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• scRNA-seq and scTCR-seq data IMCISION

  We performed single cell RNA and TCR sequencing (10x Genomics) on immune infiltrates (CD45+ cells) from 18 HNSCC patients enrolled in the IMCISION trial (Vos et al. 2021). Viable immune cells were isolated from pre-treatment and on-treatment primary tumor biopsies of 10 patients responding (1 partial pathological response and 9 major pathological responses) and 7 patients non-responding to anti-PD-1 and anti-CTLA4 combination immunotherapy. One patient treated with anti-PD-1 monotherapy (1 major pathological response) was included in the dataset.

  Study EGAS00001007368

• RNAseq of circulating monocytes of familial hypercholesterolaemia (FH) patients before and after treatment, and healthy controls.

  RNAseq of circulating monocytes of familial hypercholesterolaemia (FH) patients before and after treatment, and healthy controls. Please cite original paper: Monocyte and macrophage lipid accumulation results in downregulated type-I interferon responses. Willemsen et al. Frontiers in Cardiovascular Medicine (2022) Familial hypercholesterolemic patients (n=10) and healthy subjects (n=9): the study population, design, and further processing of these human study subjects and their samples have been extensively described (Stiekema et al., 2021). Briefly, untreated FH patients who indicated to start lipid-lowering therapy (statin, PCSK9 antibody, and/or ezetimibe) according to their treating physician were included. The healthy controls were age, sex, and body mass index (BMI) matched with the FH patients. After inclusion, FH patients fasted for at least 9 hours before blood samples were drawn for lipid measurements and monocyte isolation. This was repeated after 12 weeks of lipid-lowering therapy. RNA-seq was performed on circulating monocytes. V1 = visit 1. V2 = visit 2.

  Dataset EGAD00001008967

• RNA-seq Revision

  The dataset comprises bulk RNA‑seq libraries generated on the Illumina NextSeq 500 platform, including primary human hepatocytes (four donors), colon tissue (four masked replicates), and a comprehensive set of iPSC‑derived samples from the JHU106, ChiPSC18, ChiPSC22, and H9 lines. The collection covers multiple differentiation stages from iPSC to DE to HLC and cultivation protocols (CEL, HAY, SPH) with at least three replicates per condition. All sequencing data are provided as raw FASTQ files, with colon samples delivered as masked FASTQ in accordance with patient consent requirements.

  Dataset EGAD00001008951

• Tcells_CD_scRNAseq

  This set features unfiltered, aligned, UMI-based single cell RNA sequencing count data for 5290 Blood, intraepithelial ileum (IEL) and lamina propria ileum (LPL) T cells from Crohn's disease patients as published in Uniken Venema et al, Gastroenterology 2019

  Dataset EGAD00010001649

• Sahel Data Access Committee

  Genome-wide genotype array data of Fulani populations presented in Fortes-Lima et al. 2025. Citation: Population History and Admixture of the Fulani People from the Sahel. Cesar A. Fortes-Lima, Mame Y. Diallo, Václav Janoušek, Viktor Černý, and Carina M. Schlebusch. American Journal of Human Genetics 112(2), February 6, 2025. doi: https://doi.org/10.1016/j.ajhg.2024.12.015

  Dac EGAC50000000290

• Low-coverage Whole Genome Sequencing, Colorectal advanced adenomas, NKI-AvL TGO COCOS series

  For this tissue dataset, we applied low-pass whole genome sequencing to 96 advanced adenomas. Advanced adenomas were classified as lesions with low-risk or high-risk of progression, according to the presence of specific DNA copy number changes (Carvalho et al, CancerPrevRes, 2018).

  Dataset EGAD00001004078

• Whole exome sequencing of 27 Greenlanders

  The data contain whole exome sequencing of 27 Greenlanders in nine trios. Data were produced by Agilent SureSelect capture followed by paired-end Illumina HiSeq 2000 sequencing to a depth of 90.1X. More details on processing and analysis can be found in Moltke et al, Nature 2014 (PMID 25043022).

  Dataset EGAD00001003813

• Chromatin 3D interactions mediate genetic effects on gene expression (RNA-seq)

  RNA-seq data for 168 Lymphoblastoid Cell Lines (LCL) and 78 Fibroblasts (FIB) from the Gencord Cohort. This dataset was generated as part of the following study: Delaneau et al (2019). Chromatin 3D interactions mediate genetic effects on gene expression.

  Dataset EGAD00001004872

• Epichaperome - Englander Institute for Precision Medicine - Weill Cornell Medicine DAC

  This dataset accompanies the publication of Sugita M et al. "Targeting the Epichaperome As an Effective Precision Medicine Approach in a Novel PML-SYK Fusion Acute Myeloid Leukemia" Npj Precision Oncology 2021

  Dataset EGAD00001006904

• ETMR H3K27Ac ChIPSeq

  H3K27Ac ChIP-seq DNA libraries for 5 ETMR samples were prepared using NEBNext ChIP-seq Illumina Sequencing library preparation kit. ChIP-seqlibraries were sequenced using single-end 50 bp reads on the Illumina HiSeq 2000 platform. ChIP-seq peaks analysed was conducted as published previously(Torchia et al. 2016).

  Dataset EGAD00001004809

• Bulk RNAseq of Neuroblastoma patient's tumors

  This dataset contains 9 bulk RNAseq of neuroblastoma patient's tumors used to compare with derived PDXs and/or single-cell data in the Thirant C et al, Nature Communications, 2023. They were intially produced for the Berlanga P., Cancer Discovery, 2022.

  Dataset EGAD00001010287

• eQTL summary statistics

  This dataset contains the eQTL summary statistics (nominal pass, significant eQTLs, best associated variant per gene). eQTL mapping was performed with fastQTL. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

  Dataset EGAD00001005041

• PFA ependymoma study -WGS data

  WGS bam file for the 18 samples used in Michealraj et al. Cell 2020. The dataset includes PFA ependymoma tissue, derived line and blood samples of 6 patients WGS data were aligned with BWA to the hg38 human reference genome (igenome) and further processed according to the GATK best practice pipeline.

  Dataset EGAD00001006045

• Center for Common Disease Genomics [CCDG] - Cardiovascular: TexGen

  Cardiovascular disease (CVD), especially coronary heart disease, heart failure and cerebrovascular disease remain the leading causes of death in men and women across all race groups in the United States. Substantial evidence exists for genetic factors underlying CVD risk, and their discovery offers an opportunity to enhance understanding of disease mechanisms, to provide specific diagnostic and prognostic indicators, and to identify novel therapeutic targets. The Centers for Common Disease Genomics (CCDG) are a large-scale genome sequencing effort undertaken as a collaboration to identify rare risk and protective alleles for common chronic diseases, with a current focus on early onset heart disease, hemorrhagic stroke, and autism. In this study, whole genome sequencing (WGS) was performed in 6,146 individuals with any personal or family history of CVD from the TexGen study who were recruited from several institutions in the Texas Medical Center located in Houston, Texas. The participants included patients who were admitted with a variety of diagnoses including acute coronary syndromes, strokes, and transient ischemic attacks, or who underwent percutaneous coronary interventions or coronary artery bypass grafting (CABG) (Virani SS et al. Am J Cardiology 107:1504-1509, 2011). Patients in the TexGen cohort with a confirmed diagnosis of acute coronary syndrome (ACS) or CABG when discharged from the hospital between 2001-2008 were eligible for a follow-up study of recurrent myocardial infarction (Virani SS et al. Circulation J 76:950-956, 2012), while those presenting with ACS beginning in 2007 were recruited for an investigation of the role of depressive symptoms in the risk of major adverse coronary events (Sanner J et al. Biol Res Nurs 20:168-176, 2018). In addition, the initial criterion for enrollment in a third TexGen sub-study undertaken between 2007 and 2013 was the occurrence of premature acute myocardial infarction in men ≤ 50 years and women ≤ 55 years in order to establish a blood sample collection resource with the intention of localizing genes that contribute to disease risk. This definition was later expanded to include individuals with a clinical history of premature coronary heart disease such as CABG or percutaneous coronary interventions.

  Study phs003010

• 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

• A phase II trial of the aurora kinase A inhibitor alisertib for patients with castration resistant and neuroendocrine prostate cancer: efficacy and biomarker evaluation

  Neuroendocrine prostate cancer (NEPC) is an aggressive variant of prostate cancer that may develop de novo or as a mechanism of treatment resistance. N-myc is capable of driving NEPC progression. Alisertib inhibits the interaction between N-myc and its stabilizing factor Aurora-A, inhibiting N-myc signaling, and suppressing tumor growth. In this single arm, multi-institutional open label phase 2 clinical trial of alisertib, sixty men were treated with alisertib 50mg twice daily for 7 days every 21-days. Eligibility included metastatic prostate cancer and at least one: small cell neuroendocrine morphology; ≥50% neuroendocrine marker expression; new liver metastases without PSA progression; elevated serum neuroendocrine markers. The primary endpoint was six-month radiographic progression free survival. Pre-treatment biopsies were evaluated by whole exome and RNA-seq.

  Study phs001666

• Genome-wide Association Study and Meta-Analysis of Ewing Sarcoma

  We combined a set of 122 French Ewing sarcoma (EWS) cases from the Institut Curie, 19 EWS cases from the National Cancer Institute (NCI) Center for Cancer Research (CCR), and 29 EWS cases from the NCI Bone Disease and Injury Study. All EWS cases were confirmed by medical record review and the presence of a specific EWSR1-ETS translocation were noted when data was available. Each participant provided informed consent and each participating study was approved by the Institutional Review Boards of their study center. DNA was extracted using standard methods from blood, saliva (Oragene), or buccal cells. All de novo genotyping of EWS cases was performed at the NCI CGR on the Illumina OmniExpress-24 v1.1 array. Genotyping was performed according to manufacturer's guidelines using the Infinium HD Assay automated protocol.

  Study phs001549

• Modeling Malignant Progression in Glioma

  Gliomas are the most common primary brain tumor in humans. Low-grade gliomas (WHO grade II) invariably progress to high-grade gliomas (WHO grade III or IV). Although malignant progression may take many years, the survival rate after transformation to a high-grade glioma is poor, often only 12-15 months. In this data set, we have identified low-grade gliomas that have progressed to high-grade gliomas or high-grade gliomas that have progressed from low-grade gliomas. Some cases are matched pairs (meaning we have both the original low-grade tumor and the subsequent high-grade tumor). The samples deposited have been analyzed with bulk-RNA sequencing. They are also de-identified but are clinically annotated. When available, genetic information including IDH mutation status, 1p/19q deletion and histological subtype are also included.

  Study phs002607

• Platinum Pedigree Consortium Long-Read Sequencing

  Platinum Pedigree Consortium includes whole genome sequencing of blood-derived DNA using five technologies on a 4-generation family. This is the CEPH-Utah (CEU) family 1463 and includes 4 grandparents from 1st generation, 2 parents from 2nd generation, 5 children from 3rd generation, 9 individuals from the 4th generation representing 2 branches of the 3rd generation, and their 2 additional parents. Family was not selected for disease, rather large size to study genetic transmission and human variation.Data available through dbGaP include raw sequence data: PacBio HiFi reads in unaligned BAM formats, Ultra-Long Oxford Nanopore (ONT) reads in FASTQ formats, Illumina sequencing, strand-seq and Element sequencing data in FASTQ format. Additionally, alignment files for HiFi reads mapped to the GRCh38 and CHM13v2.0 reference genomes, as well as de novo genome assemblies generated for this project are included.

  Study phs003793

• Molecular dissection of germline chromothripsis in a developmental context

  Complex germline genomic rearrangements can affect many genes and regulatory elements, but the precise mechanisms that caused the phenotype of patients with such rearrangements are often unknown. To dissect the impact of germline chromothripsis in a relevant developmental context, we performed trio-based RNA expression analysis on blood cells,induced pluripotent stem (iPS) cells and iPS-cell derived neuronal cells from a patient with de novo germline chromothripsis and both healthy parents. In addition, we performed Hi-C on iPS cell-derived neural progenitors of the patient and the father to study the effects of the chromothripsis rearrangements on the architecture of the derivative chromosomes. We demonstrate that a combination of patient-derived iPS cell differentiation and trio-based molecular profiling is a powerful approach to improve the interpretation of pathogenic complex genomic rearrangements.

  Study EGAS00001001896

• Whole exome sequencing data of germline and two independent primary leukemias of five patients

  The contribution of genetic predisposing factors to the development of pediatric acute lymphoblastic leukemia (ALL), the most frequently diagnosed cancer in childhood, has not been fully elucidated. Children presenting with multiple de novo leukemias are more likely to suffer from genetic predisposition. Here, we selected five of these patients and analyzed the mutational spectrum of normal and malignant tissues. In two patients, we identified germline mutations in TYK2, a member of the JAK tyrosine kinase family. These mutations were located in two adjacent codons of the pseudokinase domain (p.Pro760Leu and p.Gly761Val). In silico modeling revealed that both mutations affect the conformation of this auto-regulatory domain. Consistent with this notion, both germline mutations promote TYK2 autophosphorylation and activate downstream STAT family members, which could be blocked with the JAK kinase inhibitor I. These data indicate that germline activating TYK2 mutations predispose to the development of ALL.

  Study EGAS00001001889

• Study the differences at the trascriptome level between iNKT and T cells

  Chimeric antigen receptor anti-CD19 (CAR19)-T cell immunotherapy-induced clinical remissions in CD19+ B cell lymphomas are often short-lived. We tested whether CAR19-engineering of the CD1d-restricted invariant NKT (iNKT) cells would result in enhanced anti-lymphoma activity. CAR19-iNKT cells co-operatively activated by CD1d- and CAR19-CD19-dependent interactions are more effective than CAR19-T cells against CD1d-expressing lymphomas in vitro and in vivo. The swifter in vivo anti-lymphoma activity of CAR19-iNKT cells and their enhanced ability to eradicate brain lymphomas underpinned an improved tumor-free and overall survival. CD1d transcriptional de-repression by all-trans retinoic acid results in further enhanced cytotoxicity of CAR19-iNKT cells against CD19+ chronic lymphocytic leukemia cells. Thus, iNKT cells are a highly efficient platform for CAR-based immunotherapy of lymphomas and possibly other CD1d-expressing cancers.

  Study EGAS00001003176

• Analysis of IDHwt-glioblastoma samples from paired primary and recurrent tumor samples

  IDHwt-glioblastomas rapidly recur after initial treatment. To study genetic evolution in glioblastoma, we analyzed whole genomes of 21 pairs of primary and recurrent tumor samples using next generation sequencing. In addition we sequenced RNA from 16 tumor pairs and a panel of 50 glioma-associated genes in tumor pairs from 43 patients (including 14 of the 21 patients included in the WGS discovery set). Glioblastoma subtypes were determined using 450k/EPIC methylation arrays. This study was supported within the e:med program of the German Ministry of Education and Research (BMBF) by the collaborative research project ‘SYS-GLIO - Systems-based prediction of the biological and clinical behavior of gliomas’ (https://www.sys-med.de/de/demonstratoren/sys-glio/) This study is part of the Heidelberg Center for Personalized Oncology - HIPO-043

  Study EGAS00001003184

• Hereditary Cancer Diagnostics with I2HCP gene panel

  This dataset contains targetted DNA sequencing data generated in the context of genetic diagnostics of hereditary cancer. Target enrichment was performed with the I2HCP, a custom hereditary cancer gene panel based in Agilent SureSelect and developed by the Germans Trias i Pujol Research Institute (IGTP, Badalona, Catalonia, Spain) and the Catalan Institute of Oncology (ICO, L'Hospitalet de Llobregat, Catalonia, Spain). After the enrichment, 108 samples were sequenced in Illumina HiSeq machines and 130 in MiSeq machines. Some of the samples were sequenced on both platforms. The dataset also includes MLPA validation data for all identified copy-number alterations, annotated with exon resolution and information about negative MLPA results. All this data was generated in the context of routine diagnostics and compiled together with MPLA validation data for a genetic diagnostics oriented benchmark of germline CNV calling tools.

  Study EGAS00001004316

• Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors

  Malignant rhabdoid tumor (MRT) is one of the most aggressive childhood cancers for which no effective treatment options are available. Reprogramming of cellular metabolism is an important hallmark of cancer, with various metabolism-based drugs being approved cancer treatment. In this study, we use patient derived tumor organoids (tumoroids) to map the metabolic landscape of several pediatric cancers. Combining gene expression analyses and metabolite profiling using mass spectrometry, we find nucleotide biosynthesis to be a particular vulnerability of MRT. Treatment of MRT tumoroids with de novo nucleotide synthesis inhibitors lowers nucleotide levels in MRT tumoroids and induces apoptosis. Lastly, we demonstrate invivo efficacy of methotrexate in an MRT PDX mouse model. Our study revealsnucleotide biosynthesis as an MRT-specific metabolic vulnerability, which can ultimately lead to better treatment options for children suffering from this lethal pediatric malignancy.

  Study EGAS00001007877

• RCC_HTA2.0_Buettner2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Buettner et al, Genome Med 2022. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.26.0, R version 3.6.1). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 23).

  Dataset EGAD00010002353

• PDX_HTA2.0_Guergen2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) and RCC metastases related to Guergen et al, Front Oncol 12:2022 889789. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.34.0). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 25).

  Dataset EGAD00010002392

• BAM files from capture-based targeted sequencing of 4 agressive B-cell lymphoma tumour samples (DLBCL-panel)

  This dataset contains BAM files from capture-based targeted sequencing of 4 agressive B-cell lymphoma tumour samples for cases 2, 3, 4 and 13. The sequencing panel used is a DLBCL-oriented panel containing 136 genes, described in Mozas P. et al., Hematol Oncol 2023.

  Dataset EGAD50000000802

• Data from Shea et al Can Research 2025

  This dataset contains single cell RNA sequencing (192 fastq files for 59 samples), whole exome sequencing (20 BAM files -hg38- for 20 samples) and bulk RNA sequencing (138 paired-end fastq files and 17 single-end fastq files for 8 samples)

  Dataset EGAD50000001334

• HIV-phyloTSI: PANGEA (veSEQ-HIV)

  This dataset includes sample numbers TSI_0001 to TSI_0202 and TSI_0316 to TSI_0425 for the PANGEA (veSEQ-HIV) cohort of the study. Samples were sequenced using the Illumina NovaSeq system and the veSEQ-HIV method (see Bonsall, Golubchik et al 2020, DOI: 10.1128/JCM.00382-20). Each sample has a BAM file, and its associated reference file.

  Dataset EGAD50000001309

• HIV-phyloTSI: PANGEA (PCR amplicon)

  This dataset includes sample numbers TSI_0426 to TSI_0527 for the PANGEA (PCR amplicon) cohort of the study. Samples were generated by pooling four overlapping PCR amplicons (see Gall et al 2012, DOI: 10.1128/JCM.01516-12). The sequencing was conducted using the Illumina NovaSeq system. Each sample has a BAM file, and its associated reference file.

  Dataset EGAD50000001308

• DKFZ-St.Jude Medulloblastoma - 8 MB cases, exome/WGS data

  Tumor/Control pairs for 8 medulloblastoma cases, MB cohort, mixed exome and whole genome data, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

  Dataset EGAD00001006660

• MNM - 16S rDNA amplicon dataset of 20 dense timeseries of fecal samples from Belgian women

  Fastq files for the 16S rDNA amplicon library of 714 fecal samples of 20 time series (as described in Vandeputte et al. 2021, Nature Communications)

  Dataset EGAD00001008275

• 340 human whole genome sequences from Angola and Mozambique

  CRAM files of 340 human genomes from Angola and Mozambique. Paired-end reads were generated in an Illumina-X Ten and were mapped against the human reference genome build hg19/GRCh37. More details about the sequencing and the samples in Tallman et al. 2023. Nature Communications.

  Dataset EGAD00001011992

• RNA-seq data from DMD patients and healthy controls

  This dataset comprises RNA-seq expression profiles from 57 subjects, of which 39 are DMD patients and 18 healthy controls. The data are described in the following article: Signorelli, Ebrahimpoor et al. (in review). Peripheral blood transcriptome profiling enables monitoring disease progression in dystrophic mice and patients.

  Dataset EGAD00001006826

• Fixed single-cell transcriptomic characterization of human radial glial diversity

  The human neocortex is created from diverse intermixed progenitors in the prenatal germinal zones. These progenitors have been difficult to characterize since progenitors - particularly radial glia (RG) - are rare, and are defined by a combination of intracellular markers, position and morphology. To circumvent these problems we developed a method called FRISCR (Fixed and Recovered Intact Single Cell RNA) for transcriptome profiling of individual fixed, stained and sorted cells. We developed and validated FRISCR on human embryonic stem cells. We then profiled primary human RG (96 - 132 days post conception) that constitute only 1% of the mid-gestation cortex. These RG could be classified into ventricular zone-enriched RG (vRG) that express ANXA1 and CRYAB, and outer subventricular zone-localized RG (oRG) that express HOPX. Our study identifies the first markers and molecular profiles of vRG and oRG cells, and provides an essential step for understanding molecular networks driving the lineage of human neocortical progenitors. Reprinted from Thomsen et. al. Nature Methods (2015), with permission from Nature Publishing. Human embryonic stem cell data may be obtained through NCBI's GEO database, using accession number GSE71858. Raw data from one human sample that was not consented to be released to dbGaP may be obtained directly from the authors of Thomsen et. al., 2015.

  Study phs001016

• De Novo Mutation Rates at the Single-Mutation Resolution in the Human Genome

  We developed a method to measure the origination rates of target mutations of choice and applied it to the HbS and nearby mutations in the human beta-globin (HBB) gene, as well as to the equivalent mutations in the nearly identical delta-globin (HBD) gene in sperm cells from African and European donors. Specifically, after extracting DNA from the sperm of the donors, each sample is enriched for the HbS mutation and nearby mutations by the restriction enzyme Bsu36I, which cleaves the wild-type (WT) sequence CCTGAGG at positions 16–22 of HBB and the homologous positions of HBD while leaving the HbS mutant and other mutants in these positions intact. Next, unique barcodes are attached to the DNA fragments from these Bsu36I-treated samples in order to reduce error by consensus sequencing of copies originating from the same original fragment. To determine how many target WT sequences have been removed (scanned) by Bsu36I digestion and hence to be able to calculate the de novo mutation rate, we run a second reaction in parallel for each donor. This reaction involves the same steps as the former reaction except for digestion by Bsu36I (Bsu36I-untreated). Spiking into the Bsu36I-treated and untreated samples known amounts of mock HBB-like DNA molecules that are fully resistant to Bsu36I digestion allows to calculate in the sequence analysis stage the Bsu36I-enrichment score based on the change in their frequency between the two treatments, which in turn is used to calculate the number of scanned WT sequences. Our results show significant correspondence between de novo mutation rates and past observations of alleles in carriers, showing that mutation rates vary substantially in a mutation-specific manner that contributes to the site frequency spectrum. We also found that the overall point mutation rate is significantly higher in Africans than Europeans in the HBB region studied. Finally, the rate of the 20A>T mutation, called the “HbS mutation” when it appears in HBB, is significantly higher than expected from the genome-wide average for this mutation type. Nine instances were observed in the African HBB ROI, where it is of adaptive significance, representing at least three independent originations, and no instances were observed in the European HBB ROI or in the European or African HBD ROI.12 consented subjects; samples from two subjects were pooled

  Study phs002391

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002697

• Biology and Molecular Analysis of Human Hematopoiesis Genetics

  In this study we have performed exome sequencing using the hybrid capture method that has previously been described (Gnirke et al., Nature Biotechnology, 2009) on genomic DNA samples from patients with the congenital bone marrow failure syndrome that affects the erythroid lineage, specifically, Diamond-Blackfan anemia. This disease is characterized by a hypoplastic anemia and approximately 50% of cases are attributable to mutations in ribosomal protein gene subunits. The other 50% of cases do not have a known genetic etiology and the purpose of this study is to attempt to delineate such causes.

  Study phs000474

• NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC)

  The Diabetes Heart Study (DHS) is a family-based study enriched for type 2 diabetes (T2D). The cohort included 1443 European American and African American participants from 564 families with multiple cases of type 2 diabetes (Bowden et al., 2010. Review of Diabetic Studies 7:188-201. PMID: 21409311). The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery, and abdominal aorta all determined from non-contrast computed tomography scans.

  Study phs001412

• Comparison of transcriptomics profile of stem cell-derived beta cells from HUES8 and RC9

  Stem cell-derived islet cells have a potential to be used to restore endogenous insulin production in people with diabetes. The goal of this experiment is to compare the transcriptomics profile of stem-cell derived beta cells from two different cell lines: HUES8 (non-clinical grade) and RC9 (clinical grade) in terms of beta cell identity and maturity. Stem cell-derived islets were produced using differentiation protocol detailed in Rajaei et al. 2025 (manuscript approved in Science Translational Medicine, pending pubmed ID). Single cell transcriptomics data were generated using 10x Genomics 3' Single Cell Gene Expression kit.

  Study EGAS50000000905

• Targeted capture, whole genome sequencing, and RNAseq to identify rearrangements in B-cell lymphomas

  This study contains whole genome and custom targeted capture sequencing of mature B-cell lymphomas (DLBCL, FL, BL, HGBCL-DH-BCL2, HGBCL-DH-BCL6) to identify translocation breakpoints of common oncogene rearrangements (MYC, BCL2, BCL6). It is complemented by RNAseq data where available. Complete details are available in the publication Hilton et al, 2024, Blood. Capture sequencing: 357 samples; 364 unique libraries; cram file format aligned to hg38 Whole genome sequencing: 12 samples; 12 unique libraries; cram file format aligned to grch37 RNAseq: 257 samples; 257 unique libraries; fastq file format

  Study EGAS50000000328

• A WTCCC2 genome-wide association study for psychosis endophenotype (PE) in individuals from UK, Germany, Holland, Spain and Australia.

  A WTCCC2 project genome-wide association study for psychosis endophenotype (PE) in 5831 individuals from UK, Germany, Holland, Spain and Australia, genotyped on the Affymetrix 6.0 array. Information about the family structure of the samples can be found in the .info file which accompanies the data. It should be noted that a number of samples in this study have no phenotype information including sex, case status and family membership. Details of the WTCCC2 analysis can be found in Bramon et al. [Biol Psychiatry. 2014 Mar 1;75(5):386-97].

  Study EGAS00001000817

• PAS Pedigrees: Identification of novel genetic variants contributing to cardiovascular disease in pedigrees with premature atherosclerosis.

  The heritability of CVD has been estimated to be between 40 and 55%. Due to the low MAF, PAS-causing mutations cannot be identified by indirect genotyping because their presence cannot be inferred from common haplotypes, as has been done successfully to uncover common risk variants by GWAS. It has been shown by Ng et al that the causative gene for rare syndromes can be unequivocally identified by sequencing the exomes of only four cases and eight controls. We expect exome sequencing to result in a high number of mutations and non-causitive coding variants.

  Study EGAS00001000052

• Pulmonary atypical carcinoid multi-omic dataset on up to 42 tumours from same patient

  Pulmonary atypical carcinoid. DNA WES and RNA-Seq on 42 tumour samples collected at autopsy, 10x Chromium linked read whole genome sequencing on four tumours plus one normal sample, and targeted DNA sequencing on two clinical biopsies and one blood plasma sample. Note – RNA-Seq dataset features complex batch effect attributable to tissue processing artefacts, as described in "Complex patterns of genomic heterogeneity identified in 42 tumor samples and ctDNA of a pulmonary atypical carcinoid patient" - Robb et al., 2022 and detailed in Supplementary Table S3. Note – RNA-Seq dataset features complex batch effect attributable to tissue processing artefacts, as described in "Complex patterns of genomic heterogeneity identified in 42 tumor samples and ctDNA of a pulmonary atypical carcinoid patient" - Robb et al., 2022 and detailed in Supplementary Table S3.

  Dataset EGAD00001009296

• Privacy Notice for EGA Web user

  Privacy Notice for EGA Public Website This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org , or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? For providing you access to the website and for offering support whilst using the website, we need your consent under Article 5 (2) of the IP 68 (equivalent to Article 6 (1)(a) of the GDPR). For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: IP addresses Date and time of a visit to the service website Operating system Amount of data transmitted Browser Email address (only when support is requested by the user) The data controller will use your personal data for the following purposes: To provide the user access to the service To better understand the needs of the users and guide future improvements of the service To monitor website activities according to and in compliance with the Terms of Use To better understand the needs of the website visitors and guide future improvements of the service To conduct and monitor website security activities To create anonymous usage statistics 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? There are no personal data transfers to third countries or international organisations. 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. Object at any time to the processing of your personal data unless we can demonstrate that we have legitimate reasons to process your personal data. Request free of charge and without excessive delay rectification or erasure of your personal data if we have not been processing it respecting the data protection policies of the respective controllers. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-website

• Privacy Notice for Data Access Committee Account

  Privacy Notice for EGA Data Access Committee Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: email at dpo@embl.org, or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: Name Email address Title/Position Organisation Organisational affiliation Business address Telephone number IP addresses Date and time of a visit to the service website Operating system Amount of data transmitted Browser Username Password The data controller will use your personal data for the following purposes: To provide DAC user account and authenticated access to the service, To publicly publish some information to facilitate scientific research, To better understand the needs of the data subjects and guide future improvements of the service, To create anonymous usage statistics (from number of DACs, datasets per DAC). 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data), The general public via Internet will get access to your name, email address, business address, telephone number and organisation you belong to. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Data categories ‘name`, `email address`, `telephone number`, `business address`; `organisation’ of the DAC user are published on the Internet. They thus become accessible to recipients in countries outside the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI), is necessary for important reasons of public interest embedded in the aims of EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union 6. How long do we keep your personal data? Any personal data directly obtained from you will be retained as long as the service is live. Such duration serves the purpose of enabling scientific research and ensures legal compliance and facilitates internal and external audits if they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-dac

• RCC_HTA2.0_Reustle2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Reustle et al., Clin Transl Med 12:2022 e883. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.26.0, R version 3.6.1). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 23).

  Dataset EGAD00010002352

• lpWGS of solid and liquid samples from female patients with metastatic breast cancer

  low-pass Whole Genome Sequencing (lpWGS) to assess the representativeness of seven body liquids from female patients with metastatic breast cancer. 20 patients. 216 liquid samples, 745 solid samples, 20 matched normal samples. 0.5X coverage. Illumina single read sequencing. Fastq files are provided. lpWGS from Richard et al., Nature Communications, 2025.

  Dataset EGAD50000001851

• Exome sequencing of 277 rainforest hunter-gatherers and neighbouring farmers from Central Africa

  Exome sequencing of 277 rainforest hunter-gatherers (RHG) and neighbouring farmers (AGR) from Central Africa was performed based on the Nextera Rapid Capture Expanded Exome Kit (62-Mb content) with the Illumina HiSeq 2500. After QC filters, exomes of 266 unrelated individuals were obtained at high coverage (Lopez et al., Curr Biol 2019).

  Dataset EGAD00001005138

• RNA-seq data from hypothalamic tissue from individuals with Prader-Willi syndrome and age-matched controls.

  RNA-seq data (bam files) from the hypothalamus of 4 individuals with Prader-Willi syndrome and 4 age-matched control individuals. Detailed information about the study design, case-control matching and RNA-seq data processing is provided in the accompanying publication [Bochukova et al (2018) Cell Reports].

  Dataset EGAD00001004034

• A next-generation dual guide CRISPR system for genetic interaction library screening

  Raw sgRNA sequencing data from a pilot CRISPR screening library to test the dual guide vector system (8,914 guide pairs), and from a large scale genetic interaction screen (~100,136 guide pairs) in HT-29 cells. This data refers to Burgold et al. Nature Communications 2025.

  Dataset EGAD00001015754

• ETMR ATACSeq

  ATACSeq library amplification was performed on 5 ETMR tumour samples using the NEBnext High Fidelity 2xPCR Master Mix (New England Biolabs, Cat#M0541S) according to the manufacturer’s protocol. ATAC-seq libraries were sequenced using single-end 50 bp reads on the Illumina HiSeq 2000 platform. ATAC-seq peaks analysed was conducted as published previously(Torchia et al. 2016).

  Dataset EGAD00001004805

• NIMH (National Institute of Mental Health) De Novo Mutation Identification in Taiwanese Schizophrenia Trios

  The substantial reproductive impact of schizophrenia, for which affected individuals have fewer than half as many offspring as unaffected individuals do, implies that mutations of largest effect will frequently be de novo mutations. Ascertaining exome sequence variation in father-mother-offspring trios allows such mutations to be identified and distinguished from the far-larger amount of rare variation that is inherited by each individual. The pursuit of this approach in a large, well-powered cohort of trios can also provide lessons that inform the development of such gene discovery strategies more generally in human genetics. Schizophrenia trios from the Taiwanese population are being collected by Dr. Ming Tsuang (PI, UC San Diego, California) and investigators in Taiwan (PI, Dr. Hai Gwo Hwu; both funded by NIMH grant 1R01MH085560; Expanding Rapid Ascertainment Networks of Schizophrenia Families in Taiwan). A total of 3800 trios are anticipated to be collected by May 2013. This represents a highly homogenous national sample from the same ancestral population. DNA samples will be obtained from the NIMH Repository, Rutgers University Cell and DNA Repository (described below) and stored at the Broad Institute. Genetic and data analyses will be performed at the Broad Institute. We propose to sequence the whole exome of trios by hybrid capture and Illumina next generation sequencing and perform targeted genotyping and validation of variants (SNPs, indels and CNVs) using several molecular methods, to include emulsion-based PCR and Sanger sequencing.

  Study phs001196

• Purified vs unpurified stem cell-islets

  A scRNAseq dataset consisting of stem cell-derived islets treated with gradient separation (HUES8_Pure_Islets) and unpurified control (HUES8_control_islets). scRNAseq was done on cryopreserved stage 7 stem cell (HUES8 cell line)-derived islets. Details about stem cell differentiation and sequencing can be found on the publication by Rajaei et al. (2025, Science Translational Medicine). This dataset correspond to Fig 4 of the publication.

  Dataset EGAD50000001396

• Thirty cutaneous SCC WES tumour samples with matched normal

  Thirty cutaneous SCC WES tumour samples with matched normal include 20 samples from South et al. JID and 10 new samples. These 30 samples has been used to support the findings in the TGFb Nature Communications paper (DOI: 10.1038/ncomms12493). They are also a part of the ongoing study of cSCC genomic landscape of 40 cSCC samples in total.

  Dataset EGAD00001002253

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - barretts_1

  Samples from Ross Innes et. al 2015 - doi:10.1038/ng.3357

  Dataset EGAD00001001394

• Capture Hi-C on Hodgkin lymphoma

  In situ promoter capture Hi-C on Hodgkin lymphoma cell line L-428 in experimental triplicates. Hi-C libraries were prepared as previously described (Orlando et al., 2018, https://currentprotocols.onlinelibrary.wiley.com/doi/pdf/10.1002/cphg.63). Promoter capture was based on 32,313 biotinylated 120-mer RNA baits (Agilent). Hi-C libraries were sequenced using Illumina HiSeq 2000 technology. The files are in FASTQ format.

  Dataset EGAD00001004321

• 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

• Metagenome for FINRISK2002

  The dataset contains data for n=7211 FINRISK 2002 participants who underwent fecal sampling. Demultiplexed shallow shotgun metagenomic sequences were quality filtered and adapter trimmed using Atropos (Didion et al., 2017), and human filtered using Bowtie2 (Langmead and Salzberg, 2012). The files are in FASTQ format.

  Dataset EGAD00001007035

• Genomic Profiling of Peripheral T-cell Lymphoma

  Peripheral T-cell lymphomas (PTCLs) are malignant and highly aggressive hematologic tumors arising from mature post-thymic T cells. The diagnosis of PTCL includes diverse lymphoma subgroups, altogether accounting for about 15% of all non-Hodgkin lymphomas. Despite recent advances in uncovering the mutational landscape of PTCLs, the prognoses of most PTCLs remain poor. To overcome the limits of exome sequencing and identify new genomic abnormalities in PTCL, we performed RNAseq and whole genome sequencing. From our analyses, we identified a recurrent in-frame deletion (VAV1 Δ778-786) generated by a focal deletion-driven alternative splicing mechanism as well as novel VAV1 gene fusions (VAV1-THAP4, VAV1-MYO1F, and VAV1-S100A7). These genetic lesions result in increased activation of VAV1 catalytic-dependent (MAPK, JNK) and non-catalytic-dependent (nuclear factor of activated T cells, NFAT) VAV1 effector pathways. These results support an oncogenic role for VAV1 signaling in the pathogenesis of PTCL (Abate et al., 2017). Recently, we have also identified a novel chimeric oncogene, FYN-TRAF3IP2, in the RNA-seq and whole genome sequencing analyses. FYN-TRAF3IP2 leads to aberrant NF-κβ activity downstream of T-cell receptor signaling and induces NF-κβ-driven T-cell transformation when expressed in hematopoietic progenitors in mice. This novel gene fusion supports the oncogenic driver role of NF-κβ signaling in the pathogenesis of PTCL (Kim et al., in review).

  Study phs001962

• 10X CD4 auto-antigens

  Ex vivo CD4 T-cells from 4 donors were stimulated with antigen-coupled beads to aCD3, ABD, EBNA1, ANO2 or CRYAB and the LiveCD3+CD4+CFSEdim cells were sorted by flow cytometry. Cells were labelled with barcoded antibodies to identify the original stimulus. All stimulations from each donor were pooled into four reactions, i.e. one reaction per donor. Libraries were assembled with the 10X Chromium Next GEM Single Cell 5’ Kit for TCR and transcriptome with feature barcodes. Dataset contains raw fastq reads as well as supplementary information needed to link fastq files to modality, i.e. gene-expression, protein or VDJ, and includes supplementary information to de-multiplex the reactions by stimulation condition.

  Dataset EGAD50000002201

• Genomic Advances in Sepsis (GAinS): RNA-seq

  Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. This cohort comprises a subset of patients enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 34 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected on the first, third and/or fifth day following ICU admission. RNA was extracted from leukocytes isolated at the bedside using LeukoLOCK kits. We have previously identified sepsis response signatures (SRSs), transcriptomic endotypes that are associated with differential early mortality (Davenport et al, Lancet Respir Med, 2016; Burnham et al, AJRCCM, 2017) and response to treatment in a clinical trial (Antcliffe et al, AJRCCM, 2018). We generated RNA sequencing data on 903 samples, including 134 samples repeated from our previously released microarray data. Libraries were prepared using NEB Ultra II Library Prep kits (Illumina) and sequenced on a NovaSeq 6000. Reads were aligned to the reference genome (GRCh38) using STAR and gene counts quantified using featureCounts (annotation Ensembl v99). Counts were TMM-normalised and log-transformed. Following QC, processed data were available on 864 samples from 667 unique patients.

  Dataset EGAD00001008730

• Genes and Blood Clotting Study (GABC)

  Objectives: Use genome-wide approaches to identify genetic variants that influence common thrombosis and hemostasis factors, as well as selected common human traits. Design/Methods: The GABC study was a prospective sibling cohort design. Siblings were recruited by targeted email to the undergraduate and graduate student email lists at the University of Michigan. Healthy persons between 14 and 35 years old who had healthy siblings within the same age restriction were able to participate. Study participants agreed to an online informed consent and subsequently completed a 52-question online survey describing their specific bleeding traits as well as many common human traits. Fifty milliliters of blood was collected into a citrate-dextrose solution (ACD) from each participant. An aliquot of whole blood was used for an automated complete blood count analysis and the remainder was processed into platelet poor plasma and buffy coat portions. Plasma and buffy coat aliquots were snap frozen and stored in liquid nitrogen for future studies. 1189 individuals representing 507 sibships were collected between 06/26/2006 and 01/30/2009. Phenotyping Survey Details: To characterize individual bruising and bleeding history, the online survey recorded answers to questions based on a modified von Willebrand Disease (VWD) screening questionnaire. To characterize a collection of participant's common human traits, the survey recorded answers to questions about height, weight, presence of skin tags, history of acne, eye color, hair color, hair line characteristics, skin sunburn sensitivity, skin tanning ability, natural skin color, freckling, cheek dimpling, earlobe shape, shoe size, foot arch characteristics, hand fifth digit morphology, history of dyslexia, history of migraine headaches, history of seasonal allergies, history of apthous ulcers, tendency to sneeze while walking into a bright sunny place, history of dental caries, need for corrective eye lenses, handedness and like or dislike of strongly flavored foods. Biochemical phenotyping: Assays for plasma Von Willebrand Factor (VWF) antigen were performed using ELISA and "Alphalisa" techniques. Automated complete blood count analysis was performed on a Bayer Advia 120 on all participants (including WBC differential, RBC indices, and platelet count.) For the dbGaP v2 update, new biochemical phenotypes have been submitted and include von Willebrand Factor, von Willebrand Factor propeptide, plasminogen, gamma prime fibrinogen, ADAMTS 13, antithrombin III, protein C, and protein S. All new phenotypes were obtained using "Alphalisa" techniques. Genotyping Details: SNP genotyping was performed using genomic DNA extracted from peripheral blood at the Broad Institute, (MIT/Harvard). Genotyping was performed on the Illumina Omni-1 quad chip at the Broad Institute. For the dbGaP v2 update, genotyping data from the Illumina Human Exome was deposited. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to blood clotting through large-scale genome-wide association studies of siblings. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization was performed by the primary investigators at the University of Michigan, Ann Arbor, and at the GEI-funded GENEVA Coordinating Center at the University of Washington. This study serves as a resource for investigators who are interested in the genetic determinants of specific plasma proteins in a healthy population. The sibling cohort design allows for linkage analysis in addition to association studies. Analysis of thrombosis and hemostasis related traits should help elucidate specific biochemical and genetic networks that maintain hemostasis. We hope to identify specific genetic determinants of VWF levels in order to better understand the factors that influence the development of VWD.

  Study phs000304

• The Environmental Determinants of Diabetes in the Young Study (TEDDY)

  Study Overview The Environmental Determinants of Diabetes in the Young (TEDDY) Study is a longitudinal study that investigates genetic and genetic-environmental interactions, including gestational events, childhood infections, dietary exposures, and other environmental factors after birth, in relation to the development of islet autoimmunity and type 1 diabetes (T1D). A consortium of six clinical centers assembled to participate in the development and implementation of the study to identify environmental triggers for the development of islet autoimmunity and T1D in genetically susceptible individuals. Beginning in 2004, the TEDDY study screened over 400,000 newborns for high-risk HLA-DR, DQ genotypes from both the general population and families already affected by T1D. The TEDDY study enrolled around 8,676 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) in the 15-year prospective follow-up. Participants are followed every three months for islet autoantibody (IA) measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive participants continue to be followed at three month intervals and autoantibody negative participants are followed at six-month intervals. In addition to the analysis of autoantibodies, additional data and sample collection are performed at each visit. Parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. Additional information on the TEDDY study is available in the following articles: Rewers et al., 2008, PMID: 19120261 and Hagopian et al., 2006, PMID: 17130573. Details of the TEDDY protocol can be found in Hagopian et al., 2011, PMID: 21564455. TEDDY data currently available in dbGaP include: gene expression, SNPs, exome, microbiome (gut, nasal, and plasma), RNA sequencing, and whole genome sequencing. For more information on TEDDY Study version history please refer to TEDDY Study dbGaP README File. ImmunoChip SNP DNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for SNP genotyping. Genotyping was performed by the Center for Public Health Genomics at the University of Virginia using the Illumina ImmunoChip SNP array, which contains around 196,000 SNPs from 186 regions associated with 12 autoimmune diseases (Hadley et al., 2015, PMID: 26010309). Data cleaning and validation included the removal of subjects with a low call rate (< 5% SNPs missing) and differences in reported sex and prior genotyping at the TEDDY HLA laboratory. Additionally, SNPs with a low call rate or Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements, were removed from the final dataset (Törn et al., 2015, PMID: 25422107).TEDDY-T1DExome ArrayDNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for genotyping. Genotyping was performed by the University of Virginia using the Illumina TEDDY-T1DExome array. The TEDDY-T1DExome array is a custom chip that contains 550,601 markers from the Infinium CoreExome-24 v1.1 BeadChip and an additional 90,214 tagSNPs specifically selected by the TEDDY investigators based on their associations with nutrients, vitamins, type 2 diabetes, autoimmune diseases, body-mass index, or other exposures and phenotypes measured by TEDDY study.The Illumina GenTrain2 algorithm was used for genotype calling. Sample quality control metrics included sample call rate, heterozygosity rate and concordance of gender between the information reported and genotyped. Gene Expression The TEDDY study collected peripheral blood for the extraction of total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA (200 ng) was further used for cRNA amplification and labeling with biotin using Target Amp cDNA synthesis kit (Epicenter catalog no. TAB1R6924). Labeled cRNA was hybridized to the Illumina HumanHT-12 Expression BeadChips based on the manufacturer's instructions. The HumanHT-12 Expression BeadChip provides coverage for more than 47,000 transcripts and known splice variants across the human transcriptome. Microbiome The TEDDY microbiome study aimed to characterize the longitudinal development of the microbiome, including bacteria, viruses and other microorganisms in the gut, plasma, and nasal cavity of prediabetic and diabetic subjects compared to autoantibody negative non-diabetic subjects. Stool samples used were collected monthly from 3 to 48 months, after which stool samples were collected every 3 months. Nasal swab samples were collected every 3 months starting at 9 months of age until 48 months, after which nasal swabs were collected every 6 months. Plasma samples were collected every 3 months starting at 3 months of age until 48 months, after which plasma samples were collected every 6 months. If the subject was autoantibody positive at 48 months then they remained on the 3 month collection interval for nasal swab and plasma samples. Samples underwent 16s rRNA gene sequencing, DNA and viral RNA metagenomics shotgun sequencing, and sequencing of the internal transcribed spacer (ITS) regions. Additional information on the TEDDY microbiome data is available in the following articles: Vatanen et al., 2018, PMID: 30356183, Stewart et al., 2018, PMID: 30356187, and Vehik et al., 2020, PMID: 31792456. RNA Sequencing The TEDDY study aimed to characterize the transcriptome in subjects with islet autoimmunity and type 1 diabetes compared to matched control subjects. Peripheral blood was collected to extract total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA was then sent to the Broad Institute for the generation of the TEDDY RNA sequencing (RNA-Seq) data. The RNA samples were prepped using Superscript III reverse transcriptase and Illumina's TruSeq Stranded mRNA Sample Prep Kit. The TruSeq libraries were run on the Illumina HiSeq2500 platform. Whole Genome Sequencing The TEDDY study aimed to conduct deep whole genome sequencing and examine the genomic variations in subjects with islet autoimmunity and type 1 diabetes compared to matched autoantibody negative and non-diabetic children. DNA from whole blood was obtained from TEDDY children for whole genome sequencing. The WGS data were generated on the Illumina HiSeq X Ten system.

  Study phs001442

• Use_of_Deep_Sequencing_to_Dectect_Clonal_Mutations_In_Sun_Exposed_Skin_Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Study EGAS00001000515

• Use_of_Deep_Sequencing_to_Dectect_Clonal_Mutations_In_Sun_Exposed_Skin_Epidermis_PART2

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Study EGAS00001000603

• Chinese Alternating Hemiplegia of Childhood (AHC) Disease Study

  AHC is a rare and severe neurological disorder, and characterized by episodic hemiplegia or quadriplegia attacks, accompanied by other paroxysmal symptoms of oculomotor abnormalities, dystonia, seizures and autonomic disturbances; the age of onset usually occurrs before 18 months of life. Sodium-potassium ATPase alpha3 subunit (ATP1A3) has recently been identified as a causal gene for sporadic AHC by three groups. However, there has not been any large genetic study on a Chinese cohort. In the submitted data, whole-exome sequencing of three trios and three sporadic cases in a Chinese cohort produced an average of 18.8 gigabases of raw sequence. Through our analysis pipeline including BWA mapping, GATK recalibration, variant calling and filtering, all six patients contained missense mutations in ATP1A3 which were further confirmed as de novo mutations. Along with validation in additional patients, this study confirmed ATP1A3 as a causal gene in Chinese AHC patients, and reported six novel mutations.

  Study phs000660

• A Genome-wide Association Study (GWAS) of Risk for Osteosarcoma

  This is a genome-wide association study (GWAS) of osteosarcoma, the most common primary bone malignancy. Osteosarcoma typically occurs in adolescents and young adults. It occurs at increased frequency in several inherited cancer predisposition syndromes but the genetic contribution to sporadic osteosarcoma is largely unexplored. The objective of this study was to identify genetic risk factors for osteosarcoma by conducting a genome-wide association study. We developed collaborations with multiple institutions in order to attain the necessary sample size required to discover novel loci in the genome associated with osteosarcoma using the GWAS approach. Genomic DNA (either blood or buccal in source) derived from osteosarcoma cases was obtained from each participating institution or research group. De-identified blood or buccal cell DNA samples from osteosarcoma cases were derived from existing biobanks at the collaborative institutions. Control subjects were derived from existing NCI cohorts and matched by gender and ethnicity.

  Study phs000734

• Vanderbilt Genome-Electronic Records (VGER) Project: QRS Duration

  An important potential enabling resource for Personalized Medicine is the combination of a DNA repository with Electronic Medical Record (EMR) systems sufficiently robust to provide excellence in clinical care and to serve as resources for analysis of disease susceptibility and therapeutic outcomes across patient populations. The Vanderbilt EMR is a state of the art clinical and research tool (that includes >1.7 million records), and is associated with a DNA repository which has been in development for over 3 years; these are the key components of VGER, the Vanderbilt Genome-Electronic Records project, a part of NHGRI's eMERGE network. The VGER model acquires DNA from discarded blood samples collected from routine patient care, and can link these to de-identified data extracted and readily updated from the EMR. The phenotype we analyze here is the QRS duration on the electrocardiogram, since slow conduction (indicated by longer QRS duration) is a marker of arrhythmia susceptibility.

  Study phs000188

• ALLELE Consortium Glioblastoma Project

  Glioblastoma patient samples were sequenced for this project. The purposes of this project are: (1) to establish an umbrella protocol as a mechanism for identifying patients (in the USA and international sites) who agree to the collection, storage, and broad usage of their specimens and ongoing collection, and review of their medical information for the purposes of minimal-risk research and use of such data in clinical trials on which the patient may enroll; (2) to develop operations that facilitate investigator access to the data and/or tissue to conduct research, while minimizing risks to participants and promoting responsible conduct; and (3) to provide the infrastructure for the sharing of de-identified, coded samples, clinical data, and genomic data between participating investigators and institutions. Eligible patients include patients with known or suspected nervous system tumors or other neurologic diseases. Whole exome sequencing from the stated project will be released under this submission.

  Study phs003000

• Direct genetic transformation bypasses tumor-associated DNA methylation alterations

  Tumors represent dynamically evolving populations of mutant cells, and many advances have been made in understanding the biology of their progression. However, key unresolved questions remain about the conditions that support their initial transformation, which cannot be easily captured in patient populations but are instead modeled using transgenic cellular or animal systems. Here, we used extensive patient atlas data to define common features of the tumor DNA methylation landscape as they compare to healthy human cells and used this benchmark to screen 21 engineered human and mouse models for their ability to reproduce these patterns. Notably, we find that genetically induced cellular transformation can trigger global changes in DNA methylation levels that are consistent with extensive proliferation but rarely recapitulate the widespread de novo methylation of Polycomb targets as found in clinical samples. Our results raise pertinent questions about the relationship between genetic and epigenetic aspects of tumorigenesis and provide an important molecular reference for evaluating existing as well as newer tumor models.

  Study EGAS50000000902

• Natural history of clonal haematopoiesis (2017-09-04)

  The incidence of acute myeloid leukemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 60. Only 10-15% of cases evolve from a pre-existing myeloproliferative or myelodysplastic disorder; the remaining cases arise de novo without a detectable prodrome and are diagnosed upon development of bone marrow failure. Analysis of diagnostic blood samples has demonstrated that de novo AML is preceded by the accumulation of somatic mutations in pre-leukemic hematopoietic stem and progenitor cells (preL-HSPCs) that subsequently undergo clonal expansion. If individuals in this pre-leukemic phase could be identified, methods for determination of risk and monitoring for progression to overt AML could be developed. However recurrent AML mutations also accumulate during aging in healthy individuals who never develop AML, referred to as age related clonal hematopoiesis (ARCH). To distinguish individuals with preL-HSPCs at high risk of developing AML from those with ARCH, we undertook deep targeted sequencing of genes recurrently mutated in AML in blood samples from 133 individuals in the European Prospective Investigation into Cancer and Nutrition (EPIC) study taken on average 6 years before they developed AML (pre-AML group), together with 683 matched healthy individuals (Control group). Pre-AML cases displayed accelerated age-correlated accumulation of somatic mutations.The identity, number and variant allele frequency (VAF) of mutations differed between the two groups, and were incorporated into a computational model of AML risk prediction that accurately distinguished pre-AML cases from controls on average 7 years prior to AML development. Our findings provide proof of concept that early prediction of AML development is feasible in high-risk populations, paving the way for early disease detection, monitoring, and potentially prevention.

  Dataset EGAD00001003703

• RNA-seq from human embryonic tissues (additional samples 2018)

  How the genome activates or silences transcriptional programmes governs organ formation. Little is known about this in human post-implantation embryos undermining our ability to benchmark the fidelity of in vitro stem cell differentiation or cell programming, or interpret noncoding variation as potential causes of disease. Here, by studying histone modification we identified genome-wide open chromatin states and active repression across thirteen tissues during human organogenesis. We integrated the data with transcription to build the first view of how promoter states from nearly 20,000 genes differentially regulate alternative organ fates, arguing against bivalency during human organogenesis. The data illustrate tissue-specific as well as complex patterns of enhancer activity functional in zebrafish and impute master transcription factors. Overlaying 739 noncoding de novo mutations in patients allowed phenotypic correlation of developmental disorders to unanticipated target genes. Taken together, the data provide a comprehensive genomic framework for understanding normal and abnormal human development.

  Study EGAS00001003738

• A microRNA-signature that correlates with cognition and is a target against cognitive decline

  While some individuals age without pathological memory impairments, others develop age-associated cognitive diseases. Since changes in cognitive function develop slowly over time in these patients, they are often diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. Thus, there is great need for the identification of inexpensive and minimal invasive approaches that could be used for screening with the aim to to identify individuals at risk for cognitive decline that can then undergo further diagnostics and eventually stratified therapies. In this study we use an integrative approach combining the analysis of human data and mechanistic studies in model systems to identify a circulating 3-microRNA signature that reflect key processes linked to neural homeostasis and informs about cognitive status. We furthermore provide evidence that expression changes of this signature represent multiple mechanisms de-regulated in the aging and diseased brain and are a suitable target for RNA therapeutics.

  Study EGAS00001005627

• Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation

  Raw sequencing files from scRNA-seq dataset used in Schmassmann et al. 2023. Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation. Elife 12 (https://elifesciences.org/articles/92678) Dataset content: 14 samples from 5 donors File type: paired-end fastq files Technology: Illumina sequencing Experimentation used: scRNA-seq using the 10X technology

  Dataset EGAD50000000434

• Head and Neck Organoid Biobank cohort, Issing et. al., 2025, RNA + WES data

  This dataset contains the raw fastq files of RNA and whole exome sequencing of the head and neck organoid biobank. For RNA sequencing, 41 organoid samples collected at different timepoints as well as before and after genetic modification are included. For WES, 25 samples of early organoid cultures or matching tumor tissues are included.

  Dataset EGAD50000001733

• Single-cell CITE-seq and TCR-seq data from AIM⁺ HIV-1-specific T cells

  Single-cell sequencing data from 2 HIV-1 post-intervention controllers and 2 non-controllers reported in Fisher, Garcia, Frattari, Naasz, et al. Longitudinal samples were collected before antiretroviral therapy inititation, during suppressive therapy, and after analytical treatment interruption.

  Dataset EGAD50000002247

• BulkTCR-sequencing data from different human intestinal CD8 T cell subsets.

  5000 cells of each subset of CD8 T cells (CD103-KLRG1+, CD103-KLRG1- and CD103+ from LP and CD103+ IELs) were sorted into tubes. A modified SMART protocol was used in first-strand cDNA synthesis, and TCRalpha / TCRbeta genes were amplified in two rounds of semi-nested PCR reaction, following the method described in detail in Risnes et al., 2018.

  Dataset EGAD00001005049

• Sequencing data for oesophageal / related samples - Kazachenka et al (DNA)

  Data supporting: "The transcriptional landscape of endogenous retroelements delineates esophageal adenocarcinoma subtypes" WGS for 452 samples

  Dataset EGAD00001011095

• RNA-seq transcriptome of bronchial brush samples from COPD and control

  Human subjects (COPD patients or apparently healthy controls) where investigated by bronchoscopy and a 5 mm brush was used to sample the subsegment airways of the right lung. The material obtained mainly consist of bronchial epithelial cells plus some contamination with leukocytes. For further details see Ziegler-Heitbrock et al, European Respiratory Journal, 40:823-829, 2012.

  Dataset EGAD00001002003

• Genotype data

  This dataset contains the imputed genotypes for 197 individuals. All individuals were genotyped with the Illumina HumanCoreExome-24 array. The individuals were phased with SHAPEIT and imputed to the 1000 Genomes Project Phase III using IMPUTE2. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity

  Dataset EGAD00001005038

• Privacy Notice for the Account User

  Privacy Notice for EGA User Account This Privacy Notice explains what personal data is collected by the specific service you are requesting, for what purposes, how it is processed, and how we keep it secure. Note that this service collects personal data directly provided by the user, and also collects personal data from users that is provided by other organisations. 1. Who controls your personal data and how to contact us? European Genome- Phenome Archive - EGA offers a service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects, jointly managed by European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI) and Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG). EMBL-EBI and CRG represent joint Data Controllers’ of processing of your personal data. They and their Data protection officers may be contacted for data protection queries and for exercising your rights under Section 8. You may contact EMBL-EBI, represented by dr. Thomas Keane, by: email at: tk2@ebi.ac.uk or post at EMBL-EBI, Wellcome Genome Campus, CB10 1SD Hinxton, Cambridgeshire, UK. EMBL’s Data Protection Officer may be contacted by: telephone at +49 6221 387-8590, email at dpo@embl.org, or post at EMBL Heidelberg, Data protection officer, Meyerhofstraße 1, 69117 Heidelberg, Germany. You may contact CRG, whose EGA team is represented by dr. Jordi Rambla de Argila, by: email at jordi.rambla@crg.eu, or post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), Dr.Aiguader 88, PRBB Building, 08003 Barcelona, Spain. CRG Data protection officer may be contacted by: email at dpo@crg.eu post at Fundació Centre de Regulació Genòmica - Centre for Genomic Regulation (CRG), C/ Dr. Aiguader, 88, PRBB Building, 08003 Barcelona, Spain. 2. Which is the lawful basis for processing personal data? We process your personal data on the grounds of important public interest. For monitoring your activities on the website, we process your personal data on the grounds of important public interest. Such legal basis is found in Article 5(1)(a) of EMBL Internal Policy No 68 on General Data Protection (hereinafter IP 68), which is equivalent to Article 6 (1)(e) of the EU General Data Protection Regulation (hereinafter GDPR) and upon which personal data are processed for the achievement of the aims laid down in 1973 agreement establishing EMBL, such as the promotion of the cooperation in the fundamental research, in the development of advanced instrumentation and in advanced teaching in molecular biology and dissemination of information. 3. What personal data is collected from users of the service? How do we use this personal data? We collect the following personal data from you: Name Email address Title/Position Organisation Organisational affiliation Username and password (to authenticate access to the system) IP Address (for anonymous usage statistics) We process your personal data: to provide you with the authenticated access to the EGA service (opening and managing submission and distribution account), to publicly publish some aggregate data to facilitate scientific research (e.g. number of accounts, geographic distribution), to better understand the needs of the users and to guide future improvements of the service, to create anonymous usage statistics. If you do not provide us with your personal data we will not be able to open the user account and offer you our services or we will only provide you a subset of functionalities available within the service. 4. Who will have access to your personal data? The personal data will be disclosed to: Authorised staff in the data controller’s institutions acting on data controller`s behalf and instructions (for all user account data), Requested dataset Data access committee – DAC will have access to the name, email, organization, affiliation, title/position of the distribution user account, using it for their own purpose of granting access to their datasets. 5. Will your personal data be transferred to third countries (i.e. countries not part of EU/EEA) and/or international organisations? Distribution user account data are in the process of granting access disclosed to dataset(s) DAC, which might be a recipient in countries outside of the European Economic Area. Insofar as the second joint controller may be subject to GDPR, data transfer to and from the first joint controller (EMBL-EBI) is necessary for important reasons of public interest embedded in the aims of the EMBL and justified in the Article 9(4) of IP 68 (equivalent to Article 49(1)(d) of GDPR) read in conjunction with EMBL`s 1973 establishing agreement and Article 179(2) of the Treaty on the Functioning of the European Union. 6. How long do we keep your personal data? All data are stored for as long as you have the account open. Thereafter the storage is prolonged for as long as our service is live, even if you stop using our services. This prolongation is necessary for further scientific research, to ensure legal compliance and security and to facilitate internal and external audits it they arise. By contrast, the log files for the data categories related to anonymous usage statistics (raw web service logs) are processed only for 30 days and thereafter erased. 7. The joint Data Controllers provide these rights regarding your personal data You have the right to: Not be subject to decisions based solely on an automated processing of data (i.e. without human intervention) without you having your views taken into consideration. Request at reasonable intervals and without excessive delay or expense, information about the personal data processed about you. Under your request we will inform you in writing about, for example, the origin of the personal data or the preservation period. Request information to understand data processing activities when the results of these activities are applied to you. It must be clarified that rights under points 4 and 5 are only available whenever you need support whilst using our website. For other processing based on the grounds of important public interest you cannot exercise your rights to object, rectify or erase your personal data according to the Article 13(2)(a)(b) of IP 68 (equivalent to Article 17(3)(b)(d) and Article 21(6) of the GDPR). 8. Supervisory authority If you wish to complain against the processing of your personal data, you may do so by post at: EMBL Heidelberg, Data Protection Committee, Meyerhofstraße 1, 69117 Heidelberg, Germany, or Autoritat Catalana de Protecció de Dades (Catalan Data Protection Authority), C/Rosselló 214, Esc A, 1r 1a, Barcelona 08008, Spain. Published at: February 6, 2019

  Documentation data-protection/privacy-notice/ega-user-account

• Replication data for RNA-SEQUENCING: A RELIABLE TOOL TO UNVEIL TRANSCRIPTIONAL LANDSCAPE OF PAEDIATRIC B-OTHER ACUTE LYMPHOBLASTIC LEUKAEMIA

  This dataset contains the raw data of the RNA-seq experiments described in the paper "RNA-Sequencing: a reliable tool to unveil transcriptional landscape of pediatric B-other acute lymphoblastic leukemia" It contains the raw data from 60 pediatric patients diagnosed with B cell progenitor acute lymphoblastic leukemia lacking the main genetic alterations. RNA material was extracted from bone marrow or periphereal blood and RNA libraries were prepared using Illumina® TruSeq™ stranded mRNA kit following manufacturer's instructions and were sequenced in a NextSeq 550 using a v2 HighOutput 150 cycle kit 2x75bp. Funding: Instituto de Salud Carlos III (ISCIII), PI21/00213 

  Dataset EGAD50000000981

• Unravelling the contribution of HIF pathway and its therapeutic potential in human AML leukemia-initiating cells

  We performed single cell RNA sequencing (scRNA-seq) from bone marrow on 11 pediatric (0-14 years-old) and adolescent and young adult (AYA) (15-39 years-old) de novo AML samples (Dx) (4 inv(16), 3 t(8;21) and 4 rMLL). In addition, for some patients also relapse sample was sequenced (2 inv(16), 2 t(8;21) and 3 rMLL). Cells were sorted into CD34+/CD38- and CD34-/CD38+ and sequenced separately.

  Dataset EGAD00001008514

• HV31 - Read identifier list for local CCS, CLR, ONT and MGI reads

  This file contains read identifiers for local CCS, CLR, ONT and MGI reads for each of the eight selected genomic regions (HLA, KIR, IGH, IGK, IGL, TRA, TRD, andTRG). We extracted these reads by aligning whole-genome sequencing data to a draft whole-genome de novo assembly, and selecting reads that map to contigs representing each region. These reads were involved in the polishing and validation of the HV31 assembly. Please refer to the relevant manuscript (https://doi.org/10.1101/2021.02.03.429586) for additional details. Read identifiers are stored in JSON format. Along with the full FASTQ files, this file enables convenient re-analysis of the HV31 sequencing data in the eight selected regions.

  Dataset EGAD00001007761

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002698

• SC_DDD-G-3

  Unfiltered genotype data for DDD Study trios (patient and parents) (N=2,166 samples), some of which were used for replication of neurodevelopmental disorder polygenic risk (Niemi et al., Nature 2018). Samples were genotyped on the Illumina HumanOmniExpress BeadChip

  Dataset EGAD00010001602

• Breast Cancer Histology Images

  Fresh frozen breast cancer H&E tissue images collected and annotated by the International Cancer Genome Consortium (ICGC), that included the BASIS collaboration. Associated with whole genome sequence data as originally described by Nik-Zainal et al, Nature, 2016 (DOI: 10.1038/nature17676) and deposited with ID EGAS00001001178

  Dataset EGAD00010001911

• RNA-seq dataset

  RNA-seq data from CD20+ sorted cells obtained from peripheral blood and lymph node Follicular Lymphoma patients. These samples were unstimulated after thawing and additionally, peripheral blood samples were stimulated during 7 days in culture as described in Dobaño-López C et al. Stranded RNA-seq libraries were performed using the TruSeq library kit (Illumina, San Diego, CA, USA). Libraries were sequenced on a NextSeq 2000 (Illumina) in a 2x50bp length.

  Dataset EGAD50000000347

• scKaryoSeq of CRISPR-Cas9 edited primary human T cells

  To explore T cell-intrinsic driving forces of CRISPR-induced aneuploidy at the TRAC gene locus, we performed scKaryo-seq (Bolhaqueiro et al., Nature Genetics 2019). We compared the impact of the small molecule pifithrin-alpha in activated TRAC KO T cells. In a separate experiment, we determined the effect of pifithrin-alpha on non-activated T cells edited at the TRAC locus or treated with non-targeting Cas9 RNPs.

  Dataset EGAD50000000929

• Shallow whole genome sequencing DETECT samples

  Shallow whole genome sequencing of samples from the paper Beddowes et al. A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival. Mol. One 2025. This includes 1048 longitudinal plasma samples from 149 patients and 35 normals. Samples were sequenced with shallow whole genome sequencing for copy number estimation. All the files are single-end fastq files.

  Dataset EGAD50000001333

• Sequence data for "An allele-resolved nanopore-guided tour of the human placental methylome" (Kindlova et al 2025)

  Sequence data generated for the study "An allele-resolved nanopore-guided tour of the human placental methylome" includes Illumina WGS, Illumina RNA-seq, Illumina EM-seq, and Oxford Nanopore Technologies PromethION sequence data.

  Dataset EGAD50000001850

• TenK10K Phase 1: Whole Genome Sequencing tandem repeats multi-sample VCFs

  Tandem repeat variants were called for 1,925 samples from phase 1 of the TenK10K project. Variant calling from WGS alignments to the GRCh38 reference assembly was completed with ExpansionHunter v5. This dataset is comprised of autosomal tandem repeat variants provided as multisample compressed VCF format files. SNV-derived principal component scores used in the manuscript (Tanudisastro et al.) are also provided in this dataset.

  Dataset EGAD50000002378

• WTS data from PASS-01 trial

  WTS data for pancreatic cancer samples (PASS-01 Trial; Knox et al., Journal of Clinical Oncology, 2025).  The dataset includes tumour bam files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=115 tumours)

  Dataset EGAD50000002308

• WGS data from PASS-01 trial

  WGS data for pancreatic cancer samples (PASS-01 Trial; Knox et al., Journal of Clinical Oncology, 2025).  The dataset includes tumour and normal cram files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=127 tumour/normal pairs)

  Dataset EGAD50000002309

• Assessment of cannabidiol and Δ9-tetrahydrocannabiol in mouse models of medulloblastoma

  These data were used in the following publication: Andradas, C.; Byrne, J.; Kuchibhotla, M.; Ancliffe, M.; Jones, A.C.; Carline, B.; Hii, H.; Truong, A.; Storer, L.C.D.; Ritzmann, T.A.; et al. Assessment of Cannabidiol and delta9-Tetrahydrocannabiol in Mouse Models of Medulloblastoma and Ependymoma. Cancers 2021, 13, 330. https://doi.org/10.3390/cancers13020330 There are 4 paired-end RNA-seq samples from paediatric brain cancer cell lines.

  Dataset EGAD00001006923

• Whole genome sequencing of 40 rainforest hunter-gatherers and neighbouring farmers from Central Africa

  Exome sequencing of 20 rainforest hunter-gatherers (RHG) and 20 neighbouring farmers (AGR) from western central Africa was performed using 101-bp paired-end reads on Illumina HiSeq 2000. All individuals presented very low rates of missing values ranging from 0.5% to 4%, and a mean depth of coverage of 6.5× (ranging from 4× to 13×)(Lopez et al., Curr Biol 2019).

  Dataset EGAD00001005139

• Bajau and Saluan adaptation study data

  This dataset includes whole genome sequencing data from 93 Bajau and Saluan individuals that were used in the Ilardo et al 2018 study on adaptation to diving in Sea Nomads. Sequencing libraries were built using the TruSeq Nano DNA Library Preparation Kit on an Illumina NeoPrep instrument. Each pool was sequenced 125 Paired-End over one or two lanes on the Illumina HiSeq2500 (version 4 chemistry). Samples were sequenced to an average depth of 5x.

  Dataset EGAD00001004207

• Chromatin 3D interactions mediate genetic effects on gene expression (ChIP-seq)

  ChIP-seq data for Lymphoblastoid Cell Lines (LCL) and Fibroblasts (FIB) from the Gencord Cohort: - 160 LCLs assayed for H3K27ac, H3K4me1 and H3K4me3, - 78 FIB assayed for H3K4me3 and 79 FIB assayed for H3K27ac and H3K4me1 This dataset was generated as part of the following study: Delaneau et al (2019). Chromatin 3D interactions mediate genetic effects on gene expression.

  Dataset EGAD00001004871