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• mRNA and T cell receptor sequencing of patients with Pandemrix-associated narcolepsy type 1

  PBMCs isolated from 27 individuals (11 narcolepsy type 1 patients, 16 healthy controls) were stimulated with the peptide Neuroaminidase 175-189 or Protein-O-mannosyl transferase 1 (POMT1) 675-689 or media as control. FACS sorted CD4+ and CD8+ lymphocytes from one patient were subjected to the same stimulation. Transcriptome profiling was done with a 3' tagging protocol. T cell receptor repertoires were profiled with amplicon sequencing (Rep-seq). The dataset contains FASTQ files with sequencing reads, transcript count matrices and TCR clonotypes.

  Dataset EGAD00001006797

• mRNA and T cell receptor sequencing of patients with Pandemrix-associated narcolepsy type 1

  PBMCs isolated from 27 individuals (11 narcolepsy type 1 patients, 16 healthy controls) were stimulated with the peptide Neuroaminidase 175-189 or Protein-O-mannosyl transferase 1 (POMT1) 675-689 or media as control. FACS sorted CD4+ and CD8+ lymphocytes from one patient were subjected to the same stimulation. Transcriptome profiling was done with a 3' tagging protocol. T cell receptor repertoires were profiled with amplicon sequencing (Rep-seq). The dataset contains FASTQ files with sequencing reads, transcript count matrices and TCR clonotypes.

  Dataset EGAD00001006796

• BRCA2, ATM, and CDK12 defects differentially shape prostate tumor driver genomics and clinical aggression

  This dataset contains all available targeted exon sequencing bam files from our study, "BRCA2, ATM, and CDK12 defects differentially shape prostate tumor driver genomics and clinical aggression". Patient identifiers are denoted by the first segment of the sample aliases (e.g. "P1"), and additional information is appended to reflect which sample is referenced. These include serial cfDNA samples ("-1", "-2", "-3", etc.), paired white blood cell or benign tissue control samples ("-Control"), or primary archival tissue samples derived from a diagnostic biopsy, prostatectomy, or transurethral resection of the prostate ("-Tissue"). All samples were sequenced using Illumina technology.

  Dataset EGAD00001006733

• VCF file from 16 patients affected by acute intermittent porphyria

  VCF file from 16 patients affected by acute intermittent porphyria. Whole genome sequencing of these samples was performed in an Illumina HiSeq 4000 instrument. Libraries were prepared using the Fisher PE Kit (Kapa Biosystems). BAM files were processed at the CNAG (Barcelona) with their pipeline, including GATK v3.6 for genotyping and other tools such as snpEff for annotating variants, to produce this VCF file with a total of 10,630,259 variants, out of which 8,731,523 are SNVs.

  Dataset EGAD00001006952

• scRNA-seq dataset of patient and healthy donors

  scRNA-seq dataset on a patient (P) presenting with defects of immunity and four healthy donors (C1, C2, C3, C4). This dataset contains raw and processed files from scRNA-seq performed on samples using the 10x Genomics Chromium Controller with the Chromium Single Cell 3′ Reagent Kit (v3 chemistry). There are 15 paired-end fastq files (3 per patient/donor - I1, R1, R2) and 15 processed files generated with 10x Genomics Cell Ranger v3.0.2 software against GRCh38 human reference transcriptome (3 per patient/donor - barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz).

  Dataset EGAD00001008372

• Cell-free DNA and bone marrow samples from myelodysplastic syndromes

  We have assessed the molecular profile of a cohort of 70 patients with MDS by next-generation sequencing (NGS) using cfDNA and compared the results to paired bone marrow (BM) DNA.

  Dataset EGAD00001008567

• Genetic regulation of RNA splicing in human pancreatic islets

  Here we provide access to newly generated RNA-seq data for 101 human islet samples used to map genetic effects on gene expression and alternative splicing (eQTLs and sQTLs) in a total of 399 human islets. We also make publicly available genotyping array data for 128 human islets, including the fraction of 101 human islet samples with existing RNA-seq data.

  Dataset EGAD00001009102

• WGS of tissues from members of family with germline POLD1 L474P variant

  The study includes WGS data for DNA extracted from blood, fibroblasts or buccal swabs from sixteen family members, who represent four sub-families, each including two parents and one to three children, comprising a total of eight offspring. In two sub-families POLD1 L474P was carried by the father; in one sub-family, by the mother; and in the other sub-family, both parents had wild-type POLD1.

  Dataset EGAD00001009282

• Test dataset with ligh-weight files

  This is a test dataset derived from public data of the 1000 Genomes Project. Its purpose is not to allow for any inference about cohort data or results, but to aid bioinformaticians in the technical development and testing of tools, as well as data consumers in learning how to access information. This dataset consists of 3 pairs of light-weight (sliced) files: BAM + BAI, CRAM + CRAI and VCF + TBI. These files can be downloaded directly through the EGA-download-client PyEGA3 (https://github.com/EGA-archive/ega-download-client). For any further questions, please contact the DAC (Helpdesk - email: helpdesk [at] ega-archive [dot] org).

  Dataset EGAD00001009826

• H3K27ac/H3K27me3 landscape of medulloblastoma

  We profiled 111 patient medulloblastoma primary tumor samples by bulk RNA-seq (19 samples), 27ac (98 samples) / 27me3 (61 samples) ChIP-Seq, WGS (4 samples) and 27ac hichip (8 samples). Submitted data consists of data generated from previously unpublished tumors as well as complementary data for data sets already published for identical medulloblastoma tumors (ex: 27me3 ChIP-Seq and RNA-Seq data submitted for a tumor with publicly available WGS data). The raw fastqs and hg19 aligned RNA-Seq bams are provided.

  Dataset EGAD00001009709

• WGS data from NEN patient derived tumor organoids (PDTOs) and matched parental tumors - UMCU/NKI

  The dataset includes cram files from WGS of 6 NEN tumors or metastases and matched PDTOs. For all tumors, cram files from WGS of either matched normal tissue or matched blood from the corresponding patients are included. Analysis VCF files are also included in the dataset. The sequencing was done with a NovaSeq 6000 instrument.

  Dataset EGAD00001009989

• Long-read sequencing identifies a common transposition haplotype predisposing for CLCNKB deletions

  This dataset contains CLCNKA/CLCNKB locus alignment data from 27 patients with Bartter syndrome and structural variants encompassing the CLCNKB gene. Due to data protection regulations and in accordance with the patient consent, only relevant alignments from the following regions are shared: hg19: chr1:16,300,000-16,400,000 hg38 (linked read dataset only): chr1:16,000,000-16,100,000 Methods to generate libaries were: long-range amplicon PCR (24 samples), targeted long-fragment enrichment (Samplix/Xdrop technology, 4 samples), long-read whole genome (PacBio Sequel II HiFi reads, 3 samples), 10X linked read short read whole genome (1 sample).

  Dataset EGAD00001011064

• TXT_Cytof_15B

  Matrix of normal values from 39 marker CyTOF assay performed on longitudinal BMMC. FCS files from the CyTOF assay were normalized and concatenated using Fluidigm's CyTOF software and then de-multiplexed using Astrolabe Diagnostics, Inc., a commercial, cloud-based platform for single-cell analysis.

  Dataset EGAD00001011143

• SNF_CyTOFF_20

  Matrix of normal values from 39 marker CyTOF assay performed on baseline BMMC. FCS files from the CyTOF assay were normalized and concatenated using Fluidigm's CyTOF software and then de-multiplexed using Astrolabe Diagnostics, Inc., a commercial, cloud-based platform for single-cell analysis.

  Dataset EGAD00001011146

• Blood plasma and FFPE derived total RNA seq dataset from DLBCL and PMBCL patients

  Blood plasma samples (n=168) and matched diagnostic formalin-fixed paraffin-embedded (FFPE) tissue samples (n=69) of DLBCL patients, PMBCL patients and healthy controls were collected between 2016-2021. Plasma samples were collected at diagnosis, at interim evaluation, after treatment, and in case of refractory or relapsed disease. RNA was extracted from 200 µl plasma using the miRNeasy serum/plasma kit and from FFPE tissue using the miRNeasy FFPE kit. RNA was subsequently sequenced on a NovaSeq 6000 instrument using the SMARTer Stranded Total RNA-seq pico v3 library preparation kit.

  Dataset EGAD00001011679

• Enhanced Adjuvanticity of a Personal Neoantigen Vaccine Generates Potent Neoantigen-Specific Immunity

  Personalized neoantigen-targeting vaccines can induce durable and diverse T cell responses and have been associated with improved outcomes. To augment immunogenicity, we tested a synthetic long peptide vaccine formulated with the adjuvants Montanide and poly-ICLC in 10 patients with melanoma. The vaccines, co-administered locally with ipilimumab and systemically with nivolumab, generated de novo ex vivo T cell responses against the majority of immunizing neoepitopes in all 9 fully vaccinated patients, and ex vivo CD8+ T cell responses in 6 of 9. Hundreds of circulating and intratumoral T cell receptor (TCR) clonotypes emerged following vaccination that were distinct from those arising after PD-1 inhibition. By linking vaccine-specificity and cellular phenotype of TCRs in post-treatment tumors at single cell resolution, we demonstrate remodeling of the intratumoral T cell repertoire following vaccination. These observations demonstrate the impact of multi-pronged immune adjuvanticity on the T cell repertoire in the context of neoantigen-targeting vaccines. We are submitting WES data from whole blood samples and tumor FFPE samples, and RNA-seq data from tumor FFPE samples. We are also submitting RNA-seq data from purified tumor samples. scRNA-seq data will also be submitted for skin samples (pre and post neoantigen vaccine dose #3), and tumor samples before starting treatment, before starting neoantigen vaccine Dose #1, and before neoantigen vaccine dose #4. Bulk TCR-seq data will be submitted for blood samples.

  Study phs003919

• GeneSTAR (Genetic Study of Atherosclerosis Risk) NextGen Consortium: Functional Genomics of Platelet Aggregation Using iPS and Derived Megakaryocytes

  The causal mechanisms of common diseases and their therapies have been only marginally illuminated by genetic variants identified in genome wide association studies (GWAS) utilizing single nucleotide polymorphism (SNPs). Platelet activation pathways reflecting hemostasis and thrombosis are the underlying substrate for many cardiovascular diseases and related acute events. To overcome GWAS limitations, genomic studies are needed that integrate molecular surrogates for platelet-related phenotypes assayed in cell-based models derived from individuals of known genotypes and phenotypes. In our GWAS study of native platelet aggregation phenotypes and aggregation in response to low dose aspirin in 2200 subjects (GeneSTAR, Genetic Study of Aspirin Responsiveness), important genome wide "signals" (p<5x10-8) associated with native platelet aggregation and important "signals" associated with platelet responsiveness to aspirin were identified and replicated. Although we are currently performing functional genomics studies to elucidate our most promising findings in known genes (PEAR1, MET, PIKC3G), most "signals" occurred in intergenic regions or in introns. Mechanistic interpretation is limited by uncertainty as to which gene(s) are up- or down-regulated in the presence of most SNP modifications. In this 3 phase proposal, we will (1) create pluripotent stem cells (iPS) from peripheral blood mononuclear cells, and then differentiate these stem cells into megakaryocytes (2) develop an efficient strategy to produce iPS and megakaryocytes using a novel pooling method, and (3) produce iPS and megakaryocytes from 250 subjects in GeneSTAR (European Americans and African Americans), selected based on specific hypotheses derived from GWAS signals in native and post aspirin platelet function; characterize genetic mRNA transcripts using a comprehensive Affymetrix array; measure protein expression for transcripts of interest using mass spectrometry; examine mRNA and protein expression patterns for each GWAS signal to determine the functional pathway(s) involved in native platelet phenotypes; and examine the functional genomics of variations in responsiveness to aspirin using our prior genotyped and phenotyped population. Precise information about the exact functional processes in megakaryocytes and platelets may lead to innovative and tailored approaches to risk assessment and novel therapeutic targets to prevent first and recurrent cardiovascular and related thrombotic events.

  Study phs001074

• NICHD Genomic and Proteomic Network for Preterm Birth Research (GPN)

  We performed genome-wide association studies (GWAS) to study the Spontaneous Preterm birth (SPTB). Maternal and neonatal DNA from 743 SPTB (20 to and less than 34 weeks), and 752 controls (39 to and less than 42 weeks) who fully consented for public research usage were collected from participants in several clinical centers in Alabama, Illinois, New York, North Carolina, Rhode Island, Texas, and Utah. Cases were 1:1-matched with controls according to race/ethnicity (White, Hispanics, African Americans, and Others), maternal age (<20, 20-29, 30-39, 40+), and parity (yes or no). To determine the case-control status for each participant, a Gestational Age (GA) was determined. DNA samples were taken from blood or saliva if blood was not available. Automated DNA extractions were performed on the Qiagen M48 robot, and samples were organized in 96-well plates with barcoding and sample tracking systems. Subsequent manipulations were performed on the Biomek FX liquid handling workstation with 96-channel pipetting. DNA quantitation was performed by dye-based assay on a Molecular Devices SpectraMax Plus plate reader. Samples were genotyped using Affymetrix Genome-Wide Human SNP Array 6.0. This work was conducted at the Microarray Facility at the University of Pennsylvania. Patient data were collected through chart reviews and patient interviews, which included Demographic information (parental age, race, ethnicity, etc.); Medical history (pre-pregnancy weight, height, medications, STD history, medical conditions, etc.); Social history (marital status, years of education, alcohol use and tobacco use); Obstetrical history including outcome of all prior pregnancies and dates of termination; History of preterm labor or premature rupture of membranes symptoms, evaluation or hospitalization for those symptoms in current pregnancy; Medications taken during current pregnancy; History of cervical evaluation (manually or ultrasonographically) or fetal fibronectin measurements; Pregnancy complications; Labor (type, indications, membrane status, and induction method); Delivery type and indications for cesarean section; Neonatal outcome (sex, weight, length, Apgar score, neonatal complications, admission to intensive care unit, etc.); and Maternal family history of SPTB.

  Study phs000714

• Type 1 Diabetes Genetics Consortium (T1DGC): Genome-Wide Association Study in Type 1 Diabetes, 2008

  Cases with Type 1 Diabetes (T1D) in the UK, were part of the Wellcome Trust Case Control Consortium (WTCCC) - http://www.wtccc.org.uk - that first reported in 2007: Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447, 661-678. [PubMed: 17554300] In this genome-wide association study (GWAS), funded by the NIH and JDRF, and sponsored by the Type 1 Diabetes Genetics Consortium (T1DGC), we were able to extend the case and control groups used in the WTCCC, with the intention of performing a well-powered meta-analysis. The study is written up as: Barrett, J.C., Clayton, D.G., Concannon, P., Akolkar, B., Cooper, J.D., Erlich, H.A., Julier, C., Morahan, G., Nerup, J., Nierras, C., Plagnol, V., Pociot, F., Schuilenburg, H., Smyth, D.J., Stevens, H., Todd, J.A., Walker, N.M., Rich, S.S. and The Type 1 Diabetes Genetics Consortium Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nature Genetics, PMID: 19430480. Resources - data: * Case data from this study is deposited here (i.e. in dbGaP) * Control data from this experiment - with subjects from the 1958 British Birth Cohort - is deposited with the European Genotype Archive (EGA): http://www.ebi.ac.uk/ega/ from where the WTCCC data is also available. * A complete description of how to request all components of the meta-analysis is available at: http://www.t1dbase.org/page/PosterView/display/poster_id/324 * Additional genetic data on the same case subjects, including some HLA types, are available from the Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory (JDRF/WT-DIL): http://www-gene.cimr.cam.ac.uk/todd/ Resources - samples: Case and control DNA samples are also available: * Case DNA samples are available from the JDRF/WT-DIL, as above, and will be available from the NIDDK Genetics Repository at Rutgers: https://www.niddkrepository.org * Control DNA samples are available from the 1958 British Birth Cohort (aka National Child Development Study): http://www.cls.ioe.ac.uk/studies.asp?section=000100020003 Use restrictions: There are access limitations to both data and samples, in order to keep their use in line with subjects' consent.

  Study phs000180

• Copy-Number Analysis of Understudied Black Women Ovarian Cancers

  Two general types of genetic alterations drive cancer progression: mutations and copy number alterations (CNAs). With the exception of p53, single nucleotide variant mutations (here, simply "mutations") are not drivers of 80% of tumors within the most frequent and deadly histotype of ovarian cancer: serous ovarian cancer (SOC). Rather, CNAs are more prevalent in SOC than any other cancer type studied by phs000178 The Cancer Genome Atlas (TCGA). Fully two-thirds of genes are altered by CNAs in the average SOC. Bioinformatic methods have shown that these CNAs modulate specific molecular pathways, such as autophagy, and this finding enabled effective pathway-targeted therapies1. Unfortunately, TCGA ovarian cancer data lacks racial diversity. Only 6% of SOC tumors (n=32) studied are from African origin. Black women diagnosed with ovarian cancer are more likely to die from their disease than white women. Five-year survival after diagnosis is 31% among blacks versus 42% among whites, and this disparity is seen in every age group and tumor stage distribution. Dr. Kelemen examined data from 365 white and 95 black ovarian cancer patients from the Hollings Cancer Center (HCC) Cancer Registry between 2000 and 2015 and found that black women had an 81% higher risk of death after diagnosis compared to white women (HR 1.81, 95% CI 1.35-2.43), independent of diagnosis center (98% were treated at HCC but half were diagnosed elsewhere), tumor stage, histology, extent of residual tumor remaining following surgery, insurance status, smoking, type of treatment for ovarian cancer, and age-adjusted Charlson comorbidity index. This disparity remained even when restricted to women who received the standard of care, surgery-chemotherapy sequence (HR 1.79, 95% CI 1.10-2.89). Despite receiving the same treatment, black race was still associated with inferior survival. A similar disparity has been reported by others, indicating that the HCC experience is representative of national data. Here, an additional set of high-grade serous ovarian cancer primary tumors were acquired from biorepositories with a focus on expanding data originating from African American women. Data were analyzed for copy-number alterations using exome sequencing and control-FREEC software.

  Study phs002313

• RNA-Seq of Whole Blood from Patients with Intracranial Aneurysms

  Rupture of intracranial aneurysms (IAs) causes intracranial hemorrhaging that leads to high rates of neurological deficits and death. Although rupture rates are low, clinicians must decide whether to treat or monitor these potentially dangerous lesions. In the current clinical practice, the most common metric to measure risk of rupture is aneurysm size. However, clinical data show that small aneurysms can also rupture. As a result, alternative clinical stratification scores have been proposed, including the PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, and Site) score based on patient demographics and IA characteristics to stratify ruptured and unruptured IAs, and the Rupture Resemblance Score (RRS) that stratifies ruptured and unruptured IAs based on hemodynamic and morphological properties. However, all metrics require imaging on digital subtraction angiography (DSA), which is invasive, expensive, requires the use of X-rays, and is associated with transient or permanent neurological and non-neurological complications. We hypothesize that individuals with dangerous IAs have detectable gene expression differences in their blood that could be used as biomarkers to determine rupture risk. We propose to use whole blood transcriptomes to develop a "one-stop" diagnostic test that can detect the presence of IAs and determine the risk of rupture based on circulating RNA expression biomarkers using our prototype AneuScreenTM platform. We aim to develop and validate biomarkers to predict risk, as calculated by the currently-used metric of aneurysm size, the clinical PHASES score, and the RRS. Here, we collected blood samples from consented individuals who were receiving cerebral imaging at the Gates Vascular Institute (Buffalo, NY) for intracranial aneurysm. RNA extracted from blood samples (n=43) was subjected to RNA-sequencing and added to our existing database (n=44). When combined with our previous data, we had transcriptome data from 68 aneurysms (after additional sample filtering). This dataset was stratified into low- and high-risk according to IA size, PHASES score, and RRS score. Differentially expressed genes were identified and used to construct predictive models. Fastq files and basic demographic information for the 43 newly-sequenced intracranial aneurysm samples on this project will be available through dbGaP.

  Study phs003072

• NHLBI GO-ESP: Early-Onset Myocardial Infarction (Broad EOMI)

  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. In the Grand Opportunities Exome Sequencing Program Early MI Project (GO ESP - EOMI), we are sequencing cases with extremely early-onset MI drawn from 8 cohorts. These cohorts include five hospital or community-based studies that ascertained individuals based on MI status. These include PennCATH, Cleveland Clinic Genebank, Massachusetts General Hospital Premature Coronary Artery Disease Study (MGH-PCAD), Heart Attack Risk in Puget Sound (HARPS), and Translational Research Investigating Underlying Disparities in Myocardial Infarction Patients' Health Status (TRIUMPH). Cases were selected based on MI occurring in men aged ≤50 years and women aged ≤60 years. In addition, early-MI cases are being drawn from three population-cohort studies including the Framingham Heart Study, the Women's Health Initiative, and the Atherosclerosis Risk in Communities Study. MI-free controls are being drawn from five population-based cohort studies including the Framingham Heart Study, the Women's Health Initiative, Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, and the Jackson Heart Study. Controls were selected based on two factors: (1) highest predicted risk for MI based on Framingham risk score; and (2) absence of prevalent or incident MI despite a high predicted risk.

  Study phs000279

• Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

  The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

  Study phs001222

• 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

• Genome-Wide Pleiotropy Scan Across Multiple Cancers

  A whole-exome sequencing (WES) study was conducted in 3,233 cases diagnosed with multiple primary cancers and 3,229 matched cancer-free controls (90% non-Hispanic white, 3% African-American, 3% East Asian, and 4% Latino) selected from individuals in the Kaiser Permanente Research Bank (KPRB) who were members of the Kaiser Permanente Northern California (KPNC) health plan. Cancer-free controls were matched to cases on age at specimen collection (within 2 years), sex, genotyping array (which matched on self-reported race/ethnicity), closest distance using the first two principal components for genetic ancestry, and reagent kit. Cases and controls were drawn from two prospective KPRB cohorts: the Research Program on Genes, Environment and Health (RPGEH) and the ProHealth study. Participants were sequenced by the Regeneron Genetics Center using the Illumina NovaSeq 6000 platform, and sample preparation and quality control were performed using a high-throughput, fully-automated system [PMID: 33087929]. Reads were aligned to the GRCh38 reference genome, and variants were called using WeCall [PMID: 33087929]. Participants with sex discordance, 20x coverage at less than 80% of targeted sites, and/or contamination greater than 5% were excluded. After quality control, we retained n = 6,247 (3,111 cases, 3,136 controls) individuals for downstream analyses. Among participants selected for this WES study, n = 5,432 (2,299 cases; 3,133 controls) consented to deposition of data to the National Institutes of Health (NIH).Further quality control was applied to filter low quality variants. Genotype calls with low depth of coverage (DP) were updated to missing (DP < 7 for SNPs and DP < 10 for indels), after which sites with low allele balance (AB) - variants without at least one sample having AB ≥ 15% for SNPs or AB ≥ 20% for indels - were removed. Lastly, variants with missingness > 10% and Hardy-Weinberg equilibrium p-value < 10-15 were excluded. Further description of quality control and downstream single-variant and gene-based analyses is available in Cavazos et al, 2022 [medRxiv].

  Study phs002809

• B cell receptor silencing reveals origin and dependencies of high-grade B cell lymphomas with MYC and BCL2 rearrangements

  High-grade B cell lymphomas with MYC and BCL2 rearrangements (HGBCL-DH-BCL2) represent highly aggressive Germinal center (GC) derived B cell malignancies with dismal prognosis and limited therapeutic options. In the present study, we investigated the expression of BCR complex components, including immunoglobulin (IG) heavy (H) and light (L) chains, and CD79A and CD79B signaling subunits in HGBCL-DH-BCL2, scoring 65% of cases with undetectable IGH immunoreactivity (IGHUND). Transcriptomics (bulk RNA-seq) and genetic (whole exome/genome sequencing) analyses indicated that IGHUND and IGH+ HGBCL-DH-BCL2 lymphomas represent distinct biological entities. Specifically, IGHUND HGBCL-DH-BCL2 exhibit a GC DZ-like molecular program, and select subset-specific gene mutations pointing to distinct evolutionary trajectories respect to the IGH+ counterparts. IG profiling revealed that IGHUND HGBCL-DH-BCL2 preserved potentially productive, hypermutated IGH variable (V) gene rearrangements, indicating a selective advantage conferred to the malignant B cells by residual IGH molecules. Accordingly, disruption of the productively rearranged IGHG1 gene in BCRnull HGBCL-DH-BCL2 cell line model confirmed the dependency on IGH expression for optimal fitness. Using transcriptomics and in situ RNA-scope analysis, we reported that IGHUND HGBCL-DH-BCL2 originated from IG-class switched GC B cells, while IGH-expressing tumors were selected for continuous IGM expression. Moreover, while IGH+ HGBCL-DH-BCL2 favor IGM/IG-Kappa expression, IGHUND counterparts complete IG-Lambda light chain rearrangements. Notably, BCR silencing, caused by accelerated IGH turnover and reduced IGH expression, precedes HGBCL-DH-BCL2 onset, inducing RAG1/2-dependent IG light chain editing and eventually facilitating t(8;22)/IGL::MYC translocations. Finally, IGH silencing observed in HGBCL-DH-BCL2 cell models, which leads to intracellular retention/silencing of CD79B, results in reduced sensitivity to the CD79B-targeting antibody-drug conjugate Polatuzumab-vedotin. Collectively, HGBCL-DH-BCL2 originates from isotype-switched t(14;18)+ GC B cells that undergo IG light chain editing fuelling intra-clonal diversification, BCR silencing, and the acquisition of t(8;22) translocation, while preserving IGH dependency.

  Study EGAS50000001047

• Analysis of chromosomal background of cancerous mutations using a long-read sequencer

  In our previous study detecting cancerous complex SVs, we performed whole-genome sequencing of lung cancer clinical samples using PromethION. In this study, its depth and quality was substantially enriched and we conducted the phasing analysis in human lung cancer genomes. In addition, long read and short read RNA-seq was performed for transcriptome analysis.

  Study JGAS000349

• Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution

  We have used next generation sequencing to sequence genomes (>43-fold coverage) and transcriptomes of an oestrogen-receptor-alpha-positive metastatic lobular breast cancer at depth. We found 32 somatic non-synonymous coding mutations present in the metastasis, and measured the frequency of these somatic mutations in DNA from the primary tumour of the same patient.

  Study EGAS00000000054

• cis-eQTL mapping of TB-T2D comorbidity in a five-way admixed SA cohort

  The aim of the study was to identify ancestry-specific genetic variants associated with differentially expressed genes in TB-T2D comorbid patients compared to T2D patients, as well as between TB patients and healthy controls. Both global and local ancestry was incorporated in regression models to account for the genetic heterogeneity in our complex multi-way admixed population.

  Study EGAS00001007059

• Archive growth Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue In this section, we expose the overall volume of data available to download and the different archived file types. EGA Archive growth in size and number of files The below figure represents the EGA archive growth in size (TB) and number of files. EGA Archive Growth per year lineChart('ega-archive-growth', 'https://stats.ega-archive.org/growth/archive', ['Volume (TB)'], ['T']) Archive files The below figure represents on a initial level, the percentage of archived files by data technology. The second level, acessible by clicking in the required extension, displays the number of files by extension archived in the ega archive. Please click over the extension to learn more about the files. EGA Archived Files barChart('ega-archived-files', 'https://stats.ega-archive.org/extensions', false ,'', true)

  Documentation about/statistics/archive

• Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia [WGS]

  This dataset contains low‑pass whole‑genome sequencing data from 203 individuals representing four Indonesian populations: the general urban population of Denpasar and the traditional community of Pedawa Village in Bali, as well as traditional community of Yoboi Village (in Sentani lake) and Sereh Village (individuals from highland Papua residing near Sentani lake) in Papua. Sequencing was performed by Gencove using their low‑coverage whole‑genome platform. The dataset was produced as part of the Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia, a study aimed at characterizing how genetic background and environmental context shape immune cell states across diverse Indonesian communities.

  Dataset EGAD50000002384

• Comparison between b2m KO and US2 expressing iPSC lines

  This dataset contains bulk RNA-seq transcriptomic profiles from a human induced pluripotent stem cell (hiPSC) line and three engineered derivatives: B2M knockout, EGFP overexpression, and US2 overexpression, alongside the parental line. Total RNA integrity was assessed using the Experion RNA StdSens 1K Analysis Kit on the Bio-Rad Experion Automated Electrophoresis System prior to library preparation and sequencing. Libraries were sequenced on an Illumina NovaSeq 6000 generating ~20 million reads per sample. Raw read quality was assessed with FastQC, reads were aligned to the human reference genome hg38 (Ensembl release 109) using STAR, and alignment/library QC metrics (e.g., orientation, composition, coverage) were evaluated with Picard.

  Dataset EGAD50000002321

• Variant calling for LUNG-NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. This dataset contains whole exome sequencing data from tumor samples processed with the Vegan pipeline. In the absence of matching germline samples, variant calling is performed using two panel of normals (one for female and one for male). It includes SNP and CNV calling.

  Dataset EGAD50000002235

• RNAseq

  Libraries for sixty-eight cases (23 EATL and 45 MEITL) were prepared starting from 1 µg of total RNA using the TruSeq Stranded total RNA Gold kit from Illumina (San Diego, California, USA) and were sequenced in three batches on a HiSeq 4000 machine from Illumina with an average output of 63 million reads per sample (range 49-126).

  Dataset EGAD50000001619

• Single cell RNAseq and TCRseq data from tumor and blood samples from 4 patients with muscle invasive bladder cancer

  For this dataset we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients. This dataset contains 4 tumor samples as well as 4 blood samples. Each sample is made up of 2 sets of paired fastq files. The first pair contains reads corresponding to RNA transcripts (_Transcripts in file name), while the second pair contain reads corresponding to TCRs (_VDJ in file name). Sequenced on the Illumina NovaSeq6000 platform in a paired-end run using an SP flow cell (v1.5, 300 cycles).

  Dataset EGAD50000001381

• scRNAseq data of human innate lymphoid cells (ILCs) and natural killer (NK) cells from fresh umbilical cord blood

  scRNA-seq was performed on the BD Rhapsody platform. ILCs (ILC1, ILC2, ILC3) and NK cells were bulk sorted from fresh cord bloods of 3 donors. The 4 samples containing ILCs and NK cells from each donor were stained with Sampletag antibodies (12 samples in total) before Abseq staining with the BD Immune Discovery panel and 6 additional antibodies was performed to better classify immune cell subsets. The sorted population were pooled before loading onto the BD Rhapsody cartridge. The manufacturer's protocol was followed for library construction and samples were sequenced on a Illumina NovaSeq 6000.

  Dataset EGAD50000001713

• Cityscape Serum peptide Mass Spec data

  Matrix of counts from the serum peptide mass spec data from patients enrolled in the CITYSCAPE trial, and the sample annotation. Specifically, serum samples at C1D1, C2D1, C3D1, SCRN were collected from a total of 132 patients and subject to Mass Spec at Biognosys. The current study focused on patients who have samples at both C1D1 and C2D1 (n = 64 pairs). Associated metadata also included.

  Dataset EGAD50000000369

• Single-nucleus mRNA-Sequencing of prenatal and postnatal samples from the brain and its border regions

  Single-nucleus mRNA Sequencing of prenatal and postnatal samples from the brain and its border regions. Most samples were multiplexed with several samples run in one 10X reaction. A separate immune cell dataset was combined with published data from Braun et al 2023 and Yang et al 2021 integrated using harmony is included.

  Dataset EGAD50000000044

• GSA pilot raw data

  Unfiltered genotype data for a pilot study (Batch 1) of 1,140 DDD Study participants (and 12 "Empty" samples). Samples include 380 mothers, 382 fathers and 378 probands, and form 376 trios. Most of the probands have been previously genoyped on the llumina HumanCoreExome BeadChip (EGAD00010001598) or the Illumina InfiniumCoreExome Beadchip (EGAD00010001600). All samples were genotyped on the Illumina Global Screening Array.

  Dataset EGAD00010002567

• Summary Statistics GWAS SSNS

  Column 1 rsid: SNP identifier;Column 2 chromosome: name of chromosome on which the SNP is located;Column 3: position: base pair position on the chromosome;Column 4 minor_test_allele: the base that constitutes the minor allele;Column 5 major_allele: the base that constitutes the major allele;Column 6 maf: the frequency of the minor allele, indicated as a fraction of 1;Column 7 allele_freq_cases: the minor allele frequency in cases;Column 8 allele_freq_controls: the minor allele frequency in controls;Column 9 regression_pvalue: the p-value for the difference in allele frequency between cases and controls;Column 10 odds_ratio: the odds ratio, as calculated using logistic regression under an additive model with adjustment for the first ten principal components of ancestry

  Dataset EGAD00010002316

• FFPE tumor RNA exome capture sequencing

  This dataset includes raw, untrimmed FASTQ files generated from bulk RNA exome capture sequencing of FFPE tumor samples from 268 stage III colorectal cancer patients, prior to receiving adjuvant chemotherapy treatment. RNA libraries were prepared with the Illumina TruSeq RNA Exome kit and sequenced (PE51bp) using an Illumina NovaSeq 6000 with an S4 flow cell. The metadata file "RNAseq_metadata.tsv" contains columns with relevant quality metrics "DV200" and "cDNA_ng_ul" per sample, and a column indicating whether the sample was part of one or more published analyses: Franken et al., Eur. J. Cancer, 2026. PMID: 41650786. DOI: https://doi.org/10.1016/j.ejca.2026.116262 Crnovrsanin et al., XXX, 2026. PMID: XXX. DOI: XXX

  Dataset EGAD50000002440

• Multiregion Whole Exome sequencing of pHGG and DIPG

  The failure to develop effective therapies for paediatric glioblastoma (pGBM) and diffuse intrinsic pontine glioma (DIPG) is in part due to their intrinsic heterogeneity. Analysis of 142 sequenced cases revealed multiple tumour subclones, spatially and temporally co-existing in a stable manner as observed by multiple sampling strategies. This dataset provides multi region sequencing of high grade gliomas and diffuse intrinsic pontine gliomas from 15 patients. DNA was extracted from FFPE sections in 2-13 regions of each tumour and sequenced with Agilent SureSelect whole exome sequencing. Germline DNA was also sequenced in 14 cases. Data was aligned to hg19 with bwa and is provided as 79 separate BAM files.

  Dataset EGAD00001004114

• Multiple Malignancy Familial Comparison

  Patient (who has had multiple malignancies) has previously been found to harbour a pathogenic p53 variant which is probably mosaic. This finding is based on exome sequencing performed elsewhere. In this study we will resequence the locus in question to ascertain whether the variant is indeed mosaic.

  Dataset EGAD00001001062

• ESGI-Identification of novel genes and mechanisms leading to Primary Ciliary Dyskinesia

  Approximately 80% of clinically clearly diagnosed patients suffering from primary ciliary dyskinesia (PCD) cannot be assigned to a specific gene defect. Despite extensive research on PCD and despite the increasing number of PCD genes and knowledge about their sites of action as e.g structural component or cytoplasmic pre-assembly factor, the biology of motile cilia and the pathomechanism leading to PCD is largely unknown. The aim of this study is to identify novel PCD related genes and processes relevant for motile cilia function.We will perform exome sequencing, aiming on the analysis of family trios. In these families, the diagnosis of PCD is secured, but the underlying gene defects has so far not been identified.

  Dataset EGAD00001001092

• Genetic background for the major psychiatric disorders in the general Finnish population

  Low coverage (4-6x) sequencing on samples from population cohorts (Finrisk, Health2000) will be done at Wellcome Trust Sanger Institute (WTSI) using Illumina HiSeq sequencing technology. We will produce 100bp paired end reads. Variants will be called using the 1000 Genomes Project pipeline. The samples have been selected from a national representative set of 8028 samples from persons of 30 years or older, which were screened for psychotic and bipolar disorders using the Composite International Diagnostic Interview, self-reported diagnoses, medical examination, and national registers.

  Dataset EGAD00001001250

• C9orf72 region reads of 3001 samples

  This dataset includes cram files from 3,001 samples. These cram files include all read pairs where at least one of the reads aligns within 1kb of the C9orf72 repeat expansion. Additionally, these cram files also contain reads that are aligned to any of 29 pre-determined off target locations where the aligners are known to mis-align reads associated with this repeat expansion. These samples were sequenced using a combination of 2x100bp reads on an Illumina HiSeq2000 and 2x150bp reads on an Illumina HiSeqX sequencer and aligned using the Isaac aligner.

  Dataset EGAD00001004834

• Polymorphisms in the Mitochondrial Genome associated with Bullous Pemphigoid in Germans

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

  Dataset EGAD00001005379

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Kazakhs (DNA samples from the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan; Gulnara Svyatova, Principal Investigator

  Whole genome sequencing of 100 unrelated Kazakhs in order to impute genotypes into PE cases and controls from Kazakhstan and to provide genetic data and infrastructure for future genetic studies in Kazakhstan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This dataset is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator)

  Dataset EGAD00001005467

• Sequencing data for oesophageal and related samples - Noorani et al (WGS)

  Data supporting: "Genomic evidence supports a clonal diaspora model for metastases of esophageal adenocarcinoma." Noorani et al. WGS (BAM files) 134 samples for 18 cases Includes primary, lymph-node, distant metastatic, Barrett's and normal samples.

  Dataset EGAD00001005434

• Colon Cancer Organoid Cultures and Tumors Whole Genome Sequencing Data

  Five hundred nanograms of genomic DNA was fragmented by Covaris S2, the fragmented DNAs were performed end-repair, A-tailing at the 3 prime end, adaptors ligation with an IDT dual-indexed UMI adaptor system at the terminal ends. The adapter ligated library with size range 300-750bp were selected by dual-SPRI method. Twenty percent of the size selected PCR-free libraries were enriched by 5 PCR cycles prior to library size assessment by Bioanalyzer Fragment Analyzer. The PCR-free libraries were quantified by qPCR.The PCR-free libraries were denatured and diluted to optimal concentration. Illumina NovaSeq 6000 was used for Pair-End 151bp sequencing.

  Dataset EGAD00001005759