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• PAGE: The Charles Bronfman Institute for Personalized Medicine (IPM) BioMe BioBank

  The Institute for Personalized Medicine (IPM) BioMe Biobank is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM BioMe Biobank populations include 28% African American, 38% Hispanic Latino predominantly of Caribbean origin, 23% Caucasian/White. IPM BioMe Biobank disease burden is reflective of health disparities with broad public health impact. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study (phs000356).

  Study phs000925

• Prostate cancer datasets WGS

  Low pass WGS: 48 samples (5 blood samples from 6 patient data): 22 Tumour cores and 26 normal/benign cores (Next Seq )

  Dataset EGAD00001004466

• Cookies

  Cookies https://ega-archive.org does not identify users on this site. It does use cookies, though. What is a cookie? Cookies are text files containing small amounts of information which are downloaded to your device when you visit a website. They allow a website to remember your preferences and are therefore useful to improve your online experience. Find out more information about cookies. Types of cookies we use Functional These cookies record the columns you wish to display or hide in the results page.Performance These cookies are used to analyse trends, administer the website, track visitor movements and gather broad demographic information for aggregate use. We use the information to compile reports and to help us improve our websites. These cookies are not linked to personally identifiable information. Session cookie A session cookie for a website only exists whilst the user is reading or navigating the website. When the user closes their web browser these cookies are usually removed.

  Documentation cookies

• WGS in insulinomas

  Whole-Genome Sequencing datasets of insulinoma samples and paired blood controls

  Dataset EGAD50000000464

• Transcriptomic profiling of patient-derived xenografts and organoids in prostate cancer

  Dataset contains RNA-seq of 30 samples (normal prostate tissue, human prostate cancer, PDX and organoids).

  Dataset EGAD00001006404

• Whole Exome Sequencing of Human Gastro-esophageal Cancer PDXs

  The dataset includes 51 whole exome sequencing datasets generated using Illumina paired-end sequencing technology. These data derive from 26 patient-derived xenograft (PDX) tumors and their matched normal tissues, which consist of either normal gastric mucosa or blood samples. In one case (GTR0607), the matched normal tissue data are unavailable. As a result, the dataset comprises 102 FASTQ files, providing raw sequencing reads for comprehensive genomic analysis.

  Dataset EGAD50000001407

• WGS data of patient derived organoids (PDO) generated from dMMR colorectal tumor subclones

  The dataset includes bam files from WGS of 26 monoclonal patient derived organoid (PDO) lines isolated from 6 independent tumor subclones of a dMMR colorectal tumor. These organoids were grown as part of an in vitro timecourse experiment for the duration of 9 weeks; bam files represent the mutational load at the start of the timecourse (t0) and the end of the timecourse (t1).

  Dataset EGAD50000000427

• PYDP Papuan Y chromosome Diversity Panel

  The PYDP dataset includes 26 bam files of Y chromosome sequences for Papua New Guinean individuals from different locations, extracted from whole genome sequences. DNA was extrated from saliva samples (Oragen kit). Sequencing libraries were prepared using the TruSeq DNA PCR-Free HT kit. 150 bp paired-end sequencing was performed on the Illumina HiSeq X5 sequencer.

  Dataset EGAD00001008572

• Gynecology and Lubricant Effects (GALE) Study

  The GALE study is a longitudinal study of the association between lubricant use and the vaginal microbiota in women receiving transvaginal ultrasound (TVUS) at the Diagnostic Radiology and Nuclear Medicine Department at the University of Maryland School of Medicine. Participants undergo a clinical exam at enrollment (at least 5 days prior to TVUS) and self-collect daily, mid-vaginal samples in the week leading up to TVUS, including immediately before the procedure. At the TVUS appointment, the sonographer applies a single-use packet of Glide lubricating jelly to the probe. The product was selected for study as it was currently being used in the TVUS clinic at the University of Maryland Medical Center and is a clinical lubricant which is very similar in composition to many sex lubricants. Participants collect samples the evening after TVUS and present for a follow-up clinical exam within a week of TVUS. Participants continue to sample twice weekly for an additional 8 weeks (returning completed kits each week), complete daily health and behavior diaries, and attend one final clinical exam at week 10. The clinician evaluates participants for bacterial vaginosis (BV) at each clinical visit using Amsel's criteria, and also looks for signs of vulvovaginal candidiasis (VVC) and trichomonas using a wet mount.

  Study phs002211

• Warfarin Pharmacogenetics: Pharmacogenetic Optimization of Anticoagulant Response (POAT) and Genetic and Environmental Determinants of Warfarin Response (GEDWR)

  Although the efficacy of warfarin in the treatment and prevention of thromboembolic disorders is proven, it is vastly underutilized with difficulties in management and risk of complications being the main deterrents. Recognition of genetic regulation of warfarin response has fueled efforts to quantify this influence, but the focus has been restricted to select genes and outcomes mainly in European Americans. Race appears to influence warfarin dose requirements with African Americans requiring larger and Asians requiring lower doses compared to Europeans. This variation in dose requirement by race may at least partially be explained by genetic differences. The Genetic and Environmental Determinants of Warfarin Response (GEDWR) and the Pharmacogenetic Optimization of Anticoagulation Therapy (POAT) are prospective cohort study aimed at defining the influence of CYP2C9, VKORC1 and other genes. All patients were followed at monthly intervals from initiation of therapy. At each visit factors influencing warfarin response such as warfarin dose, INR, concurrent medications, etc. were documented. Information on concurrent medications was updated at every clinic visit by self-report and verified by medical record review. Concomitant use of drugs such as drugs that alter warfarin pharmacokinetics, including CYP2C9 inhibitors (e.g., amiodarone), and pharmacodynamics such as antiplatelet agents (e.g. aspirin). Although the a priori hypothesis focused on the candidate-gene approach, with the recognition that the candidate-gene approach is bound by the assumption that our knowledge of genetic influences on warfarin response is complete. Among African Americans known variation in candidate genes (CYP2C9 and VKORC1) explain substantially less variability in warfarin dose requirements. Therefore a genome-wide association study (GWAS) was conducted on African American patients to identify novel variants associated with warfarin dose requirements.

  Study phs000708

• Center for Common Disease Genomics [CCDG] - Cardiovascular: PEGASUS-TIMI 54

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules. Source: ccdg.rutgers.eduFor this study, The Broad Institute of MIT and Harvard generated genetic data for 7,481 individuals from the PEGASUS-TIMI 54 clinical trial run by Brigham and Women's Hospital TIMI study group using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all samples serving as controls.  

  Study phs002243

• Center for Common Disease Genomics [CCDG] - Cardiovascular: ENGAGE Atrial Fibrillation-TIMI 48

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1. Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfFor this study, The Broad Institute of MIT and Harvard generated genetic data for 13,667 individuals from the ENGAGE AF-TIMI 48 clinical trial run by Brigham and Women's Hospital TIMI study group using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all cases with atrial fibrillation.

  Study phs002774

• BLUEPRINT release August 2016, ChIP-Seq for band form neutrophil, on genome GRCh38

  ChIP-Seq data for 4 band form neutrophil sample(s). 26 run(s), 23 experiment(s), 23 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002454

• Potential Modulatory Role of Osteoprotegerin in Bone Metabolism of Patients with 21-Hydroxylase Deficiency

  21-hydroxylase deficiency (21-OHD) is an inherited disorder that results from a mutation on the CYP21A2 gene. It affects the adrenal glands and is the most common cause of congenital adrenal hyperplasia (CAH). 21-OHD CAH causes the body to produce an insufficient amount of cortisol and an excess of androgen, the type of hormone that produces male characteristics. The primary treatment for 21-OHD CAH, glucocorticoid replacement therapy, has been shown to cause bone loss. However, the elevated hormone levels caused by 21-OHD CAH may increase production of the protein osteoprotegerin (OPG), which in turn may protect against bone loss. This study will compare bone density and OPG levels in women who have 21-OHD CAH and have undergone a lifetime of glucocorticoid replacement therapy to that in women who have neither of these criteria. In doing so, the study will aim to determine the relationship between OPG and bone loss. Because of the excess of androgen caused by 21-OHD CAH, women with CAH may exhibit some male-like characteristics. Glucocorticoids are a member of a class of drugs called corticosteroids, which are used in hormone replacement therapy. In order to counteract the effects of 21-OHD CAH, women with the disease are given hormone replacement therapy with glucocorticoids beginning at infancy. Glucocorticoids are known to cause bone loss. Despite many years of treatment with glucocorticoids, however, young women with 21-OHD CAH seem to be protected against bone loss. Researchers believe that the increased androgen levels in these women lead to increased estrogen levels, which in turn increase OPG production. The increase in OPG levels may protect women against bone loss. This study will evaluate bone density and OPG levels in women with and without 21-OHD CAH to determine the relationship between OPG and bone loss. Participants in this observational study will attend only one study visit. At this visit, they will undergo a blood draw; a scan of their lower spine, hip, and forearm; height and weight measurements; and a body fat analysis test. This last test will entail a weak and painless electrical signal being sent from foot to foot. Participants will not attend any follow-up visits for this study.

  Study phs001314

• Heart and Vascular Health Study (HVH)

  Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Background The HVH originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants, which have added case subjects with stroke, VT, and AF, and used a common control group. Study aims have focused on the associations of medication use with cardiovascular events. Starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later and who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotype data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples.

  Study phs001013

• Sequencing of pancreatic cancer primary tumors and metastases

  The extent of heterogeneity of driver gene mutations present in naturally occurring metastases is largely unknown, i.e. treatment-naïve metastatic disease. To address this issue, 60x whole genome sequencing of 26 metastases from 4 patients was carried out. We found that the identical driver gene mutations were present in every metastatic lesion of each patient studied. Passenger gene mutations not known or predicted to have functional consequences accounted for all intratumoral heterogeneity. Even with respect to these passenger gene mutations, the genetic similarity among the founding cells of metastases was markedly higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of driver gene mutations among metastases in the same patient has critical, encouraging implications for the success of future targeted therapies in advanced stage disease.

  Study EGAS00001002186

• Count Me In (CMI): The Metastatic Breast Cancer (MBC) Project (CMI-MBCproject)

  Count Me In - The Metastatic Breast Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Breast Cancer Research The Metastatic Breast Cancer Project is a research study that directly engages patients with metastatic breast cancer via social media and advocacy groups and empowers them to accelerate cancer research by sharing their samples and clinical information. Our goal is to create a publicly available dataset of genomic, molecular, clinical, and patient-reported data to enable research. Patients in the US or Canada may register online. Registered patients are sent an online consent form that asks for permission to obtain and analyze their medical records, tumor tissue, saliva, and blood samples. Once enrolled, patients are sent a saliva kit and asked to mail back a saliva sample, which is used to extract germline DNA. Study staff contact participants' medical providers and obtain medical records and a portion of their stored tumor biopsies. Patients may be asked to mail in a blood sample, which is used to extract cell free DNA (cfDNA). Whole exome sequencing (WES) is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. Clinically annotated genomic data are used to study specific patient cohorts (including outliers) and to identify mechanisms of response and resistance to therapies. All de-identified data, including genomic, clinical, and patient-reported data, are shared via public databases on a pre-publication and recurring basis as it is generated. The latest data release in cBioPortal is available here. Study updates are shared with participants regularly.

  Study phs001709

• Test Study for EGA using data from 1000 Genomes Project - Phase 3

  The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies...

  Study EGAS00001005042

• eMERGE Geisinger eGenomic Medicine (GeM) - MyCode Project Controls

  A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patient agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. For the initial eMERGE Geisinger eGenomic Medicine (GeM) genotyping project, a subset of 1,232 unique samples were genotyped using Illumina HumanOmniExpress-12 v1.0 arrays, and used as population controls for other Geisinger Clinic case cohorts, including abdominal aortic aneurysm and gastric bypass surgery cases. These samples were selected from a larger subset of approximately 6,000 MyCode DNA samples using a partial matching algorithm that included age, sex, and body mass index as variables.

  Study phs000381

• HERBY trial WES

  Whole exome sequencing of non-brainstem paediatric high grade glioma from the HERBY phase II randomised trial. DNA from 86 cases was subjected to Illumina paired end whole exome sequencing using a customised SureSelect Human All Exon V6 capture set. Germline DNA from whole blood was sequenced for 83 cases. 26 cases were sequenced from both fresh frozen tissue and FFPE material, 10 were sequenced from only fresh frozen material and 50 from only FFPE. Data is provided as bwa aligned BAM files

  Dataset EGAD00001004036

• WES dataset of a TIL-ACT metastatic melanoma cohort

  Whole-exome sequencing (WES) data from 13 patients with metastatic melanoma in a TIL-ACT cohort, generated to characterize tumor genomics and neoantigen landscapes relevant to adoptive T cell therapy.

  Dataset EGAD50000001731

• alopecia areata

  exome sequencing files from 25 alopecia areata samples from spain.

  Dataset EGAD00001006370

• RNA-Sequencing and Somatic Mutation Status of Adrenocortical Tumors: Novel Pathogenetic Insights

  To investigate the relationship between transcriptome profile and genetic background in a large series of adrenocortical tumors and to identify new potential pathogenetic mechanisms, we performed transcriptome profiling by high-throughput sequencing. We collected snap-frozen tissue from patients with adrenocortical tumors (n = 59) with known genetic background: 26 adenomas with Cushing syndrome, 17 adenomas with mild autonomous cortisol secretion, 9 endocrine-inactive adenomas, 7 adrenocortical carcinomas. Additionally, we sequenced 4 control samples.

  Study EGAS00001004533

• Breast Cancer Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of 26 primary breast cancers from Wu et al. (2021) study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001007495

• 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