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• Small RNA sequencing dataset from human prefrontal cortex tissue - ALS vs CTR

  For mature miRNAs and hairpins, BAM and FASTq files

  Dataset EGAD50000000468

• TOAPR-B patient cell-free DNA WGS and WES

  Sequencing files for TOPARP-B patients as described in manuscript

  Dataset EGAD50000000407

• RNAseq RPKM

  RNA-seq data from ILC samples. This dataset includes counts normalized for sequencing depth and gene length.

  Dataset EGAD50000000828

• Centre Leon Berard - DAC - seq data Neuroendocrine tumors - B Gibert

  Review committee for the neuroendocrine tumor genetic data set uploaded by Benjamin GIBERT (CRCL), Anthony FERRARI (CLB) and Thomas WALTER (HCL)

  Dac EGAC50000000218

• DAC for "Capturing disease severity in LIS1-lissencephaly reveals proteostasis dysregulation in patient-derived forebrain organoids" with Julia Ladewig(Julia.ladewig@zi-mannheim.de), Moritz Mall(m.mall@dkfz-heidelberg.de), and Matteo Gasparotto(matteo.gasparotto@zi-mannheim.de)

  Dac EGAC00001003588

• Walter and Eliza Hall - Aix-Marseille Université

  Data Access Committee for the Liao et al. 2025 study, D4Z4End2End: complete genetic and epigenetic architecture of D4Z4 macrosatellites in FSHD, BAMS and reference cohorts.

  Dac EGAC50000000655

• Division of Cancer Evolution National Cancer Center Research Institute Data Access Committee

  Data Access Committee for data from Division of Cancer Evolution, National Cancer Center Research Institute

  Dac EGAC50000000737

• MD Anderson OPMD DAC

  Datasets and agreement used for the OPMD dataset access of the publication Reconstructing oral cavity tumor evolution through brush biopsy, Springer Nature, DOI: 10.1038/s41598-024-72946-3

  Dac EGAC50000000384

• scWGS PDX

  Single cell WGS (low pass) for PT1-derived PDX samples

  Dataset EGAD00001006137

• scRNA primaries

  Single cell RNA-seq for primary samples

  Dataset EGAD00001006135

• Fecal 16S HV metadata

  Metadata for fecal 16S-V4 rRNA gene sequence data from NCT02749630 healthy volunteers.

  Dataset EGAD00001008821

• Uncovering tumor intrinsic and extrinsic factors that regulate hepatocellular carcinoma growth using patient derived xenograft assays

  Exome Sequencing and RNA Sequencing Data for PDX Samples

  Dataset EGAD00001005734

• Treatment arm information and sample sheet

  Table of treatment arm information for the 418 RNAseq evaluable population.

  Dataset EGAD00001009502

• Reference epigenome OB56_N_PreA_smRNA-Seq data generated from KEP study

  A OB56_N_PreA_smRNA-Seq single end data for Preadipocytes(fat)

  Dataset EGAD00001003495

• Reference epigenome IPS02_N_NPC_WGBS data generated from KEP study

  A IPS02_N_NPC_WGBS paired end data for Neural progenitor cells(Nestin)

  Dataset EGAD00001003474

• Reference epigenome IPS03_N_ENeuron_WGBS data generated from KEP study

  A IPS03_N_ENeuron_WGBS paired end data for Early neuron cells(Tuj1)

  Dataset EGAD00001003475

• Reference epigenome OB57_D_PreA_mRNA-Seq data generated from KEP study

  A OB57_D_PreA_mRNA-Seq paired end data for Preadipocyte(fat)

  Dataset EGAD00001003487

• Reference epigenome CKD25_C_Podo_smRNA-Seq data generated from KEP study

  A CKD25_C_Podo_smRNA-Seq single end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003499

• Reference epigenome CKD25_C_Podo_mRNA-Seq data generated from KEP study

  A CKD25_C_Podo_mRNA-Seq paired end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003483

• RNA sequencing data to study "A biobank of patient-derived pediatric braintumor models"

  RNA sequencing data for the PDOX model EPD-613FH

  Dataset EGAD00001003573

• Reference epigenome CKD24_C_Podo_mRNA-Seq data generated from KEP study

  A CKD24_C_Podo_mRNA-Seq paired end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003482

• Illumina HiSeq 2000

  Three files of patients 20, 23 and 25 with WGS done on Illumina HiSeq 2000. For research purpose and authorised user only.

  Dataset EGAD00001003438

• Reference epigenome OB57_D_PreA_smRNA-Seq data generated from KEP study

  A OB57_D_PreA_smRNA-Seq single end data for Preadipocyte(fat)

  Dataset EGAD00001003496

• RNA-Seq Pair End

  RNA analysis of two patients 11 and 15 with WGS done on Illumina HiSeq2000. For research purpose and authorised user only.

  Dataset EGAD00001003429

• Reference epigenome CKD24_C_Podo_smRNA-Seq data generated from KEP study

  A CKD24_C_Podo_smRNA-Seq single end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003498

• V2 Colorectal panel test

  Targeted gene screen of cell line tumour samples for testing the new V2 Colorectal gene panel.

  Dataset EGAD00001003253

• ATAC-seq for placental and buffycoat cells.

  We performed ATAC-seq experiments using 2 placental samples and 2 buffycoat samples.

  Dataset EGAD00001004291

• ChIP-Seq files for RMS.

  ChIP-Seq files accompanying the paper titled "Identification of Therapeutic Targets in Rhabdomyosarcoma Through Integrated Genomic, Epigenomic, and Proteomic Analyses".

  Dataset EGAD00001004312

• H3Africa SIREN Phenotype

  Phenotype data for 3421 Samples from Nigeria and Ghana, sequenced with the Illumina NestSeq 500.

  Dataset EGAD00001011075

• Res1_PC9_exp2_MC_01.04.22

  8 cell pellet samples for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Dataset EGAD00001012233

• Res1_PC9_exp1_MC_29.03.22

  8 cell pellet samples for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Dataset EGAD00001012232

• Whole Exome Sequencing of DNA from Pre-and Post-Chemotherapy Needle Biopsies of Triple Negative and Inflammatory Breast Cancers Enrolled in the S0800 Trial

  Purpose: The purpose of this study was to assess the somatic mutation landscape of breast tumors before and after neoadjuvant chemotherapy. The data includes whole exome sequencing of pre- and post- tissues that were collected in the context of an already published clinical trial SWOG S0800 (ZA Nahleh et al. Breast Cancer Research and Treatment. 158:485-495, 2016). The trial compared the efficacy of sequential nab-paclitaxel followed or preceded by doxorubicin/cyclophosphamide anthracycline chemotherapy with or without bevacizumab as preoperative therapy for stage II-III breast cancer. Experimental Design: 29 pre-treatment biopsies and 9 matching post-treatment surgically resected cancer tissues were available for analysis and were subjected to whole exome sequencing to identify mutational patterns associated with response to neoadjuvant chemotherapy. The 9 paired samples with residual invasive cancer after therapy were also analyzed to assess changes in mutational patterns in response to therapy. No matching normal tissues were available for germline sequencing and therefore we used n=7 post-treatment breast tissues without residual cancer (i.e. complete eradication of cancer by therapy) as a normal cohort to facilitate somatic variant calling.Conclusion: These results suggest that genomic disturbances in BRCA-related DNA repair mechanisms, reflected by a dominant mutational signature 3, confer increased chemotherapy sensitivity. Cancers that survive neoadjuvant chemotherapy, frequently have alterations in cell cycle regulating genes but different genes are affected in different patients.

  Study phs001883

• LCLF1.0 Data

  In this study, we investigated ad libitum food intake of 20 healthy adult volunteers who each completed a 4-week stay at the National Institutes of Health (NIH). During their stay, they consumed a low-carbohydrate, high-fat (LCHF) diet and a low-fat, high-carbohydrate (LFHC) diet for 2 weeks each, in random order. We collected information about energy intake and metabolic changes in response to the two test diets. The test diets were presented to subjects in amounts exceeding their daily energy requirements, and subjects were instructed to eat as much or as little of each diet as desired. This study implemented 7-day rotating menus for each test diet. The diets were matched for presented calories and protein, but the LCHF diet was low in carbohydrate (~10% of calories) and high in fat (~75% of calories) whereas the LFHC diet was high in carbohydrates (~75% of calories) and low in fat (~10% of calories). The two test diets had a common foundation of vegetables with low amounts of digestible carbohydrates such as lettuce, spinach, kale, cabbage, cauliflower, zucchini, tomato, asparagus, broccoli, peppers, brussels sprouts, and green beans. The LCHF diet included meat, poultry, fish, eggs, dairy, and nuts. The LFHC diet included legumes, rice, root vegetables, soy products, corn, lentils, peas, whole grains, bread, and fruit. The test diets were designed using a standard computerized nutrition database, and blood samples were collected from the subjects.

  Study phs003187

• Single cell transcriptomics in expanded Tregs of APS-1 patients

  Aim of study: Exploring single cell transcriptomics in expanded Tregs of with autoimmune polyendocrine syndrome type 1 (APS-1) patients (global gene expression, immune panel, TCR). N= 9 APS-1 patients and 9 healthy controls Protocol 1. Regulatory T cells (Tregs) were isolated from EDTA-blood, activated with anti-CD3/CD28 and IL2, expanded in cell culture for 14 days and stored at -150℃ in AB serum or FBS + 5% DMSO until use. 2. Cells were thawed, run through a Live/Dead column and carefully counted. 10000 Tregs were used as input for the 10x protocol. 3. cDNA was generated and amplified using Single Cell VDJ 5’ Gel Beads, Chromium Next GEM Chip K Single cell Kit, Next GEM Single Cell 5’ GEM Kit v2 and 5’ Feature Barcode Kit (all from 10x genomics). 4. Gene expression (GEX) libraries were generated by using the Library Construction Kit from 10x genomics. 5. T-cell receptor (TCR) libraries were generated using the Single Cell Human TCR Amplification Kit and the Library Construction Kit from 10x genomics. 6. 10x Genomics Target Hybridization Kit and Human Immunology Panel was used with GEX libraries. Only 8 patient samples and 8 control samples were used for the immune panel. 7. All libraries have a unique sample index (Dual Index TT Set A). 8. All samples were sequenced on Illumina NovaSeq 6000 on a NovaSeq S2 flow cell.

  Study EGAS50000000181

• Spatio-temporal Profiling of a Rhabdoid Tumor Case Study

  Background Immune checkpoint inhibition (ICI) has revolutionized oncology, offering extended survival and long-term remission in previously incurable cancers. While highly effective in tumors with high mutational burden, lowly mutated cancers, including pediatric malignancies, present low response rate and limited predictive biomarkers. Patients and methods We present a framework for the identification and validation of tumor-reactive T cells as a biomarker to quantify ICI efficacy and as candidates for a personalized TCR-T cell therapy. Therefore, we profiled a pediatric malignant rhabdoid tumor patient with complete remission after ICI therapy using deep single-cell T cell receptor (TCR) repertoire sequencing of the tumor microenvironment (TME) and the peripheral blood. Results Tracking T cell dynamics longitudinally from the tumor to cells in circulation over a time course of 12 months revealed a systemic response and durable clonal expansion of tumor-resident and ICI-induced TCR clonotypes. We functionally validated tumor reactivity of TCRs identified from the TME and the blood by co-culturing patient-derived tumor cells with TCR-engineered autologous T cells. Here, we observed unexpectedly high frequencies of tumor-reactive TCR clonotypes in the TME and confirmed T cell dynamics in the blood post-ICI to predict tumor-reactivity. Conclusion These findings strongly support spatio-temporal tracking of T cell activity in response to ICI to inform therapy efficacy and to serve as a source of tumor-reactive TCRs for personalized TCR-T designs.

  Study EGAS00001008174

• UK10K COHORT TWINSUK

  The UK10K project proposes a series of complementary genetic approaches to find new low-frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome-wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein-coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will directly analyse quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The TwinsUK samples will be part of the cohort study and will undergo whole genome sequencing. For further information with regard to this cohort please contact Brent Richards (brent.richards@kcl.ac.uk) or Nicole Soranzo (ns6@sanger.ac.uk).

  Study EGAS00001000108

• Long-read trio sequencing of unsolved patients with intellectual disability

  Long-read sequencing (LRS) has the potential to comprehensively identify all medically-relevant genome variation, including variation commonly missed by short read sequencing (SRS) approaches. To determine this potential, we performed LRS up to 40x coverage using the Pacific Biosciences Sequel instrument for 5 patient-parent trios with intellectual disability, whose aetiology remained unresolved after SRS exomes and genomes. A first systematic assessment of LRS coverage showed that ~35Mb of the genome was only accessible by LRS and not SRS. Structural variant (SV) calling yielded on average 28,292 SV calls per individual, totalling 12.9 MB of sequence. Trio-based analyses showed concordance for up to 95% of these SV calls across the genome, and 80% of the LRS SV calls were not identified by SRS. De novo mutation analysis did not identify any de novo SVs, confirming these are rare events. Because of high sequence coverage, we were also able to call single nucleotide substitutions. On average, we identified 3 million substitutions per genome, with a Mendelian inheritance concordance of up to 97%. Of these, approximately 100,000 were located in the ~35Mb of the genome that was only captured by LRS. Moreover, these variants affected the coding sequence of 64 genes, including 32 known to cause Mendelian disorders. Although no clinical diagnoses were made in these 5 patients, our data show the potential added value of LRS compared to SRS for identifying medically relevant genome variation.

  Study EGAS00001004319

• Disease and phenotype relevant genetic variants identified from histone acetylomes in human hearts

  Identifying genetic markers for heterogeneous complex diseases such as heart failure has been challenging, and may require prohibitively large cohort sizes in genome-wide association studies (GWAS) in order to demonstrate statistical significance1. On the other hand, chromatin quantitative trait loci (QTL), elucidated by direct epigenetic profiling of specific human tissues, may contribute towards prioritising variants for disease-association. Here, we captured non-coding genetic variants by performing enhancer H3K27ac ChIP-seq in 70 human control and end-stage failing hearts, mapping out a comprehensive catalogue of 47,321 putative human heart enhancers. 3,897 differential acetylation peaks (FDR < 0.05) pointed to recognizable pathways altered in heart failure (HF). To identify cardiac histone acetylation QTLs (haQTLs), we regressed out confounding factors including HF disease status, and employed the G-SCI test2 to call out 1,680 haQTLs (FDR < 0.1). A subset of these showed significant association to gene expression, either in cis (180), or through long range interactions (81), identified by Hi-C and Hi-ChIP performed on a subset of hearts. Furthermore, a concordant relationship was found between the gain or disruption of specific transcription factor (TF) binding motifs, inferred from alternative alleles at the haQTLs, associated with altered H3K27ac peak heights. Finally, colocalisation of our haQTLs with heart-related GWAS datasets allowed us to identify 62 unique loci. Disease-association for these new loci may indeed be mediated through modification of H3K27-acetylation enrichment and their corresponding gene expression differences.

  Study EGAS00001003586

• GR@ACE_StageI.v01

  Binary Plink files for pre-GWAS quality control in 7409 samples genotyped using Axiom 815K Spanish Biobank array (Thermo Fisher)

  Dataset EGAD00010001654

• GR@ACE_StageI.CEL_files

  Intensity calculation on the pixel values of the DAT file for 7409 samples genotyped using Axiom 815K Spanish Biobank array (Thermo Fisher)

  Dataset EGAD00010001655

• CML_CP_MBC_LBC_Illumina_ Beadchip_HT12v4_All_Samples_Gene_Expression.xlsx

  Expression dataset for CD34 sorted primary CML bone marrow samples

  Dataset EGAD00010002209

• The ERASMUSMC-HEMA Data Access Committee controlling appeals for 3q26-rearranged acute myeloid leukemia datasets from the department of Hematology at Erasmus MC

  Dac EGAC00001000162

• PBMC all cell metadata

  Cell annotation for single cells of PBMC collected from 113 patients, including UMAP coordinates and annotation.

  Dataset EGAD50000000145

• TUM Experimental Neuroimmunology

  This DAC will decide about all data requests to human data deposited at EGA that was primarily produced at the Institute for Experimental Neuroimmunology at the Technical University Munich, Germany.

  Dac EGAC50000000093

• Genetic Mechanisms of Disease Lab DAC

  Data access for raw and processed H3K27ac ChIP-seq and ATAC-seq data from "Effect of ETS2 modulation on chromatin accessibility and enhancer activity in human macrophages".

  Dac EGAC50000000087

• BROCA cancer panel sequencing for 15 samples

  BROCA panel sequencing using the BROCA-HR v8 and BROCA-GO v1 versions of the gene panel

  Dataset EGAD50000000035

• bfast CohortD clinical data

  Clinical data for BFAST Cohort D, including time-to-event, tumor response, and baseline prognostics data.

  Dataset EGAD50000000149

• Amsterdam UMC Head and Neck Cancer Biology and Immunology

  This data access committee oversees data and assesses requests for the Head and Neck Cancer Biology and Immunology lab of Amsterdam UMC, location VUmc.

  Dac EGAC50000000350

• RCC trial WES dataset

  This dataset includes WES data for 116 runs, corresponding to 58 pairs of normal(PBMC)/tumor samples from 58 patients (116 BAM files).

  Dataset EGAD50000000953

• H3Africa KDRN Phenotype

  The phenotypic data for 6431 samples of the KDRN Study from Ghana and Nigeria.

  Dataset EGAD00001009333