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• Epigentic sequence data of monocytes and macrophages

  Data for paper: Epigenetic dynamics of monocyte to macrophage differentiation with Chip Seq, NOMe, mRNA, total RNA, noncoding RNA, whole genome bisulfite seq,

  Dataset EGAD00001002201

• TRACERx pilot study, phase 2

  Multi-region Illumina whole-exome and/or whole-genome sequencing on tumor regions collected from early-stage NSCLC patients who underwent definitive surgical resection prior to receiving adjuvant therapy.Patients covered by this dataset: L012, L013, L015, L017

  Dataset EGAD00001001918

• Deep-Seq: Resistance to anti-EGFR therapy in colorectal cancer

  In this study we performed ultra deep sequencing of genes associated with anti-EGFR resistance, such as KRAS, BRAF, PIK3CA, and EGFR in 17 plasma-DNA samples from a total of 10 patients treated with anti-EGFR therapy.

  Dataset EGAD00001000688

• Primary plasma cell leukemia genomic abnormalities

  Primary plasma cell leukemia (pPCL) samples were sequenced using the Nimblegen MedExome Plus hybridization capture to detect translocations, copy number changes, and mutations in 20 pPCL samples and patient matched controls. Sequencing was performed on a NextSeq500 using 75 bp paired end reads.

  Dataset EGAD00001004323

• ICGC-LIRI-JP Release 15

  RIKEN collection WGS reads for 321 HCC and blood matched samples from 158 donors submitted to ICGC for release 15

  Dataset EGAD00001000808

• IBDCA_Edinburgh

  In this experiment we have sequenced tumour normal pairs from patients presenting with CRC who have a prior history of inflammatory bowel disease. The idea is to identify driver mutations, new genes and novel pathways associated with the development of these malignancies.

  Dataset EGAD00001001330

• Metastatic Breast Cancer Whole Genome

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

  Dataset EGAD00001000899

• Human Evolution 3

  The mtDNA and Y chromosome of up to 15 Australian Aborigines, concentrating on individuals with indigenous lineages, will be sequenced using the standard whole-genome sequencing followed by filtering out of autosomal and X sequences, so that only mtDNA and the Y chromosome will be analysed and released.

  Dataset EGAD00001001373

• Sequencing-based counting and size profiling of plasma Epstein-Barr virus DNA enhance population screening of nasopharyngeal carcinoma.

  We used targeted sequencing to capture and measure the abundance as well as the size profiles of EBV DNA in plasma of subjects with and without NPC

  Dataset EGAD00001004204

• Genomic alteration in Korean Young Age Diffuse Gastric Cancers

  To identify recurrent somatic alterations in this unique subset of gastric cancers, whole exome and SNP6 analyses were performed using frozen cancer tissue. The somatic mutation analyses were also performed using blood of the same patients.

  Dataset EGAD00001001984

• Benchmarking CRISPR Whole-genome Drop-out Screen - B&S (2019-08-07)

  This study is a benchmarking exercise to explore potential source of variation between different CRISPR drop out libraries. . This dataset contains all the data available for this study on 2019-08-07.

  Dataset EGAD00001005233

• Familial adult myoclonic epilepsy type 1 in Sri Lankan and Indian families

  Whole genome sequencing data from four affected and one unaffected individuals from two families with familial adult myoclonic epilepsy, one of Sri Lankan origin and one of Indian origin. BAM files aligned to hg19 reference genome.

  Dataset EGAD00001005777

• COVID-19 Postmortem Lung snRNA-seq

  A deeper understanding of the pathological mechanisms of SARS-CoV-2 infection is required to combat COVID-19. Through this dataset, we analyze postmortem lung cells from patients that are infected/uninfected with SARS-CoV-2 with snRNA-seq.

  Dataset EGAD00001006584

• HV31 - PacBio long-read circular consensus (CCS) senquencing

  PacBio long-read circular consensus (CCS) sequencing data for individual HV31 generated on PacBio Sequel II instrument, using size-selected (10-15 kb) DNA from CD14+ monocytes, to a sequencing depth of ~12×. Sequencing was performed at the Wellcome Sanger Institute.

  Dataset EGAD00001006979

• Genome-Wide Association Study of Anorexia Nervosa (Price Foundation, Klarman Family Foundation, Center for Applied Genomics at the Children's Hospital of Philadelphia, Scripps Translational Sciences Institute Clinical Translational Science Award)

  Twin studies are consistent with substantial heritability in anorexia nervosa (AN), although detecting and confirming individual risk alleles has been difficult, due to small effects of single alleles and limited samples in prior studies. Methods: 1105 AN DNA samples obtained in a multisite study and 3733 pediatric patients of normal body weight were genotyped using the Illumina 610Q chip at The Center for Applied Genomics at The Children's Hospital of Philadelphia. Cases and controls were of European ancestry. Single nucleotide polymorphism (SNP) genotypes were subjected to quality control procedures, including elimination of SNPs with: call rates < 95%, minor allele frequency < 5%, and if Hardy-Weinberg equilibrium testing yielded p < 0.0001. Samples were removed if not of European ancestry or if showing cryptic relatedness. Eight AN DNA samples were deleted for low call rate, and 51 AN samples were deleted for cryptic relatedness. The statistical program, PLINK, was used to calculate a P value for each SNP passing quality control using the Cochran-Armitage trend test. The PennCNV program was used to define copy number variation (CNV). Results: We performed a genome-wide association study (GWAS) using with 1033 AN cases and 3733 controls (genomic inflation factor = 1.08). There were 11 SNPs with P<1X10-5 [(rsID, chromosome location, nearest gene, distance to nearest gene (base-pair), P value) rs6959888, 7q21.13, ZNF804B, 0, 1.63E-06; rs17725255, 20p11.23, CSRP2BP, 39396, 1.72E-06; rs10494067, 1p13.3, NTNG1, 0, 5.83E-06; rs2383378, 14q12, AKAP6, 0, 6.41E-06; rs410644, 5q14.1, SSBP2, 40462, 6.74E-06; rs4479806, 5p14.1, CDH9, 156926, 7.79E-06; rs957788, 13q33.3, FAM155A, 0, 8.11E-06; rs830998, 2q31.1, LRP2, 0, 8.68E-06; rs6782029, 3p25.3, VGLL4, 0, 9.04E-06; rs512089, 9p21.3, ELAVL2, 47984, 9.85E-06; rs3808986, 11q24.3, APLP2, 29217, 9.92E-6]. CNV analyses were performed on 1015 AN cases and 3532 controls. Overall frequencies of common or rare CNVs were similar between cases and controls. Specific rare and large (>500 kb, <1%) CNVs of interest included deletion of a large (~1.4Mbp) region of chr13q12 found in 2 AN samples and at a 10 fold lower frequency in a large sample (72,918) of subjects containing the genes SGCG, SACS, TNFRSF19, MIPEP, PCOTH, C1QTNF9B, SPATA13, MIR2276, and C1QTNF9, and an overlapping deletion and a duplication observed in 3 AN samples overlapping the CNTN6 and CNTN4 genes. Partially overlapping ~ 30 kb duplications were seen in 12 AN cases and in 1 control at the CDC5L gene on chromosome 6. Partially overlapping deletion of the 3' half of the PSTPIP1 gene was seen in 5 AN cases and no controls. Finally, a ~ 60 kb deletion of the PLEC1 gene was observed in 5 AN cases and in none of 3532 controls. Discussion: This is the first GWAS of AN. These preliminary results are consistent with absence of a major gene effect in AN. These results are consistent with genetic risk conveyed by multiple common alleles of small effect, as well as some uncommon CNVs of potentially larger effect. None of the implicated genes has a clear role in eating behavior. It must be emphasized that these results are preliminary and an additional ~ 400 AN cases will be analyzed as time and resources permit. These results require confirmation through study of independent populations of AN women.

  Study phs000679

• Polygenic Risk Score for the Prediction of Breast Cancer Is Related to Lesser Terminal Duct Lobular Unit Involution of the Breast

  The Susan G. Komen Tissue Bank (KTB) at the Indiana University Simon Cancer Center is an annotated biobank, which has recruited healthy women who provided demographic, lifestyle, and cancer-related information via self-administered questionnaire, blood samples and normal breast tissues. H&E slides of the normal breast tissues were scanned for image analysis and a pathologist measured the number of terminal duct lobular units (TDLUs) ("TDLU count"). The acini count per TDLU was quantified using the TDLU analyzer software. In this analysis, we computed the recently developed polygenic risk score (PRS) based on 313 common variants for the prediction of breast cancer and related this PRS to TDLU count and acini count per TDLU. We did this for the overall PRS, the ER-positive PRS and the ER-negative PRS.

  Study phs002062

• Host Response to Respiratory Infections

  In this study, we describe a strategy to identify undiagnosed respiratory viral infections through screening nasopharyngeal (NP) swabs for the chemokine CXCL10, which is highly induced in the nasopharynx as part of the host antiviral response. Using this strategy, we conducted two screens: first, we screened NP swabs collected at Yale New Haven Hospital (YNHH) in January 2017 from patients with undiagnosed respiratory viral infections and identified patients infected with seasonal coronaviruses and the relatively uncommon influenza C virus. Second, we screened samples from the beginning of March 2020 in the weeks before YNHH tested for SARS-CoV-2 and identified four patients that had undiagnosed SARS-CoV-2 infections. Sequences uploaded as part of this study include samples with rhinovirus, human coronavirus NL63, and 8 samples as part of the January 2017 screen for undiagnosed respiratory viral infections.

  Study phs002442

• Cholesterol homeostasis and lipid raft dynamics at the basis of tumor-induced immune dysfunction in chronic lymphocytic leukemia

  Autologous T-cell therapies show limited efficacy in chronic lymphocytic leukemia (CLL), where acquired immune dysfunction prevails. In CLL, disturbed mitochondrial metabolism has been linked to defective T-cell activation and proliferation. Recent research suggests that lipid metabolism regulates mitochondrial function and differentiation in T cells, yet its role in CLL remains unexplored. This comprehensive study compares T-cell lipid metabolism in CLL patients and healthy donors, revealing critical dependence on exogenous cholesterol for human T-cell expansion following TCR-mediated activation. Using multi-omics and functional assays, we found that T cells present in viably frozen samples of patients with CLL (CLL T cells) showed impaired adaptation to cholesterol deprivation and inadequate upregulation of key lipid metabolism transcription factors. CLL T cells exhibited altered lipid storage, with increased triacylglycerols and decreased cholesterol, and inefficient fatty acid oxidation (FAO). Functional consequences of reduced FAO in T cells were studied using samples from patients with inherent FAO disorders. Reduced FAO was associated with lower T-cell activation but did not affect proliferation. This implicates low cholesterol levels as a primary factor limiting T-cell proliferation in CLL. Consequently, CLL T cells displayed fewer and less clustered lipid rafts, potentially explaining the impaired immune synapse formation observed in these patients. Our findings highlight significant disruptions in lipid metabolism as drivers of functional deficiencies in CLL T cells, underscoring the pivotal role of cholesterol in T-cell proliferation. This study suggests that modulating cholesterol metabolism could enhance T-cell function in CLL, presenting novel immunotherapeutic approaches to improve outcome in this challenging disease.

  Dac EGAC50000000556

• From matrimonial practices to genetic diversity in Southeast Asian populations: the signature of the matrilineal puzzle

  This project aims at revisiting the "matrilineal puzzle" from a population genetics' point of view. The dataset consists of 719 individuals from 12 populations sampled in continental Southeast Asia and genotyped at 598764 loci. This dataset can only be accessed and used for non-commercial research purposes with a finality complying with the informed consent provided by donors. For accessing the data, please provide: 1. An explicit title for the project you wish to use the data for. 2. A detailed institutional affiliation of all recipients and users of the data. 3. A summary (500 words) of the research project, with emphasis on its scientific and societal finality, and predicted outputs. If access is granted by the DAC, data cannot be shared with a third party not initially involved in the project, without the third party officially applying for accessing the data.

  Study EGAS00001003727

• Single-cell analysis reveals fibroblast clusters linked to immunotherapy resistance in cancer

  A subset of Cancer-Associated Fibroblasts (CAF-S1) mediates immunosuppression in breast cancers (BC), but its heterogeneity and its impact on immunotherapy response remain unknown. Here, we identify 8 CAF-S1 clusters by analyzing more than 18000 single CAF-S1 fibroblasts from BC. We validate the 5 most abundant clusters by flow cytometry and in silico analyses in other cancer types, highlighting their relevance. Myofibroblasts from clusters 0 and 3, characterized by extra-cellular matrix proteins and TGF signaling respectively, are indicative of primary resistance to immunotherapies. Cluster 0 up-regulates PD-1 and CTLA-4 protein levels in regulatory T lymphocytes (Tregs), which in turn increases CAF-S1 cluster 3 cellular content. Thus, our study highlights a positive feedback loop between specific CAF-S1 clusters and Tregs and uncovers their role in immunotherapy resistance.

  Study EGAS00001004030

• Single cell characterization of T-cell lymphoma: RNA (2025-07-31)

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015669

• hereditary BrEAst Case CONtrol study (BEACCON)

  The BEACCON study aimed to address the lack of power of previous studies to identify novel BC predisposition genes by performing extensive sequencing in 12,000 women (11,511 analysed following exclusions) and further enhancing power by using an ‘extreme phenotype’ design with enrichment of familial non-BRCA1 and BRCA2 cases, compared with a control population of older women with ongoing confirmation of cancer-free status at June 2019. Three-quarters of the 1303 candidate genes screened were selected based on empiric evidence from local (69 multi-case BC families) or international whole exome sequencing studies, and the remainder were included to provide detailed coverage of functional pathways with established associations with BC.

  Dataset EGAD00001007025

• Ancestry and somatic profile predict acral melanoma origin and prognosis – RNA

  Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

  Dataset EGAD00001015756

• Integrated clinical, whole genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer

  We report the first combined analysis of whole genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole genome and transcriptome sequence was obtained from 9 anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 years prior to death. Transcriptome analysis revealed increased expression of AR-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only 1 of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today given this knowledge, use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations is critical for actionability, and can only be determined through analysis of multiple sites of metastasis. Our findings suggest that a large set of deeply analyzed cases could serve as powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials.

  Dataset EGAD00001001869

• Multi-Modal Single-Cell, Spatial, and Genomic Analyses of Human Non-Small Cell Lung Cancer Brain Metastases

  We performed single nuclei RNA-sequencing (snRNA-seq) with matched T cell receptor sequencing (TCR-seq), and pool matched low pass whole genome sequencing (WGS) of 12 treatment-naive non-small cell lung cancer (NSCLC) primary tumors (PTs) and 31 treatment-naive NSCLC brain metastases (BMs). In total, we recovered 277,206 cell transcriptomes in 43 samples. Single-nuclei suspension from frozen NSCLC metastases were generated using methods published in Slyper et al. (Nature Medicine, 2020, PMID:32405060) with modifications. The tissue was first cut in 20 µm sections using a cryostat and stored on dry ice until the next step. Then the tissue was put on wet ice and washed once with 5 ml PBS to remove OCT. After this step nuclei were extracted by vigorous pipetting in salt-tris buffer with Tween-20 (TST) followed by a high-volume wash in salt-tris buffer (ST). Nuclei were counted and 10,000-14,000 and were loaded using a Chromium controller (10X genomics) and Chromium Single Cell 5' Reagents (V1.1 and V2). Complementary DNA libraries were generated according to manufacturer's instructions, with the modification of one additional cycle of amplification. Matched single nuclei T cell receptor (snTCR) sequencing libraries were prepared from amplified cDNA libraries using either Chromium Single Cell V(D)J Enrichment Kit for human T cells Reagent Kit, v1.1, or single cell human TCR amplification kit. Final snTCR sequencing libraries were prepared using Single Index Kit T Set A for V1.1 libraries or Library construction kit and Dual Index Kit TT set A for V2 libraries. Sequencing libraries were quantified using Tapestation D5000 reagents and a 2200 TapeStation and pooled for sequencing. Pool matched low pass whole-genome sequencing (lp-WGS) was performed in addition to snRNA-seq to improve the identification of the malignant and non-malignant cell compartments. Nuclei from snRNA-seq sample preparations were collected by centrifugation (500g, 5 min), snap frozen after removing excess ST buffer, and stored at -200C until further processing. If insufficient nuclei (0C for 9 minutes. Adapters were not diluted, and the optional PCR (5 cycles) and cleanup were performed. After library cleanup with AMPure beads (Beckman Coulter, Brea, CA), libraries were quantified with Tapestation D5000 HS tapes (Agilent) and stored at -200C until sequencing.Using multiplexed immunofluorescence in an independent cohort of treatment-naïve pairs of primary tumors and brain metastases from the same patients with NSCLC, we validated genomic and tumor-microenvironmental findings and identified a cancer cell population characterized by neural features that strongly enriched in brain metastases. This comprehensive analysis provides insights into human NSCLC brain metastasis biology and serves as an important resource for additional discovery.

  Study phs003865

• sn-RNAseq profiling of the impact of a cytokine storm model in human cardiac organoids

  We developed conditions to model conditions of diastolic dysfunction caused by inflammatory factors in human cardiac organoids. Our organoid model is based on conditions promoting maturation (Mills et al., PNAS, 2017 and Voges et al., In Revision) and incorporating human pluripotent stem cell derived cardiomyocytes, epicardial cells, fibroblasts, endothelial cells and pericytes. Following 15 days of differentiation (Voges et al., Development, 2017) we formed human cardiac organoids incorporating both our multicellular differentiation (Mills et al., PNAS, 2017) and additional endothelial cells (Voges et al., In Revision). After another 12 days of maturation in 5 days maturation medium and 5 days weaning medium (Voges et al., In Revision) human cardiac organoids were either treated with weaning medium or “cardiac cytokine storm” comprised of 100 ng/ml IFNg, 10 ng/ml IL-1 β and 10 µg/ml poly(I:C). After 48 hours human cardiac organoids were harvested and snap frozen in -80C before nuclei isolation and single nuclei RNA sequencing.Pooled hCO (~40) were homogenized in 4 mL lysis buffer (300 mM sucrose, 10 mM Tris-HCl (pH = 8), 5 mM CaCl2, 5 mM magnesium acetate, 2 mM EDTA, 0.5 mM EGTA, 1 mM DTT)(all Sigma-Aldrich) with 30 strokes of a dounce tissue grinder (Wheaton). Large pieces of hCO were allowed to settle and homogenate was passed through pre-wetted 40 µm cell strainers (Becton Dickinson). Remaining hCO material in the douncer was resuspended in 4 mL and the douncing and filtering steps were repeated twice. All steps of the homogenization were performed on ice. The filtered homogenate was centrifuged at 1500 x g for 5 min at 4oC. Nuclei pellets were then re-suspended in PBS. A fraction of resuspended nuclei were then stained with hoechst nuclear stain (1:500 dilution) and counted on a haemocytometer under fluorescent microscope.The nuclei were then re-centrifuged (1500 x g for 5 min at 4°C) and resuspended at a density to load ~5,000 nuclei per sample. Cell were loaded into the Chromium Controller (10X Genomics) for gel bead emulsion (GEM) formation. Library preparation was conducted according to the manufacturer’s recommended protocol using the Chromium Next GEM Single Cell 3’ GEM, Library & Gel Bead Kit v3.1. Libraries were sequenced on the NextSeq 500/550 v2 (Illumina) with 150 bp reads.In the snRNA-seq we note the lower than expected percentage of non-myocytes and the loss of endothelial cells (Mills et al., PNAS, 2017 and Voges et al., In Revision), indicating the protocol requires further optimization for hCO samples.

  Study EGAS00001005174

• LITS

  Difference in gene expression values between case and control, log2 values. Blood transcriptome from women participating in the Norwegian Women and Cancer study (NOWAC) Post-genome Cohort taken up to eight years before brest cancer diagnosis. Illumina HumanWG-6 version 3 or Illumina HumanHT-12 expression bead chip, combined on identical nucleotide universal identifiers.

  Dataset EGAD00010001400

• usgwas-QC_imputed_update

  Understanding Society GWAS, samples that passed quality control, imputed to UK10K + 1000 Genomes combined reference panel

  Dataset EGAD00010000918

• A novel orthotopic patient-derived xenograft model of radiation-induced glioma following medulloblastoma

  DNA methylation arrays were performed to molecularly subtype these samples based on Capper D, Jones DTW, Sill M, et al. DNA methylation-based classification of central nervous system tumours. Nature. 2018;555(7697):469-474. doi:10.1038/nature26000

  Dataset EGAD00010002017

• HGSC lines: ATACseq and RNAseq, pre- vs post-treatment with HKMTi-1-005

  Formation of a DAC to support the deposition of RNAseq and ATACseq data, from pre- vs post-treatment high-grade serous ovarian carcinoma cell lines. The lines include PEO1, PEO4, PEA2, OVCAR5, OVCAR8, and the treatment includes use of a novel epigenetic drug called HKMTi-1-005.

  Dac EGAC50000000034

• PML complete dataset

  We generated single-cell transcriptomics, single-nuclei chromatin accessibility, CITE-seq and Multiomics of patients with PML. Pools are genetically multiplexed across donors, genotypic variation is included in this dataset to enable demultiplexing.

  Dataset EGAD50000000197

• Human TRIM24-MET fusion HGG RNA-seq

  Human RNA-seq data for TRIM24-MET fusion tumor primary samples and patient/PDOX-derived cell lines. Cells were treated with 0.1% DMSO or EC90 of MET inhibitors (capmatinib, cabozantinib, crizotinib) for 4 hours. BAM files containing aligned (and unaligned) reads to hg19 are provided.

  Dataset EGAD50000000194

• The life-saving benefit of dexamethasone in severe COVID-19 is linked to a reversal of monocyte dysregulation

  Assessment of dexamethasone response in human lung through scRNA-seq analysis of bronchoalveolar lavage (BAL) samples from patients with severe COVID-19.

  Study EGAS50000000203

• scRNA-seq of bronchoalveolar lavage (BAL) samples from patients with severe COVID-19 to assess dexamethasone response in the lungs

  Single-cell RNA-sequencing of bronchoalveolar lavage (BAL) samples from patients with severe COVID-19 with or without Dexamethasone treatment and for responders and non-responders was performed using 10x Genomics technology.

  Dataset EGAD50000000292

• Exome sequencing analysis of BCP-LBL patients samples

  In order to perform comprehensive SNV and CNA analyses of a cohort of BCP-LBL patients, we performed whole exome sequencing of 41 tissue samples from BCP-LBL patients. Because the material was available as FFPE, the target coverage of the samples was >200x.

  Dataset EGAD50000000418

• EBNA2 ChIP-Re-ChIP in primary B-cells infected with EBV virus

  EBNA2 ChIP-Re-ChIP in primary bulk B cells 4 days post EBV-infection with B95-8. DNA binding elements of the viral master regulator EBNA2, EBNA2-CBF transcription factor complex or EBNA2-EBF1 transcription factor complex were analyzed to identify virally targeted genes.

  Dataset EGAD50000000301

• Clones derived from early passage tumoroids of colorectal cancer

  We obtained different clones from early passage CRC tumoroids to study mutational signatures specific for truncal or private somatic alterations. These whole genome sequences are part of a larger study on the heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer.

  Dataset EGAD50000000152

• DCLRE1B/Apollo germline mutations associated with renal cell carcinoma impair telomere protection.

  We identified 2 germline mutations in the DCLRE1B gene encoding the Apollo protein by Whole Exome Sequencing (WES) in two families with inherited clear-cell Renal Cell Carcinoma. The raw data submitted here corresponds to WES performed on Genomic Platform at Gustave Roussy Institute.

  Dataset EGAD50000000311

• Target sequencing of 53 synovial sarcoma patients

  This dataset contains 138 .bam files sequenced with Illumina NovaSeq 6000. The files with the variant calling performed to the sequencing data, as well as the clinical data (phenotype) extracted during the sample extraction.

  Dataset EGAD50000000743

• Pregnancy-associated melanoma

  The aim of this project is to assess differences in intratumoral immune composition in pregnant melanoma patients versus non pregnant melanoma controls. Samples (N=25) were obtained from a local patient database. From archived FFPE we isolated RNA and performed NGS and bio-informatica data-analysis.

  Dataset EGAD50000000706

• Enrichment Data

  Fresh fecal samples were donated from healthy individuals. We evaluated the responses of healthy adult fecal microbiota to distinct carbon source conditions, pH levels and redox potentials. Metabolite concentrations were measured by HPLC. The total genomic DNA was extracted, sequenced and analyzed. The research project was approved by the Ethic Committee of the Canton of Zurich (2017-01290).

  Dac EGAC50000000346

• BipEx_Landen_SWEBIC

  BipEx: Bipolar Exome Sequencing Broad & Karolinska Institutet. EGAS00001005860. "This research project was a collaboration between the Karolinska Institute and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of X SWEBIC Bipolar case samples from collaborators in Sweden. Genomic DNA from each samples was sequenced to a mean depth of 20x"

  Dac EGAC50000000142

• RNA-Seq of acute lymphoblastic leukemia in LLAG-0707 study

  This dataset contains RNA-Seq data of acute lymphoblastic leukemia in LLAG-0707 study. Diagnostic samples of 188 patients were sequenced. Reads were aligned to hg19 genome reference using STAR. Aligned bam files are provided in this dataset.

  Dataset EGAD50000001181

• BipEx_Pedersen_Karolinska

  "BipEx: Bipolar Exome Sequencing Broad & Karolinska Institutet. EGAS00001005856. ""This research project was a collaboration between the Karolinska Institute BioBank and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 4,765 control samples from collaborators in Sweden. Genomic DNA from each samples was sequenced to a mean depth of 20x."" "

  Dac EGAC50000000141

• McQuillin_Global_London_SCZ_Bipolar_WES

  "McQuillin_Global_London_SCZ_Bipolar_WES. This research project was a collaboration between University College London, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 1,623 Schizophrenia and Bipolar case/control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x. For EGA Study ID: 1128"

  Dac EGAC50000000311

• snRNA splicing signature RNA-Seq

  This dataset has RNA-Seq fastq files which were generated as part of the snRNA splicing signature study. Analysis can be performed to regenerate splicing signatures found for RNU4-2, RNU5B-1 and RNU5A-1 by comparing cases versus controls.

  Dataset EGAD50000001299

• HIV-phyloTSI: BEEHIVE

  This dataset includes sample numbers TSI_0203 to TSI_0315 for the BEEHIVE 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 EGAD50000001310

• Melanoma transcriptomic data from patients undergoing immunotherapy

  This dataset contains raw RNA sequencing data from melanoma patient tumor samples collected before and during immunotherapy. The data support investigation of treatment-related changes in tumor cell populations. Samples were analyzed as part of a study exploring cellular responses to immune-based therapies.

  Dataset EGAD50000001569

• Long-read Nanopore data EVOFLUx

  Bam files with all reads covering 976 fCpGs identified in Gabbutt and Duran-Ferrer 2025 to develop the EVOFLUx methodology. These include 10 samples, 6 normal B cells, and 2 CLL patients developing RT.

  Dataset EGAD50000001697

• Olink Target Protein Expression

  Olink Target 96 Inflammation panels were applied to nasal secretions (DC, CRSsNP, CRSwNP, N-ERD, n=20 each). Across both panels, 184 assays (180 unique proteins) were determined, of which 4 appeared in both panels and were measured twice (CCL11, IL10, IL5, IL-6)

  Dataset EGAD50000001328