bulk RNA-Seq) was completed for 651 patients.

Study phs003863

Targeted de-methylation of the FOXP3-TSDR

CD4+ regulatory T cells (Tregs) are key mediators of immunological tolerance and promising effector cells for immuno-suppressive adoptive cellular therapy to fight autoimmunity and chronic inflammation. Their functional stability is critical for their clinical utility and has been correlated to the demethylated state of the TSDR/CNS2 enhancer element in the Treg lineage transcription factor FOXP3. However, proof for a causal contribution of the TSDR de-methylation to FOXP3 stability and Treg induction is so far lacking. We here established a powerful transient-transfection CRISPR-Cas9-based epigenetic-editing method for the selective de-methylation of the TSDR within the endogenous chromatin environment of a living cell. The induced de-methylated state was stable over weeks in clonal T cell proliferation cultures even after expression of the editing complex had ceased. Epigenetic editing of the TSDR resulted in FOXP3 expression, even in its physiological isoform distribution, proving a causal role for the de-methylated TSDR in FOXP3 regulation. However, successful FOXP3 induction was not associated with a switch towards a functional Treg phenotype, in contrast to what has been reported from FOXP3 overexpression approaches. Thus, TSDR de-methylation is required, but not sufficient for a stable Treg phenotype induction. Therefore, targeted demethylation of the TSDR may be a critical addition to published in vitro Treg induction protocols which so far lack FOXP3 stability.

Study EGAS00001004867

Center for Cancer Genomics (CCG) Cancers of Unknown Primary Project (CUPP)

The Cancers of Unknown Primary Project (CUPP) aims to characterize difficult tumor types with the goal of determining future best treatment practices. NCI will utilize whole exome sequencing, copy-number variation, DNA methylation in conjunction with transcriptome sequencing to provide a comprehensive genomic landscape of Cancers of Unknown Primary (CUP). The samples will be processed and submitted for genomic characterization using pipelines and procedures established within the Center for Cancer Genomics (CCG).

Study phs001801

Susceptibility loci for tanning ability in Japanese population identified by genome-wide association study

We performed genome-wide association studies of Japanese Skin Type for Japanese individuals from a cohort study by the Tohoku Medical Megabank Project in order to identify variants related to tanning ability and skin pigmentation. We used imputed genotype data of 9,187 Japanese individuals, of which 4,475 individuals are from Miyagi prefecture and 4,712 individuals are from Iwate prefecture. Skin Type information was obtained from the questionnaire for cohort participants.

Study JGAS000160

Whole Genome Sequencing from patients with multiple myeloma treated with BCL2 inhibitor based treatment

Samples was collected at the Mayo Clinic. MM tumor samples were enriched using the StemCell EasySep Human CD138 positive selection kit II (StemCell, Cambridge, MA). DNA from CD138+ MM cell (tumor) or peripheral blood samples (germline control) at Mayo Clinic (Rochester or Arizona) underwent WGS. For samples collected at Mayo Clinic Rochester, library preparation was completed using the NEB Ultra II (New England Biolabs, Ipswich, MA) and the Nextera Flex systems (Illumina, San Diego, CA) and sequenced at the Mayo Clinic Genome Analysis Core with an approximate depth of 30X for tumor samples and 60X for the germline control. For samples collected at Mayo Clinic Arizona, Novogene was used for WGS following random shearing of the DNA, end-repairs, A-tailed and ligated with Illumina adapters. Sequencing was performed on the Illumina Novaseq 6000 sequencer Reference Genome: GRCh38.

Dataset EGAD50000002132

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