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• How to request data

  Request Data Access If you're looking to access data from the EGA for your research, you are in the right documentation page! In this page you will find a step by step guide on how to request data archived at the EGA, as well as some frequently asked questions you might find useful. When requesting data, you'll need to provide information about your research project and intended use of the data. Keep in mind that your data access request may require additional approvals or agreements depending on the datasets and data providers involved. Step by step guide Register yourself as an EGA user. Validate your account. A validation link will be sent to your email to activate your EGA user account. Log into the EGA page. Search the dataset of interest from the dataset catalogue or search bar. Click on “Request access” Add a comment requesting these files and send your request Your request is successfully registered, and the DAC will receive a notification about your request In addition to submitting your request, you should also contact the DAC directly via e-mail. You can access the DAC's contact information from the relevant dataset page. Frequently Asked Questions (FAQ) Which is the role of the EGA in the data access process? The European Genome-phenome Archive (EGA) facilitates the secure distribution under controlled access of personally identifiable genetic and phenotypic data. Data Access Committee (DAC) is a body of one or more individuals who are responsible for data release to external requestors, based on participant consent and/or National Research Ethics terms. How do I request access to multiple datasets? To request access for multiple datasets managed by the same Data Access Committee (DAC), please start by visiting the DAC catalogue to locate the DAC of your choice. Once you've found the relevant DAC, proceed to its dedicated page where you'll find a "Request access" button. After logging in to the EGA website, you'll be presented with a comprehensive list of datasets under the chosen DAC. Select the datasets you're interested in, and then compose a message indicating your access request. Click the "Send" button to submit your request, which will include the chosen datasets. Please be sure to review the data usage policies for the requested datasets, as policies can vary among datasets managed by the same DAC. I am a co-applicant. Will I be given a joint access account? Each applicant needs to create an EGA account themselves, with unique login details. User log-in details are for individual use only and should never be shared, under any circumstances. EGA services are only provided to EGA account holders. Therefore, the co-applicant will send a formal request to the DAC. What happens if a co-applicant leaves or a new member needs to be added to an existing DAC application? The appropriate Data Access Committee (DAC) should be contacted and informed about the required changes so that the application can be updated. I have changed my place of work since my EGA account was created. Can I still have access to data? You must contact the relevant Data Access Committee (DAC). The DAC did not reply to my data access request. How should I proceed? There is no estimated time for DAC response. Please allow up to four weeks for a response. In the meantime, please send them a weekly reminder of the status of your request by emailing them directly.If the DAC becomes unresponsive, meaning that they fail to communicate with a requestor within the specified time frame, please contact the EGA Helpdesk team. I have an account with the EGA and would like access to further datasets. How should I proceed? You need to reapply to the relevant Data Access Committee (DAC). Once the DAC has approved your application your account will be updated and an email will be sent to notify you of a change made to your account. How do I download files of the datasets I have been granted access to? The preferred method for data download and decryption is the EGA Secure Download Client. Please carefully review the provided documentation. How do I download metadata? Metadata is retrieved from the EGA webpage; you will not need to use any download client. Be informed that you will only be able to download metadata of your approved datasets. For such download, you should first log in the EGA webpage with your credentials. Then browse the metadata's dataset you have gained access and you will find a metadata download button. You may also want to have a look our metadata schema. I have forgotten or misplaced my user account password; how do I get a new one? Click on “Log in”, located in the top right corner of the EGA homepage. Then click “Forgot password”, type in your registered institutional email address, and instructions for resetting your password will be sent to you. Please check both regular and junk/spam folders. I was sent a link to set a password for my download account, but it seems like the link has expired. What should I do? The procedure is the same as the one for a forgotten password, explained in the previous question.

  Documentation access/request-data/how-to-request-data

• Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - OncoArray Genotypes

  Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (http://epi.grants.cancer.gov/gameon/). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL). To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, the GAME-ON projects and other consortia formed the OncoArray network (http://epi.grants.cancer.gov/oncoarray/), which developed and genotyped a new custom genotyping array (the "OncoArray") in large numbers of cancer cases and controls (over 400,000 samples). The OncoArray is a custom array manufactured by Illumina. The array includes a backbone of approximately 260,000 SNPs that provide genome-wide coverage of most common variants, together with markers of interest for each of the five GAME-ON cancers identified through genome-wide association studies (GWAS), fine-mapping of known susceptibility regions, sequencing studies, and other approaches. The array also includes loci of interest identified through studies of other cancer types, and other loci of interest to multiple cancer types (including loci associated with cancer related phenotypes, drug metabolism and radiation response). Additionally, SNPs relating to quantitative phenotypes such as body mass index (BMI), height, and breast density that correlate with common cancer risks are also included. The DRIVE data included under this dbGAP submission include OncoArray data from 60,015 breast cancer cases and controls genotyped at the Center for Inherited Disease Research (CIDR), University of Cambridge, National Cancer Institute, University of Copenhagen, University of Southern California and Mayo Clinic. Details on an additional approx. 80,000 breast cancer cases and controls genotyped at other centers can be found at http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/.

  Study phs001265

• Assessing Neural Mechanisms of Injury in Inborn Errors of Urea Metabolism Using Structural MRI, Functional MRI, and Magnetic Resonance Spectroscopy

  Urea cycle disorders represent a group of rare inborn errors of metabolism that lead to accumulation of ammonia, a toxic product of protein metabolism. Individuals with urea cycle disorders cannot metabolize the ammonia that accumulates due to enzyme deficiency. The symptoms of these disorders may present at birth, childhood or adulthood (milder deficiencies). There are currently eight enzyme deficiencies that constitute the range of inborn errors of ureagenesis. This project will focus on the most common enzyme disorder of the urea cycle, ornithine transcarbamylase deficiency, inherited as an X-linked trait. This project will study cognitive and motor dysfunction in patients who are female carriers of ornithine transcarbamylase deficiency (OTCD) or are males with late onset presentation of OTCD, utilizing state of the art MRI (magnetic resonance imaging), a non -invasive technique. This project seeks to improve our understanding of the underlying neural mechanisms that contribute to metabolic, cognitive, sensory and motor abnormalities in urea cycle disorders, which although individually rare, collectively constitute a major cause of neonatal encephalopathy, leading to significant morbidity and mortality. As a result of this study, a greater understanding of the anatomic, cognitive, motor, and biochemical underpinnings of neurologic damage attributable to this metabolic disorder will be gained. Experimental approaches will combine sensory, cognitive and motor testing with structural, functional and molecular magnetic resonance imaging to study symptomatic and asymptomatic heterozygous female carriers of X-linked ornithine transcarbamylase deficiency (OTCD), and late onset hemizygous males. Participants to be included in the studies will range from ages 18-60 years and will be compared to an age-matched typically developed (TD) comparison group. For our research, we use anatomic MRI, functional Magnetic Resonance Imaging (fMRI), and magnetic resonance spectroscopy (MRS) to monitor brain activity. The technique of fMRI provides detailed maps of the brain areas underlying human mental activities. By using fMRI, we are able to observe how the brain is functioning while a person is performing a specific task, such as reading. We can not only observe differences in the structure of the brain, but can also measure differences in brain function and activity as well. This information will ultimately be used to provide a basis for designing more effective interventions and methods for early identification of learning disabilities in patients with OTCD and related disorders. We will also use MRS to study various brain chemicals such as glutamine using the non-invasive MRI imaging techniques.

  Study phs001108

• Single cell genomic variation induced by mutational processes in cancer

  How cell-to-cell copy number alterations that underpin genomic instability in human cancers drive genomic and phenotypic variation, and consequently cancer evolution, remains understudied. Here, applying scaled single cell whole genome sequencing to wildtype, TP53-deficient and TP53/BRCA1/2-deficient mammary epithelial cells (n=13,818 genomes) and primary triple negative breast (TNBC) and high grade serous ovarian cancers (HGSC) (n=22,057 genomes), we identified three distinct ‘foreground’ mutational patterns defined by cell-to-cell copy number and structural variation properties occurring in the ‘background’ of cancer-associated genomic instability. Cell and clone-specific high level amplifications (HLAMPs), parallel allele-specific copy number alterations and copy number segment length variation (serrate structural variations) exhibited measurable phenotypic and evolutionary consequences. Clone-specific HLAMPs in known oncogenes were highly prevalent in fold back inversion (FBI)-bearing tumors and associated with increased clone-to-clone phenotypic variation in gene expression inferred from matched single cell RNASeq. Parallel allele-specific alterations were linked with phylogenetically determined evolutionary diversity and clone-specific mono-allelic expression. Serrate patterns present across all clones were increased in FBI tumors, most prominently on a tetraploid background and were highly correlated with increased genomic diversity of cellular populations. Taken together, we show that cell-to-cell structural-copy number variation significantly impacts the phenotypes and evolutionary diversity of TNBC and HGSC, revealing previously hidden genomic states of cancer cells.

  Study EGAS00001006343

• San Francisco Bay Area Latina Breast Cancer Study

  The genome-wide association study (GWAS) includes participants enrolled into two different studies. The first study, the San Francisco Bay Area Cancer Study (SFBCS) is a population-based case-control study of breast cancer conducted in the San Francisco Bay Area and included women ages 35-79 years from three racial/ethnic groups: Non-Hispanic whites, African Americans, and Hispanics/Latinas. For the GWAS, only Hispanic/Latina women were included. Women diagnosed with invasive breast cancer between 1995 and 2002 were identified through the Greater Bay Area Cancer Registry. Controls were identified by random digit dialing and were frequency-matched to cases by age in 5 year increments and by race/ethnicity. Hispanic/Latina ethnicity was assessed by self-report. 175 Hispanic/Latina cases and 307 Hispanic/Latina controls from the SFBCS had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission. The second study is the Northern California site of the Breast Cancer Family Registry (NC-BCFR). This population-based family study recruited breast cancer cases ages 18-64 years diagnosed from 1995-2009 that were identified through the Greater Bay Area Cancer Registry. Cases included all women at increased genetic susceptibility for breast cancer who met one or more of the following criteria: (a) being diagnosed with breast cancer at age <35 years; b) having a personal history of ovarian cancer or childhood cancer; (c) being diagnosed with two different breast cancers (bilateral breast cancers), with the first one diagnosed at age <50 years; and d) having one or more first-degree relatives with breast cancer, ovarian cancer or childhood cancer. Cases not meeting these criteria were randomly sampled and racial/ethnic minorities were oversampled. Controls were recruited by random digit dialing and were matched by 5-year age increments and by race/ethnicity. For the current GWAS only Latina/Hispanic cases and controls were included. Latina/Hispanic ethnicity was assessed by self-report. 631 Hispanic/Latina cases and 61 Hispanic/Latina controls from the NC-BCFR had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission.

  Study phs000912

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (ARIC)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000398 contains the Atherosclerosis Risk in Communities (ARIC) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000398

• Center for Common Disease Genomics [CCDG] - Cardiovascular: Genetic and Phenotypic Determinants of Blood Pressure and Other Cardiovascular Risk Factors

  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.edu The GAPP study is an ongoing national population-based prospective cohort study conducted in the Principality of Liechtenstein. Between 2010 and 2014, all inhabitants of Liechtenstein aged 25-41 years old were asked to participate in the study, and 2170 could be enrolled. The aim of the study is to identify the determinants of blood pressure and other cardiovascular risk factors and their progression over time. A large number of baseline characteristics and health information as well as several blood, urinary and genetic markers were collected. The samples were sent to The Broad Institute of MIT and Harvard to generate genetic data using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all samples serving as controls.

  Study phs002236

• Genomic Characterization of Head and Neck Squamous Cell Carcinoma Cell Lines

  Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer by incidence worldwide(1). Various chemical carcinogens (tobacco, alcohol and betel nut), human papillomavirus (HPV) infection, and genetic predisposition contribute to the etiology of HNSCC, and to the complex genetic alterations in tumor subsets that differ in prognosis and response to therapies (2). Recently, a comprehensive landscape of genomic and transcriptomic alterations in HNSCC tumors has emerged from The Cancer Genome Atlas (TCGA) Network (3). TCGA revealed novel and previously recognized gene and chromosomal region copy number alterations (CNAs), mutations, and expression clusters, and defined their frequency, co-occurrence, and relationship to common and rare subtypes of HPV(-) and (+) tumors that vary in prognosis. To identify cell line models for determining the functional role and therapeutic importance of these alterations, we are performing whole exome and RNA sequencing and bioinformatic analysis of an expanded panel of 15 HPV(-) and 11 HPV(+) HNSCC cell lines and primary oral keratinocytes. We find that the recurrent genomic alterations in cell lines are remarkably consistent with those found in more aggressive tumors, from which cell lines have traditionally been most readily adapted to culture (4). Genome-wide correlation of CN (copy number) with expression identified a suite of potential drivers or modifier genes that differ by HPV status, and are of potential biologic and therapeutic relevance. Further, our findings elucidate and validate genomic alterations underpinning numerous discoveries made with these widely-used and recently derived HNSCC lines, and provide a roadmap for their potential use as models for future studies of tumor subtypes with worse prognosis. References Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87-108. Van Waes C, Musbahi O. Genomics and advances towards precision medicine for head and neck squamous cell carcinoma. Laryngoscope Investig Otolaryngol. 2017;2(5):310-9. Cancer Genome Atlas N. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature. 2015;517(7536):576-82. White JS, Weissfeld JL, Ragin CC, Rossie KM, Martin CL, Shuster M, et al. The influence of clinical and demographic risk factors on the establishment of head and neck squamous cell carcinoma cell lines. Oral Oncol. 2007;43(7):701-12.

  Study phs001581

• International Consortium to Identify Genes and Interactions Controlling Oral Clefts

  Oral clefts represent the most common group of craniofacial birth defects in humans, and include cleft lip with or without cleft palate (CL/P) and cleft palate (CP). Oral clefts have a complex and heterogeneous etiology, with strong evidence for both genetic and environmental causal factors. Candidate gene studies and genome wide linkage studies have yielded compelling but inconsistent evidence that multiple genes control risk, and several studies have shown evidence for interaction between genes and environmental exposures, especially maternal smoking and nutrient intake. This consortium pulls together a very large collection of cases and their parents from multiple populations, and offers a unique opportunity to expand the search for genes controlling risk to the genome wide level. The specific aims are: To conduct a genome wide analysis on 2000+ case-parent trios ascertained through a case with isolated, non-syndromic CL/P or CP to test for linkage and disequilibrium. Initial analysis will consist of individual tests for gene effects while simultaneously testing for GxE interaction with common maternal exposures including vitamin supplementation, cigarette smoking and alcohol consumption (which have all been implicated as environmental risk factors for oral clefts). To use haplotypes in tests for GxE interaction incorporating population specific estimates. Since haplotype frequencies vary among populations, trios will be assigned haplotypes in a stratified estimation and then a pooled test statistic will be constructed. To test for interaction between SNPs in different genes showing evidence of influencing risk in a test for GxG interaction. To test for interaction between genes and maternal biomarkers using trios from Utah where measures of plasma folate, vitamin B-6, homocysteine and zinc in mothers are available. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to oral clefts through large-scale genome-wide association studies of well-characterized cases and their parents from multiple populations. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). The study was supported by the National Institute of Dental and Craniofacial Research (NIDCR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000094

• Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute

  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 will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis 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 hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000179 COPDGene_v6 Cohort. phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno

  Study phs000179

• University of Michigan Clinical Sequencing Exploratory Research (CSER)

  Overview. The personalization of therapy for cancer will require molecular characterization of unique and shared genetic aberrations. In particular, patients who have a sarcoma or other rare cancers and are candidates for clinical trials could potentially benefit by identifying eligibility for "targeted" drugs based on the "actionable" genes in their specific tumor. Growing technological advances in genomic sequencing has now made it possible to consider the use of sequence data in a clinical setting. For instance, comprehensive testing that includes whole exome and transcriptome sequencing may identify biomarkers for predictive or prognostic purposes and thereby inform treatment choices and prevention strategies. Thus, the translation of high throughput next generation sequencing would support a "personalized" strategy for cancer. However, the translation of clinical sequencing bears unique challenges including identifying patients who could benefit, developing informed consent and human subjects protections, outlining measurable outcomes, interpreting what results should be reported and validated, and how results should be reported. In addition, we know very little about how patients and clinicians will respond to the potentially confusing and overwhelming amount of information generated by genomic sequencing, and we lack model processes for clinically evaluating and presenting these data. For the promise of our innovative biotechnologies to be realized, "translational genomics" research that evaluates genomic applications within real-world clinical settings will be required. This proposal brings together expertise at the University of Michigan including clinical oncology, cancer genetics, genomic science/bioinformatics, clinical pathology, social and behavioral sciences, and bioethics in order to implement this clinical cancer sequencing project. Three integrated Projects have the following themes: Project 1) "Clinical Genomic Study" will identify patients with a rare cancer (i.e., 15 out of 100,000 individuals per year) who are eligible for clinical trials, consent them to the study, obtain biospecimens (tumor tissue, germline tissue), store clinical data, and assemble a multi-disciplinary Sequencing Tumor Board to deliberate on return of actionable or incidental genomic results; Project 2) "Sequencing & Analysis" will process biospecimens and perform comprehensive sequencing and analysis of tumors to identify point mutations, copy number changes, rearrangements/gene fusions, and aberrant gene expression; Project 3) "Ethics & Psychosocial Analysis" will observe the expert review process for evaluating sequence results and will examine the clinician and patient response to the informed consent process, delivery of genomic sequence results, and use of genomic results.

  Study phs000673

• Whole Blood Transcriptomics of Patients With Melioidosis

  Melioidosis is a neglected tropical infection caused by the Gram negative bacterium Burkholderia pseudomallei that is associated with high mortality rates in southeast Asia. The goal of this study was to a) identify human blood leukocyte transcriptomic features and pathways specific to melioidosis (vs other etiologies of infection), b) identify transcriptomic features and pathways specific to fatal melioidosis, and c) identify transcriptomic predictors of death in patients with melioidosis. This study used clinical data and whole blood leukocyte samples from a subset of participants in the Ubon Sepsis Study, a prospective single-center cohort study conducted at Sunpasitthiprasong Hospital, Ubon Ratchathani, Thailand between 2013 and 2017. Participants in the Ubon Sepsis Study had suspected or documented infection with accompanying systemic manifestations of infection and were enrolled, with blood sampling, within 24 hours of admission to the study hospital. Enrolled patients were followed over time and vital status was determined at 28 days after enrollment. The subset of participants from the parent Ubon Sepsis Study cohort selected for this study was comprised of 164 patients with melioidosis (defined as having a culture of clinical sample positive for B. pseudomallei), 35 patients with Gram negative bacteremia due to either Escherichia coli or Klebsiella pneumoniae, 16 patients with Gram positive bacteremia due to Staphylococcus aureus, and 19 patients who had negative blood cultures and no clinical sample culture-positive for B. pseudomallei. Fifty uninfected control patients with or without diabetes were recruited from the outpatient department and blood donation center at Udon Thani hospital, Udon Thani, Thailand from 2018 to 2019. Blood was collected at the time of enrollment in Tempus Blood RNA tubes. RNA was extracted using the Tempus Spin RNA Isolation kit. RNA sequencing (RNA-Seq) was performed at the University of Washington Northwest Genomics Center. Analysis was performed using a variety of statistical methods. The main finding of the study was that the transcriptomes of melioidosis patients, compared to patients with other infections, were characterized by upregulation of interferon signaling. The transcriptomes of patients with fatal melioidosis were notable for upregulation of inflammatory and type 2 immune responses and downregulation of genes related to T-cell function. A five-gene (EPHB1, SYCP2L, MERTK, IL5RA, and SPOCK1) predictive signature for death in melioidosis was developed.

  Study phs003724

• RNA_Seq_in_Patients_with_Primordial_Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in theinterpretation of likely causal genetic variation through identification of altered transcriptabundance and/or structure. RNA-Seq is the most sensitive assay for both investigatingtranscript structure and abundanceThe primary aim of this pilot project is to investigate to what degree integrating exome-Seqand RNA-Seq data on the same individual can accelerate the identification of causal allelesfor rare genetic diseases. There are two main strands to this: (i) identifying which variantsdiscovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarilyhave a causal variant identified from exome sequencing. The latter may identify the presenceof causal variants that lie far from coding regions (e.g. the formation of cryptic splice sitesdeep within introns, or loss of long range regulatory elements), which can be confirmed withfurther targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients withprimordial dwarfism syndromes, for 10 of these samples we have previously generate exomedata as part of our collaboration with the group of Prof Andrew Jackson. The two remainingsamples are positive controls where the causal mutation is known, and is known to affecttranscript structure and/or abundance.Primordial dwarfism is a prime candidate for these RNA-seq studies because all knowncausal mutations to date have key roles in DNA replication and thus, unsurprisingly, theproducts of the causal genes are typically ubiquitously expressed.Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) persample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000283

• Plasma MicroRNA Signatures of Aging

  Background. MicroRNAs are small non-coding RNAs that regulate gene expression post-transcriptionally and show differential expression in various tissues with aging phenotypes. Detectable in circulation, extracellular microRNAs reflect (patho)physiological processes and hold promise as biomarkers for healthy aging and age-related diseases. This study aimed to explore plasma extracellular microRNAs as biological aging indicator and their associations with health outcomes using population-level data. Methods. We quantified plasma expression levels of 2,083 extracellular microRNAs using targeted RNA-sequencing in 2,684 participants from the population-based Rotterdam Study cohort. The training and test sets included 1,930 participants from the advanced-aged initial and second subcohort (RS-I/RS-II; median age: 70.6), while the validation set comprised 754 participants from the middle-aged fourth subcohort (RS-IV; median age: 53.5). Based on 591 microRNAs well-expressed in plasma, we examined differential expression of microRNAs with chronological age, PhenoAge –a composite score of age and nine multi-system blood biomarkers–, the frailty index, and mortality. Next, elastic net models were employed to construct composite microRNA-based aging biomarkers predicting chronological age (mirAge), PhenoAge (mirPA), frailty index (mirFI), and mortality (mirMort). The association of these aging biomarkers with different age-related health outcomes was assessed using Cox Proportional Hazard, linear regression, and logistic regression models in the test and validation sets. Results. We identified 188 microRNAs differentially expressed with chronological age within the RS-I/RS-II advanced-aged population (ntraining=1158, ntest=772), of which 177 microRNAs (94.1%) were replicated in the middle-aged RS-IV subcohort (nvalidation=754). Moreover, 227 miRNAs showed robust associations with PhenoAge, 61 with FI, and 16 with ten-year mortality independent of chronological age. Subsequently, we constructed four plasma microRNA-based aging biomarkers: mirAge with 108, mirPA with 153, mirFI with 81, and mirMort with 50 miRNAs. Elevated scores on these microRNA-based aging biomarkers were associated with unfavorable health outcomes, including lower subjective physical functioning and self-reported health and increased mortality and frailty risk, but not with first- or multi-morbidity. Overall, larger effect estimates were observed for mirPA, mirFI, and mirMort compared to mirAge. Conclusions. This study describes distinct plasma microRNA-aging signatures and introduces four microRNA-based aging biomarkers with potential to identify accelerated aging and age-related decline, providing insights into the intricate process of human aging.

  Study EGAS00001008117

• AML_controls

  Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare hematologic malignancy that is most similar in expression profiles to plasmacytoid dendritic cells. However, patients often exhibit features of AML and can progress to AML. In this project, we will determine the differentially and commonly expressed genes between BPDCN and AML specimens. Available BPDCN and TET2-mutated AML specimens were taken for transcriptome microarray analysis.

  Dataset EGAD00010001726

• A Collaborative Search for New Genes for Non-Syndromic Deafness

  We seek to identify the DNA variants underlying sensorineural hearing loss. We obtain the DNA sequence of affected individuals and their family members. DNA variants are filtered to determine their segregation in affected families.

  Study phs003701

• Metagenomic characterization of tracheal aspirates from non-pulmonary sepsis patients

  Metagenomic characterization of tracheal aspirates from non-pulmonary sepsis patients. This dataset consists of non-human read data from shotgun sequencing in sepsis case samples from lung aspirates. The dataset consist of 32 paired FASTQ files sequenced in paired-read mode 2x150 bp using an Illumina HiSeq 4000 sequencer.

  Dataset EGAD50000000561

• WES of precancerous lesions from 10 lynch patients and 3 sporadics

  Raw sequencing data of WES that were obtained from precancerous samples as adenoma and MMR-deficient crypts and paired healthy tissue from MSI CRC patients of which 10 are diagnosed with lynch syndrome and 3 had sporadic cancer. These data were analyzed in order to evaluate microsatellite instability though tumorigenesis and associated to splicing deregulation in MSI tumors RNA.

  Dataset EGAD50000000644

• A first step towards clinical routine long-read sequencing in Sweden, a national pilot study on chromosomal rearrangements

  PacBio HiFi Revio WGS data from 16 individuals sequenced in the Genomic Medicine Sweden (GMS) Long read project. Each individual was sequenced on one PacBio Revio SMRT cell. The DNA was extracted from blood. The HiFi data was aligned to GRCh38 using minimap2 or the SMRT-link software.

  Dataset EGAD50000000676

• Single-cell RNA-seq of PBMC from 2 patients iGRAN-Low and 2 patients iGRAN-High

  Single-cell RNA-seq of PBMC from 2 patients iGRAN-Low and 2 patients iGRAN-High [Publication title] CXCL8 secreted by immature granulocytes inhibits wildtype hematopoiesis in chronic myelomonocytic leukemia

  Study EGAS50000000556

• Whole-genome sequencing with complement C1s deficiency linked to systemic lupus erythematosus

  This dataset includes two FASTQ files (R1 and R2) from an Illumina germline nuclear DNA whole-genome sequencing run of a single sample. The sample corresponds to a 34-year-old male with a rare deficiency in complement component C1s, linked to systemic lupus erythematosus (SLE). Genomic analysis revealed two novel mutations in the C1S gene.

  Dataset EGAD50000000988

• Bulk-RNAseq from human nerve fascicles and Schwann cells

  Bulk-RNAsequencing from human nerve fascicles from patients with polyneuropathies, and human Schwann cell cultures isolated from said nerve fascicles, in comparison to control human Schwann cell cultures and a referential fibroblast culture.

  Study EGAS50000000737

• McQuillin_Global_WES_Schizophrenia

  This research project was a collaboration between University College London, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 1,623 Schizophrenia, Bipolar and Control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing CRAM files.

  Dataset EGAD50000001316

• Targeted sequencing data of cfDNA, archival tissue, and WBC from 226 patients with mUC

  Targeted tissue (n=210), cfDNA (n=402), and WBC (n=245) Illumina sequencing of metastatic urothelial carcinoma patients. All cfDNA is collected in the metastatic setting, while archival tissue is from across the disease course. White blood cell (WBC) samples are used as patient matched germline samples. All files are in paired-end fastq format.

  Dataset EGAD50000001571

• Characterizing Immune Profiles in Extrapulmonary Tuberculosis via RNA Sequencing

  This dataset provides insight into the immune response in extrapulmonary tuberculosis (EPTB), using bulk RNA-seq data to analyze different disease severities. Hierarchical clustering identified three distinct levels of severity, revealing disease progression driven by interferon and IL-1β-mediated signaling. Additionally, the dataset helped develop a diagnostic gene expression signature for both EPTB and pulmonary TB.

  Dataset EGAD50000000943

• Comprehensive analysis of interaction between human gene expression and environmental metagenomes.

  WGS, 10x scRNA, 10X TCR, 10X BCR and CyTOF analyses were performed using blood samples collected from healthy volunteers aged 18 years or older who worked or lived in the Kashiwa-no-ha area.

  Study JGAS000321

• Genomic and transcriptomic analysis on hepatocarcinogenesis after HCV eradication

  Little is known about the genomic and transcriptomic features of hepatocellular carcinoma developing after HCV eradication (SVR-HCC). In this study, we aimed to unveil the genomic and transcriptomic basis of hepatocarcinogenesis after SVR.

  Study JGAS000234

• 419 Japanese healthy control

  Genotypes of 419 Japanese healthy individuals genotyped by using of SNP arrays (Genome-Wide Human SNP Array 6.0 and Axiom Genome-Wide ASI 1 Array). CEL files and CHP files are included in this data set.

  Study JGAS000120

• Targeted sequencing data of cfDNA, archival tissue, and WBC from 208 patients with mUC

  Targeted tissue (n=81), cfDNA (n=319), and WBC (n=208) Illumina sequencing of metastatic urothelial carcinoma patients. All cfDNA is collected in the metastatic setting, while archival tissue is from across the disease course. White blood cell (WBC) samples are used as patient matched germline samples. All files are in paired-end fastq format.

  Dataset EGAD50000002089

• A_study_of_the_molecular_pathogenesis_of_Splenic_Marginal_Zone_and_Diffuse_Large_B_Cell_Lymphoma

  We will perform exome sequencing on selected cases of splenic marginal zone lymphoma (SMZL) and diffuse large B-cell lymphoma (DLBCL) in order to characterise their genetic makeup and identify biomarkers for prognosis and prediction of treatment response.

  Study EGAS00001000335

• Triple_Negative_Breast_Cancer_Whole_Genomes

  We propose to definitively characterise the somatic genetics of Triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000092

• Transcriptome_Sequencing_of_Cancer_Cell_Lines

  In this study we will sequence the transcriptome of Verified Cancer Cell lines. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found.

  Study EGAS00001000261

• Whole-exome analysis of corticotropin-independent Cushing's syndrome

  We performed WES for 8 cases with corticotropin-independent Cushing’s syndrome, in whom paired tumor and normal DNA was obtained from fresh frozen adenomas and either normal adrenal tissues or peripheral blood, respectively.

  Study EGAS00001000661

• RNA seq of MPNST tumour samples

  RNA sequencing of 10 MPNST tumour samples as part of a larger study of MPNST. Article: Lyskjær et al, 2020, J Pathol, "H3K27me3 expression and methylation status in histological variants of malignant peripheral nerve sheath tumours".

  Study EGAS00001004528

• Genomic and Transcriptomic Profile of Paired Primary-Metastasis Colorectal Tumors

  The goal of this study is to identify mechanisms of metastization in a portuguese cohort of colorectal cancer. Namely, we want to identify patterns of genomic and transcriptomic diversification associated with metastasis.

  Study EGAS00001005276

• Tumor HTG EdgeSeq from metastatic castrate resistant prostate cancer

  This dataset contains tumor bulk HTG EdgeSeq from patients with metastatic castrate resistant prostate cancer. RNA libraries were prepared following manufacturer's user guide (HTG Molecular Diagnostics). Each library was sequenced in HTG EdgeSeq system.

  Study EGAS00001004852

• RNA sequencing of high hyperdiploid and ETV6/RUNX1-positive pediatric acute lymphoblastic leukemia

  We performed RNA-sequencing of high hyperdiploid and ETV6/RUNX1-positive ALL cases by using the Human Ribo-Zero rRNA Removal Kit to investigate the gene expression in high hyperdiploid ALL.

  Study EGAS00001003079

• Dedifferentiated_Melanoma_RNAseq

  De- and transdifferentiation of melanoma is a rare histopathological phenomenon that has not be characterised genetically. In this project we plan to sequence the genomes of de and transdifferentiated cases so as to define their genetic make-up.

  Study EGAS00001003601

• Targeted DNA sequencing on 37 Merkel Cell Carcinomas from New Zealand with known Merkel cell polyomavirus status

  To determine the genomic landscape of NZ virus-negative MCCs (VN-MCC), assess genomic evolution in metastases, and catalogue the distribution of TP53 and RB1 variants from international studies.

  Study EGAS00001006873

• RNA-Seq data from 34 CAF-S3 subset in human breast and ovarian cancers

  This dataset is related to publications Costa et al. Cancer Cell 2018 and Givel et al. Nat. Commun. 2018 which describe the identification of 4 Cancer Associated Fibroblasts (CAF) in breast and ovarian cancer. This dataset contains transcriptomic profiles obtained by RNA-Seq of 34 CAF-S3 samples from breast and ovarian Tumors.

  Dataset EGAD00001004810

• Pre-post neoadjuvant chemotherapy breast cancer dataset- RNAseq data

  This dataset contains RNAseq data of 20 paired pre-post neoadjuvant chemotherapy breast cancer samples. In total the set contains n=20 biopsies, n=20 surgery specimens. Each sample has 2 fastq files, so n=80 fastq files are uploaded in total.

  Dataset EGAD00001008421

• Whole-transcriptome characterization of cell-free RNA (cfRNA) in cancer and non-cancer patients

  Whole-transcriptome characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Dataset includes collapsed BAM files for plasma cfRNA from each patient, as well as collapsed BAM files for RNA from matched tumor tissue (when available).

  Dataset EGAD00001006484

• Single cell transcriptomics of adult human adrenal gland

  Single cell transcriptomics (10x 3') of human adrenal gland. The adrenal gland of this particular individual is characterized by the presence of mutant clone characterized by aneuploidy in chromosomes 8, 9, 13 and 22, occupying the zona glomerulosa and zona fasciculata. This dataset contains the primary sequencing data generated from the 10x genomics 3' library in fastq format.

  Dataset EGAD00001011288

• High-coverage whole genome sequencing of human populations from the Pacific

  This dataset includes high-coverage genomes (~36x) of 317 individuals from 20 populations of the Pacific (Taiwan, Philippines, Solomon Islands, Vanuatu archipelago), described in “Genomic insights into population history and biological adaptation in Oceania”, by Choin, Mendoza-Revilla, Arauna, and colleagues (Nature 2021). The data is made of 331 fastq files.

  Dataset EGAD00001006880

• CGH Array

  DNA samples were extracted from peripheral blood lymphocytes using commercially available kit (Puregene Core Kit A, Qiagen) according to manufacturer's protocol. Agilent SurePrint G3 Human CGH Microarray 180K platform was used for screening of copy number aberrations (CNAs) using array-CGH protocol recommended by manufacturer (Agilent Technologies), data mining and interpretation of array-CGH results was performed in same manner as in our previously published results.

  Dataset EGAD00001007743

• Stitched BAM files for manuscript titled Discrepancies in Tumour Mutation Burden (TMB) reporting from sequential Endobronchial ultrasound trans bronchial needle aspiration (EBUS TBNA) samples within single lymph node stations for SNP and INDEL Variant Calling.

  Stitched BAM files for manuscript titled Discrepancies in Tumour Mutation Burden (TMB) reporting from sequential Endobronchial ultrasound trans bronchial needle aspiration (EBUS TBNA) samples within single lymph node stations for SNP and INDEL Variant Calling.

  Dataset EGAD00001012639

• 10x genomics RNAseq of an isogenic human iPSC model of SMA

  10x genomics single-cell RNAseq of an isogenic human iPSC model for SMA and control. The transcriptomic analysis was performed at 3 timepoints, day 4, day 20 and day 40. The analysis of this dataset was reported in the manuscript "An isogenic human iPSC model unravels neurodevelopmental abnormalities in SMA" from Grass et al.:

  Dataset EGAD00001011259

• Whole genome sequencing of adult glioblastoma nuclei

  Three primary adult glioblastoma specimens were dissociated and nuclei were extracted. A portion of the nuclei was used for single-cell ATAC seq and the remainder were submitted for whole genome sequencing, to provide orthogonal validation of copy number variations in the samples compared to single-cell ATAC seq. Samples were sequenced on the Illumina NovaSeq 6000 in paired-end mode.

  Dataset EGAD00001007651

• Glioblastoma CRISPR Screen (2016-06-02)

  This is an in vitro genome-wide CRISPR/cas9 screen in human glioblastoma stem cells, screening for genes essential for survival of these cells. These cells express cas9 and have been transfected with a guide RNA library causing gene knockouts. We will analyse the sequencing data for depletion of guide RNAs. This dataset contains all the data available for this study on 2016-06-02.

  Dataset EGAD00001002158

• CNV detection in targeted NGS panel data

  We present targeted NGS panel data from 170 samples that were processed using the TruSightTM Cancer (TSC) panel (Illumina, San Diego, CA, USA), which targets 94 genes and 284 SNPs associated with a predisposition towards cancer. The samples are enriched for CNVs in the genes of interest. All CNVs have previously been assessed with MLPA and can therefore be considered as confirmed.

  Dataset EGAD00001003400