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• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0151_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0151_001 for Triple negative breast cancer patient-derived xenograft SA1035X8XB03425

  Dataset EGAD00001011247

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0175_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0175_002 for Triple negative breast cancer patient-derived xenograft SA1035X8XB03631

  Dataset EGAD00001011249

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0014_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0014_001 for Triple negative breast cancer patient-derived xenograft SA604X6XB01979

  Dataset EGAD00001011251

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0015_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0015_001 for Triple negative breast cancer patient-derived xenograft SA604X6XB01979

  Dataset EGAD00001011252

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0019_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0019_001 for Triple negative breast cancer patient-derived xenograft SA604X7XB02089

  Dataset EGAD00001011253

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0020_002

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0020_002 for Triple negative breast cancer patient-derived xenograft SA604X8XB02164

  Dataset EGAD00001011254

• 10x Single Cell Gene Expression Library TENX063

  10x Single Cell Gene Expression library TENX063 for Triple negative breast cancer patient-derived xenograft SA609X3XB01584

  Dataset EGAD00001011268

• Comprehensive Deep Sequencing Atlas in HCC tumors

  The atlas aims to unravel the intricate genetic landscape of HCC, providing a detailed characterization of genomic alterations, transcriptomic profiles, and key mutations associated with liver tumors. The integration of WGS, RNAseq, and WES data offers a holistic perspective, facilitating a deeper understanding of the molecular mechanisms driving HCC pathogenesis. The resulting atlas serves as a valuable resource for researchers, clinicians, and the broader scientific community, contributing to advancements in HCC diagnostics, prognostics, and therapeutic interventions.

  Dataset EGAD00001015343

• V(D)J and 5' Gene Expression data of bone marrow cells from patients with aplastic anemia

  Viably frozen blood MNCs from 9 cGVHD patients were sorted with BD Influx Cell sorter, to enrich for CD45+ cells. Gene and V(D)J transcript profiles were studied with 10x Genomics Chromium Single Cell Immune Profiling platform. The Chromium Single Cell 5’RNAseq run and library preparation were done using the Chromium Next GEM Single Cell Immune Profiling version 1.1 chemistry. The raw data was processed using Cell Ranger v3.1 pipelines.

  Dataset EGAD00001012117

• ICU transcriptomics: Assessing the role of the host immune response in patients with ventilator-associated pneumonia

  This is a study of 100 patients with the aim to provide transcriptomic sequencing data analysis of cells isolated from bronchioalveolar lavage and blood samples from critically ill patients with pneumonia on an intensive care unit in order to investigate the host contribution to disease. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001015407

• ATAC-Seq/Hi-C/4C-Seq dataset for Malignant rhabdoid study

  Study describing the dynamics of chromatin organization within malignant rhabdoid tumors. This study describes how this chromatin organization changes upon SMARCB1 rescue within patient-derived organoid models from malignant rhabdoid tumors. Identification of a novel super-enhancer of MYC and identification of patient-specific enhancer utilization to activate MYC expression in these tumors.

  Dataset EGAD00001011820

• Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer

  The dataset for the study “Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer” includes 173 bam files from hybrid capture targeted error-correction next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 32 individuals with esophageal/gastroesophageal junction cancer, who received immunotherapy-containing regimens.

  Dataset EGAD00001011822

• Whole genome sequencing of tumor samples from advanced pre-treated NSCLC patients recruited in a phase I/II single-arm trial utilising CVA21, an oncolytic coxsackie virus, in combination with pembrolizumab.

  This dataset contains paired tumor and matched normal whole-genome sequencing (WGS) data from longitudinally collected samples of patients enrolled in an Australian clinical study involving multiple cancer types. For each patient, one or more tumor biopsies were obtained at different treatment time points (Scr, Day 0, Day 15, Day 22, Day 33), and matched normal samples were collected either from blood or non-tumor tissue.

  Dataset EGAD00001015682

• Whole-genome sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumoroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015707

• Single-cell RNA-sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumouroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015708

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015709

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015714

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015716

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015718

• Cell-free MeDIP-seq of plasma samples from lymphoma patients and healthy controls

  This dataset contains cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) data generated from plasma samples of lymphoma patients and healthy controls. The study aims to characterize genome-wide methylation patterns of circulating cell-free DNA and identify hypermethylated regions associated with lymphoma. Sequencing libraries were prepared using cfMeDIP with anti-5-methylcytidine antibody enrichment and sequenced on an Illumina platform. The dataset supports differential methylation analyses and the development of classification models for lymphoma detection.

  Dataset EGAD50000002108

• Mutational signatures in single cell clone expansion samples treated with clinical stage G-quadruplex binder CX5461

  Drug induced photoreactions following exposure to UVA have been documented for several therapeutic compound classes, including psoralens and fluoroquinolones. We used whole genome sequencing to examine the mutagenic spectrum of CX5461, a quinolone-derived small molecule, in expanded retinal pigment epithelial single cell clones exposed to UVA, CX5461, or a combination of both UV and CX5461. We identified the distribution of somatic base substitutions and short indels and mutational patterns in treated samples.

  Dataset EGAD50000002513

• TenK10K Phase 1: Whole Genome Sequencing SNP + indels multi-sample VCFs

  SNP and indel 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 performed using GATK4 HaplotypeCaller in DRAGEN mode. These VCFs consist of common (>=1% minor allele frequency [MAF]) and rare (<1% MAF) variants . This dataset is comprised of autosomal variants provided as multisample compressed VCF format files. Principal component scores were derived by using gnomAD’s run_pca_with_relateds method.

  Dataset EGAD50000002377

• deCODE Genetics study on genes contributing to nicotine dependence in humans

  A genome-wide association study on smoking behavior and nicotine dependence in Icelandic smokers, assessed by the number of cigarettes smoked per day, smoking initiation and degree of dependence on nicotine. The number of cigarettes smoked per day was ascertained through questionnaires given to individuals participating in multiple disease projects at deCODE Genetics (n=16,483). Smoking initiation was analyzed by comparing those that have ever smoked (n=16,483) versus those that have never smoked (n=21,667). The nicotine dependence analysis included 3,435 nicotine dependent cases (score 4 or higher on Fagerstrom Test for Nicotine Dependence (FTND) or endorsement of at least three of the seven Diagnostic and Statistical Manual of Mental Disorders 4th edition (DSM-IV) criteria) and 3,344 low-quantity smokers as controls.

  Study phs000393

• PD-1 Instructs a Tumor Suppressive Metabolic Program to Restrain AP-1 Activity in T Cell Lymphoma

  T cell non-Hodgkin lymphomas (T-NHLs) represent a heterogeneous group of aggressive cancers of mature CD4+ T cells, for which therapeutic options are limited. Recent work uncovered that the PDCD1 encoded immune checkpoint receptor PD-1 is a key tumor suppressor in T cells. PD-1 is recurrently inactivated in T-NHL and the highest frequencies of PDCD1 deletions are detected in advanced disease, predicting worse prognosis. The tumor-suppressive mechanisms of PD-1 signaling remain unknown. In the present study, we identify transcriptional and epigenetic mechanisms underlying PD-1 tumor suppression in T-NHL.Some subjects included in this study overlap with the subjects from phs002456. To establish the link between the overlapping subjects, the Subject Consent datasets will be utilized.

  Study phs003312

• Genome Sequencing of Hepatocellular Carcinoma at The Human Genome Sequencing Center of Baylor College of Medicine (HGSC-BCM)

  Hepatocellular carcinoma (HCC) accounts for 85-90% of primary liver cancers. We have focused on three major HCC etiologies:hepatitis C virus (HCV), hepatitis B virus (HBV), and nonviral causes. The onset and progression of cancer is driven by extensive rearrangement and mutation of the genome. We combined our capability to capture and enrich exome DNA with the next generation sequencing capacity to allow us to detect and characterize the somatic mutation profile of patients with HCC. Patient samples were collected by the Liver Center, Division of Abdominal Transplantation in the Baylor College of Medicine Department of Surgery. Sequencing of HCC is one of the NHGRI Center Initiated Projects in progress in the Human Genome Sequencing Center at Baylor College of Medicine.

  Study phs000509