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• cqmuGWAS2

  DNA for 2482 individuals from Chongqing was extract from peripheral blood and genotyped by Illumina Omni Zhonghua-8 version 2 gene chips.

  Dataset EGAD00010001526

• GRIDSS somatic sv vcfs for EGAS00001004572

  Bulk GRIDSS somatic sv vcfs from tumour-normal analysis in EGAS00001004572

  Dataset EGAD00001006906

• Strelka somatic snv vcfs for EGAS00001004572

  Bulk Strelka somatic snv vcfs from tumour-normal analysis in EGAS00001004572

  Dataset EGAD00001006907

• IPF Core Biopsy Study RNA-Seq Fastqs

  RNA-Seq fastq files for 97 Idiopathic Pulmonary Fibrosis samples.

  Dataset EGAD00001007568

• Patient 16CH

  One file of patient 16 with WGS done on Illumina HiSeq X-Ten. For research purpose and authorised user only.

  Dataset EGAD00001003440

• Reference epigenome CKD27_C_Mesan_WGBS data generated from KEP study

  A CKD27_C_Mesan_WGBS paired end data for Mesangial cells(kidney)

  Dataset EGAD00001003471

• Reference epigenome CKD23_C_Mesan_WGBS data generated from KEP study

  A CKD23_C_Mesan_WGBS paired end data for Mesangial cells(kidney)

  Dataset EGAD00001003468

• Reference epigenome ADMSC04_smRNA-Seq data generated from KEP study

  A ADMSC04_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003870

• Reference epigenome KNIH008 WGBS data generated from KEP study

  A KNIH008 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for adipocytes

  Dataset EGAD00001002756

• NHLBI TOPMed: Cleveland Clinic Atrial Fibrillation (CCAF) Study

  The Cleveland Clinic Atrial Fibrillation Study consists of clinical and genetic data of patients with atrial fibrillation and control cohorts from the Cleveland Clinic CV/Arrhythmia Biobank, including the Cleveland Clinic Lone Atrial Fibrillation GeneBank. The Cleveland Clinic Lone AF GeneBank Study has enrolled patients with lone AF, defined as AF in the absence of significant structural heart disease. The CV/Arrhythmia Biobank has also enrolled participants with non-lone atrial fibrillation. All patients provided written informed consent.

  Study phs001189

• Khoe-San Genome Project

  The dataset contains BAM files of whole genome sequencing data of African Khoe-San population (n=169, 30X coverage) recruited from South Africa and Namibia. The population captured the true extent of human genetic diversity as represent the earliest diverged human population. The project described a detailed divergence of human population and identified positive selections associated forager lifestyles in Khoe-San population. These findings emphasise an inclusive catalogue with better representation of the earliest human genomic diversity to better advance biomedical research.

  Study EGAS50000001408

• RNAseq of 704 patients with soft tissue tumors

  The dataset contains transcriptome sequencing (RNA-seq) data of 704 soft tissue tumors (STT) from 704 patients. The sequencing data comes in FASTQ format and contains 1408 files. A total of 56 different STT types were included in the present study and each tumor type was represented by >2 samples. The vast majority of the patients had been diagnosed and treated at the sarcoma centers in Lund (Sweden) or Stockholm (Sweden) during the period 1988-2020, but also a few samples from other centers, obtained through previous collaborative projects, were included. RNA was extracted from fresh frozen tumor material and samples were primary lesions unless otherwise indicated. The sequencing was performed using 2x150 bp paired-end chemistry on a series of Illumina instruments at various facilities during the period 2013-2023.Samples were obtained after informed consent from the patients and the study was approved by the regional ethics committee (Etikprövningsmyndigheten, Uppsala, dnr 2023-01550-01, dnr 2025-02997-02).

  Dataset EGAD50000002120

• PanProstate Cancer Group DK data

  THE PAN PROSTATE CANCER PROJECT: Many groups around the world have generated Whole Genome DNA Sequence (WGS) data from prostate cancer patients. The pan prostate group have gathered with the idea that the accumulated data, should be collected and compared in a common format including common storage, re-analysis through a single pipeline, and investigation to achieve a variety of scientific goals. The combined collection would include the following categories: (i) cancers from different ethnic groups: eg Caucasian, Asian, Black Caribbean; (ii) cancer from different stages of progression from normal, to organ-confined disease, to metastases; (iii) early-onset prostate cancer; (iv) prostate cancer from aggressive and indolent disease; and (v) prostate cancer patients managed by different treatments with information linked to long-term clinical follow up data in many cases.This study contains the samples from the Danish prostate group.

  Study EGAS50000001616

• Whole-genome low pass sequencing of 3,514 Sardinian individuals

  The dataset includes the VCF files with the list of variants, and their frequency, found in 3,514 Sardinian individuals recruited from the SardiNIA longitudinal study (N=2090) and from a case-control study of autoimmune diseases in Sardinia (N=1424).

  Study EGAS00001002212

• WNT-signaling and Dupuytren's Disease

  The EGA hosts the summary genotype results of the GWAS in 856 patients with Dupuytren's disease and 2,836 population based controls from 'LifeLines' cohort study

  Study EGAS00000000043

• SCANDARE ovarian

  Prospective biobanking study in ovarian cancer patients aiming at better understand the link between the molecular alterations of the tumor itself, its microenvironment and immune response.

  Study EGAS50000001161

• ESGI___Whole_Genome_Sequencing_of_samples_from_the_INGI_Val_Borbera_genetic_isolate__X10_

  Whole genome sequencing of sampels from an isolated population from the Val Borbera valley in Italy. The samples are sequenced using the Illumina HiSeq X Ten system.

  Study EGAS00001001123

• Single Cell Genomic Analysis of Lymphoma

  Our study aimed to define the extent of heterogeneity between anatomically separated tumor manifestations in follicular lymphoma at single-cell resolution. We subjected single-cell suspensions derived from nodal, synchronously-acquired fine needle aspirations from two distinct tumor sites to high-throughput microfluidics-based single-cell RNA sequencing. By comparing the relative composition of the tumor subpopulations between the two tumor sites, we found that some patients can exhibit site-to-site differences. While the overall composition of the tumor microenvironment did not differ significantly between sites, we did detect a specific correlation between site-to-site tumor heterogeneity and T follicular helper cell abundance. Our study demonstrates the significant limitations of a solitary biopsy in defining the full scope of a patient's disease.

  Study phs002188

• Temporal and Clonal Progression in Pediatric Ependymoma

  Whole genome and exome-based DNA sequencing of germline and tumor specimens from serial samples of a single patient's ependymoma. The findings reveal the extent to which treatment with radiation and chemotherapies resulted in the diversification of the tumor subclonal architecture and shaped the neo-antigen landscape, and provide new insights into possible molecular mechanisms of oncogenesis, treatment response and recurrence.

  Study phs001461

• Clonal architecture and genomic features of smoking versus non-smoking oncogene-driven East-Asian non-small cell lung cancer

  Unlike smoking-related non-small cell lung cancers (NSCLC), oncogene-driven tumors are characterized by low mutational burdens and complex genomic landscapes. However, the clonal architecture and genomic landscape of the oncogene-driven tumors in smokers remains unknown. Here, we investigate the impact of tobacco smoking on the genomic and transcriptomic alterations in the context of oncogene-driven NSCLC.

  Study EGAS00001006942

• scRNA-seq of HGSC tumor and ascites

  Immune regulatory metabolites are key features of the tumor microenvironment (TME), yet with a few notable exceptions, their identities remain largely unknown. We uncovered the immune regulatory metabolic states and metabolomes of sorted tumor and stromal, CD4+, and CD8+ cells from the tumor and ascites of patients with high-grade serous ovarian cancer (HGSC) using high-dimensional flow cytometry and metabolomics supplemented with single cell RNA sequencing. Flow cytometry revealed that tumor cells show a consistently greater uptake of glucose than T cells, but similar mitochondrial activity. Cells within the ascites and tumor had pervasive metabolite differences, with a striking enrichment in 1-methylnicotinamide (MNA) in T cells infiltrating the tumor compared to ascites. Despite the elevated levels of MNA in T cells, the expression of nicotinamide N-methyltransferase, the gene encoding the enzyme that catalyses the transfer of a methyl group from S-adenosylmethionine to nicotinamide, was restricted to fibroblasts and tumor cells. Treatment of T cells with MNA resulted in an increase in T cell-mediated secretion of the tumor promoting cytokine tumor necrosis factor alpha. Thus, the TME-derived metabolite MNA contributes to an alternative and non-cell autonomous mechanism of immune modulation of T cells in HGSC. Collectively, uncovering the tumor-T cell metabolome may reveal metabolic vulnerabilities that can be exploited using T cell-based immunotherapies to treat human cancer.

  Study EGAS00001004829

• Biomarker Data from KATHERINE: A Phase III Study of Adjuvant Trastuzumab Emtansine versus Trastuzumab in Patients with Residual Invasive Disease after Neoadjuvant Therapy for HER2-Positive Breast Cancer

  Study EGAS00001006229

• Time course acetalax bisacodyl treatment

  RNA-Seq raw data of PDX treated with acetalaxor bisacodyl for 4h00 to 24h00.

  Dataset EGAD50000000875

• BelCovid_2_genotype

  Cohort: Raw genotype files for BelCovid2 cohort. Genotype Chip: Illumina Global Screening Array-24 v3.0 + Multi-Disease beadchip genomic build: b37

  Dataset EGAD00010002179

• GEN_COVID_genotype

  Cohort: Raw genotype files for GEN_COVID cohort. Genotype Chip: Illumina Global Screening Array-24 v3.0 + Multi-Disease beadchip genomic build: b37

  Dataset EGAD00010002177