3743 results for "RNA AND sequencing OR transcriptome"

in 23.35 milliseconds.

• The Normal Human Tissue Sequencing Project: Non-Diseased, Non-Malignant Tissues

  The Normal Human Tissue Sequencing Project provides RNA expression and DNA methylation data from normal (non-diseased) human tissues. This data set from a variety of source tissue is a valuable resource for human disease studies.

  Study phs000819

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX038_VOA11267_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005165

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX051_PBC04633_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005169

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX023_SA604X9XB02413_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005146

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX_015_SA604X6XB01979_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005155

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX006_PBC04106_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005163

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005141

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005144

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005142

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005152

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX051_PBC04633_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005168

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX055_VOA11924A_37C

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005170

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX049_SA928_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005178

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX067_VOA12024_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005179

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX003_SA605X3XB01966_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005159

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX054_SA604X9XB02417_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005172

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX050_PBC04573_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005167

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX004_SA605X3XB01966_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005161

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX049_SA928_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005177

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX004_SA605X3XB01966_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005162

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX056_VOA11924F_37C

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005171

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX006_PBC04106_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005164

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX049_SA928_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005176

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX020_SA604X8XB02164_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005149

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX026_VOA11083SD_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005158

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005143

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX023_SA604X9XB02413_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005145

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 36 samples; filetype=fastq

  Dataset EGAD00001005151

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX054_SA604X9XB02417_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005173

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX057_SA535X5XB02887_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005174

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX067_VOA12024_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005180

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005153

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX003_SA605X3XB01966_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005160

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX018_VOA11019SA_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005157

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX024_SA604X9XB02417_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005148

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX024_SA604X9XB02417_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005147

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 36 samples; filetype=fastq

  Dataset EGAD00001005150

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX_014_SA604X6XB01979_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005154

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX018_VOA11019SA_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005156

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX050_PBC04573_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005166

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX057_SA535X5XB02887_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005175

• The genomic landscape of germinal center derived B-cell lymphomas other than follicular, diffuse-large B-cell and Burkitt lymphom

  As part of the ICGC, the ICGC MMML-Seq project performed whole genome sequencing and RNA sequencing of germinal center derived B-cell lymphoma. Analyses were performed in concordance with the guidelines of the ICGC.

  Study EGAS00001002422

• Efficacy of CDK4/6i in preclinical models of malignant pleural mesothelioma

  Assessment of antitumor activity of CDK4/6 inhibitors using in vitro and in vivo preclinical models of MPM using RNA-sequencing. We also include the genomic characterization (whole exome sequencing) of patient-derived cell lines used in the in vitro experiments.

  Study EGAS00001005352

• Integrative multi-omic analyses of malignant pleural mesothelioma

  Multi-omic data (whole-genome sequencing, RNA-seq, EPIC 850K methylation arrays) for 123 samples from the MESOMICS project, the French project of molecular characterization of malignant pleural mesothelioma

  Study EGAS00001004812

• Small intestinal neuroendocrine tumors

  The goal of this study was to gain insights into the transcriptomes, mutations and copy number variants present in small intestinal neuroendocrine tumors. The present dataset contains RNA-sequencing performed on seven such tumors.

  Study EGAS00001003358

• Human lymphoma plasma cfRNA - raw data

  This study contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma patients, 13 primary mediastinal large B-cell lymphoma patients and 22 cancer-free controls.

  Study EGAS00001007127

• RNA Editing AZIN1 amplicon sequencing

  AZIN1 amplicon sequencing data of the EGAS00001000495 project.

  Dataset EGAD00001000708

• RNA Sequencing of Surgically Resected Colorectal Liver Metastases

  Dac EGAC00001000904

• RNA sequencing of sorted human RCC immune populations

  Dac EGAC00001002861

• bulk RNAseq from metastatic uveal melanoma tumour biopsies

  Tumour biopsies were obtained from uveal melanoma patients (n = 35) pre and 16 days post treatment with tebentafusp. Biopsies, which were either snap frozen or put in RNA later, were analysed by bulk RNA sequencing (50 million reads per sample) using the Illumina NovaSeq system.

  Dac EGAC50000000519

• Development and Validation of Patient-Derived Xenografts from Fibrolamellar Carcinoma Human Tissue

  We developed and validated Patient-Derived Xenografts (PDX) of Fibrolamellar Carcinoma human tissue from surgical resections. Human tissues from primary liver tumor, recurrent liver, and liver metastases were implanted into NOD-SCID-Gamma (NSG) mice (Jackson laboratories) and monitored for tumor growth. Some of the original tissues were frozen for further analysis including RNA sequencing. Tumors that grew were then harvested and passaged into additional mice. Some tumor tissues from the PDX samples were frozen for RNA-Seq analysis. The PDX was validated by histologic, transcriptomic and proteomic analysis. The RNA-Seq analysis was performed on original tissue samples including primary liver tumor, recurrent liver, liver metastases, normal liver, and the derived PDX.

  Study phs002435

• Transcriptomics of PPD and Control LCLs Exposed to Steroid Hormones

  Lymphoblastoid cell lines (LCLs) were derived from women with (n=11) and without (n=9) past postpartum depression (PPD) and compared transcriptomically in two studies. Data provided represents: 1) normalized RNA-seq expression (CPM) or 2) Ampliseq-RNA Expression (CPM).The two studies are described below.1) The first examined estradiol (E2) and progesterone (P) hormone conditions mimicking pregnancy and parturition: supraphysiologic E2+P-addback; supraphysiologic E2+P-withdrawal; and no added E2+P (Baseline). RNA-sequencing identified unique differentially expressed genes (DEGs, p2) The second exposed control and PPD LCLs to ALLO or DMSO vehicle for 60 hours and used Ampliseq to detect differentially expressed genes (DEGs, pnominal

  Study phs003820

• Genomic Changes in Breast Cancer Among Chinese Women in Hong Kong

  Recently, tumor sequencing and profiling analyses have improved molecular classification and refined existing breast cancer subtypes. However, epidemiologic data are absent in most somatic profiling studies even in extensively studied Western populations. The expansion of genomic studies to understudied populations with the integration of etiologic factors will allow the capture of a much wider range of genetic structure and mutagenic exposures associated with breast cancer risk. We therefore conducted a detailed molecular characterization of paired breast tumor/normal tissues using fresh frozen tissues collected from breast cancer cases in an ongoing breast cancer case-control study in Hong Kong. These analyses included whole genome (WGS)/exome sequencing (WES), targeted DNA panel sequencing, RNA sequencing (RNA-Seq), and genome-wide methylation profiling analyses.

  Study phs001870

• RNA sequencing of follicular T cell lymphoma

  Study EGAS00001004646

• Single cell sequencing data of PBMC and CSF from a cohort of Multiple Sclerosis patients and other neurological disease controls

  Neuroinflammation is often characterised by immune cell infiltrates in the cerebrospinal fluid (CSF). Here we apply single-cell RNA sequencing to explore the functional characteristics of these cells in patients with various inflammatory, infectious and non-inflammatory neurological disorders. We show that CSF is distinct from the peripheral blood in terms of both cellular composition and gene expression. We report that the cellular and transcriptional landscape of CSF is altered in neuroinflammation, but is strikingly similar across different neuroinflammatory disorders. We find clonal expansion of CSF B and T cells in all disorders but most pronounced in inflammatory diseases, and we functionally characterise the transcriptional features of these cells. Finally, we explore the genetic control of gene expression in CSF lymphocytes. Our results highlight the common features of immune cells in the CSF compartment across diverse neurological diseases and may help to identify new targets for drug development or repurposing in Multiple Sclerosis.

  Study EGAS50000000739

• Genome analysis of common diseases among older Japanese adults and development of clinical genome information storage

  A comprehensive gene expression analysis of the process leading up to the onset of Alzheimer???s disease (AD) would be helpful for understanding the mechanism. We performed an RNA sequencing analysis on a cohort of 1227 Japanese blood samples, representing 424 AD patients, 543 individuals with mild cognitive impairment (MCI), and 260 cognitively normal (CN) individuals. A total of 883 and 1169 statistically significant differentially expressed genes (DEGs) were identified between CN and MCI (CN-MCI) and between MCI and AD (MCI-AD), respectively. Pathway analyses using these DEGs, followed by protein???protein interaction network analysis, revealed key roles of ribosomal genes (RPL7, RPL11, and RPL14) and phagosomes (CDC42, PTPRC, PLCG1, and ACTR2) in MCI progression, whereas immune-related genes were involved in AD progression. Given the known effectiveness of delaying MCI progression in preventing AD, the genes related to ribosomal function and phagocytosis might emerge as biomarkers for early diagnosis.

  Study JGAS000755

• Human CD4+ T cells regulate peripheral immune responses in rheumatoid arthritis via IGFL2

  To elucidate the role of the immunoregulatory mechanisms of human CD4+ T cells, we analyzed CD4+ T cells in PBMC, synovium and synovial fluid using single-cell RNA sequencing (scRNA-seq). We identified insulin-like growth factor (IGF) like family member 2 (IGFL2), an evolutionary novel paralogous inflammatory factor found exclusively in primates. ScRNA-seq of RA synovium showed that IGFL2 is specifically expressed by CD4+ T cells, predominantly within peripheral helper T (Tph) cells, with upregulation correlating to disease severity. IGFL2 promotes TGF-��-induced CXCL13 production in CD4+ T cells. In addition, IGFL2 activates NF-��B signaling and induces monocyte gene signatures associated with pathogenic macrophages from RA synovial tissue, including CXCL10 and CXCL9. Notably, blood IGFL2 protein levels significantly correlate with RA disease severity and effectively discriminate RA patients. These findings highlight the substantial involvement of IGFL2 in RA pathogenesis, emphasizing how human CD4+ T cells exert pleiotropic regulation of local immune responses via this novel primate-specific soluble factor.

  Study JGAS000727

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  To elucidate the regulation of gene expression in immune cell subsets and its contribution to autoimmune diseases, Whole blood and various immune cell subsets from 119 Systemic Lupus Erythematosus (SLE), 65 Dermatomyositis & Polymyositis, 67 Systemic Sclerosis, 19 Mixed Connective Tissue Disease, 18 Sjogren's syndrome, 24 Rheumatoid Arthritis, 23 Behcet's disease, 18 Adult Onset Still���s Disease, 25 ANCA-associated Vasculitis, 16 Takayasu���s Arteritis and 141 healthy controls (C) were collected (Naive_CD4, Mem_CD4, Fr._I_nTreg, Fr._II_eTreg, Fr._III_T, Th1, Th2, Th17, Tfh, NK, Naive_CD8, Mem_CD8, EM_CD8, CM_CD8, TEMRA_CD8, Naive_B, USM_B, SM_B, DN_B, Plasmablast, CL_Mono (or CD16n_Mono), CD16p_Mono, Int_Mono, NC_Mono, mDC, pDC, LDG, Neu). Whole genome sequencing was performed with whole blood samples. RNA-seq was performed with each immune cell subset samples. After filtering and normalization of the gene expression data, eQTL analysis was performed in each immune cell type. 15 immune cell subsets ATAC-seq was also performed in 8 SLE and HCs, each.

  Study JGAS000220

• GATA6 expression distinguishes classical and basal-like subtypes in advanced pancreatic cancer.

  PURPOSE: To determine the impact of basal-like and classical subtypes in advanced PDAC and to explore GATA6 expression as a surrogate biomarker. EXPERIMENTAL DESIGN: Within the COMPASS trial patients proceeding to chemotherapy for advanced PDAC undergo tumour biopsy for RNA sequencing. Overall response rate (ORR) and overall survival (OS) were stratified by subtypes and according to chemotherapy received. Correlation of GATA6 with the subtypes using gene expression profiling, in situ hybridization (ISH) were explored. RESULTS: Between December 2015-May 2019, 195 patients (95%) had enough tissue for RNA sequencing; 39 (20%) were classified as basal-like and 156 (80%) as classical. RECIST response data were available for 157 patients; 29 basal-like and 128 classical where the ORR was 10% vs. 33% respectively (p=0.02). In patients with basal-like tumours treated with modified FOLFIRINOX (mFFX) (n=22) the progression rate was 60% compared to 15% in classical PDAC (p= 0.0002). Median OS in the intention to treat population (n=195) was 9.3 months for classical vs. 5.9 months for basal-like PDAC (HR 0.47 95% CI 0.32-0.69, p=0.0001). GATA6 expression by RNAseq highly correlated with the classifier (p<0.001) and ISH predicted the subtypes with sensitivity of 89% and specificity of 83%. In a multivariable analysis, GATA6 expression was prognostic (p=0.02). In exploratory analyses, basal-like tumours, could be identified by keratin 5, were more hypoxic and enriched for a T cell inflamed gene expression signature. CONCLUSIONS: The basal-like subtype is chemoresistant and can be distinguished from classical PDAC by GATA6 expression.

  Dataset EGAD00001006081

• Single-Cell RNA-Sequencing of Bone Marrow and Circulating Tumor Cells from Patients with Multiple Myeloma and its Precursor Conditions

  We performed single-cell RNA and V(D)J-sequencing of tumor cells from bone marrow and peripheral blood specimens and patients with Monoclonal Gammopathy of Undetermined Significance (MGUS), Smoldering Multiple Myeloma (SMM), and Multiple Myeloma (MM), as well as healthy donors. In this study we aimed to shed light on the mechanisms underlying tumor cell circulatory capacity and dissemination.

  Study phs003855

• DNA and RNA sequencing data from Ovarian Carcinosarcoma patients from the Glasgow Cohort.

  In this study, we analysed DNA and RNA sequencing data from Ovarian Carcinosarcoma patients, from isolated carcinoma and sarcoma components and investigated DNA variants as well as gene expression. Genomic analyses from this data and further investigation from preclinical models of ovarian carcinosarcoma support the conversion theory for disease development and indicate that microtubule inhibitors could be used to suppress EMT and stimulate anti-tumour immunity.

  Study EGAS00001006605

• RNA sequencing in blood samples of cluster headache patients

  Cluster headache is a relatively rare headache disorder, typically characterized by multiple daily, short-lasting attacks of excruciating, unilateral (peri-)orbital or temporal pain associated with autonomic symptoms and restlessness. To better understand the pathophysiology of cluster headache, we used RNA sequencing to identify differentially expressed genes and pathways in whole blood of patients with episodic (n = 19) or chronic (n = 20) cluster headache in comparison with headache-free controls (n = 20). Blood samples were subjected to globin reduction before sequencing.

  Study EGAS00001001918

• Rapid Idiosyncratic Mechanisms of Clinical Resistance to KRAS G12C Inhibition

  Using deep RNA and whole exome sequencing of pre- and post-treatment autopsy samples, we reveal diverse clonal populations that occurred through altered cell intrinsic, tumor microenvironment and immunologic remodeling mechanisms of resistance.

  Study phs002734

• CIAO Clinical Trial

  Whole exome and RNA sequencing for samples from CIAO (Checkpoint Inhibitors Assessment in Oropharynx cancer) (NCT03144778) clinical trial testing neoadjuvant anti-PD-L1 durvalumab with or without the anti-CTLA-4 tremelimumab in oropharynx cancer

  Study EGAS50000001174

• Regulatory Changes in Glioblastoma Brain Tumors and Xenografts Wave 1

  Non-coding elements in our genomes that play critical roles in complex disease are frequently marked by highly unstable RNA species. Sequencing nascent RNAs attached to an actively transcribing RNA polymerase complex can identify unstable RNAs, including those templated from gene-distal enhancers (eRNAs). However, nascent RNA sequencing techniques remain challenging to apply in some cell lines and especially to intact tissues, limiting broad applications in fields such as cancer genomics and personalized medicine. Here we report the development of chromatin run-on and sequencing (ChRO-seq), a novel run-on technology that maps the location of RNA polymerase using virtually any frozen tissue sample, including samples with degraded RNA that are intractable to conventional RNA-seq. We used ChRO-seq to develop the first maps of nascent transcription in 23 human glioblastoma (GBM) brain tumors and patient derived xenografts. Remarkably, >90,000 distal enhancers discovered using the signature of eRNA biogenesis within primary GBMs closely resemble those found in the normal human brain, and diverge substantially from GBM cell models. Despite extensive overall similarity, 12% of enhancers in each GBM distinguish normal and malignant brain tissue. These enhancers drive regulatory programs similar to the developing nervous system and are enriched for transcription factor binding sites that specify a stem-like cell fate. These results demonstrate that GBMs largely retain the enhancer landscape associated with their tissue of origin, but selectively adopt regulatory programs that are responsible for driving stem-like cell properties. We also identified enhancers and their associated transcription factors that regulate genes characteristic of each known GBM subtype, and discovered a core group of transcription factors that control the expression of genes associated with clinical outcomes. This study uncovers new insights into the molecular etiology of GBM and introduces ChRO-seq which can now be used to map regulatory programs contributing to a variety of complex diseases.

  Study phs001646

• Gene Expression Signatures Characterized by Longitudinal Stability and Inter-Individual Variability Delineate Baseline Phenotypic Groups with Distinct Responses to Immune Stimulation

  RNA sequencing (RNAseq) of peripheral blood lymphocytes was used to develop a means to assess immune function in a way that can be used in discovery science and applied to patients individually in clinical settings. The premise is that profiles of RNA present in immune cells is reflective of the combined influence of genetic and environmental variation on immune potential of individuals and that this potential can be tapped to understand human immunity in a variety of biological contexts. CD4+ cells were isolated from fresh whole blood via positive magnetic bead selection and cell lysates were prepared using Qiazol (QIAGEN) and stored at -80ºC for 3 to 8 months. RNA was extracted in batches for cDNA library preparation and RNA-Seq. For this study, we developed standard operating procedures for handling human blood samples and determined: a) the best way to enrich for CD4+ T cells from whole blood and yield high quality RNA, b) the sensitivity of this RNA profiling strategy, and c) the reproducibility of generated immune profiles from healthy subjects. We then developed bioinformatics processes to establish immune response signatures and immune response phenotypes within cohorts of individuals.

  Study phs001512

• Lipomatous tumors with 12q amplification

  RNA sequencing of 20 tumors.

  Dac EGAC50000000036

• RNA sequencing of AD, MCI and control ONS cells

  Study EGAS00001006594

• The genomic landscape of primary cutaneous anaplastic large cell lymphoma (pcALCL)

  Primary cutaneous anaplastic large cell lymphoma (pcALCL) is the second most common variant of cutaneous T-cell lymphoma. We subjected tumor biopsies from patients with pcALCL to whole-genome sequencing, whole-exome sequencing and RNA-sequencing to investigate genomic alterations and deregulated gene expression in the disease.

  Study EGAS00001004429

• Adrenal scRNA sequencing data access

  Raw sequencing datasets for manuscript "Hybrid untargeted and targeted RNA sequencing facilitates genotype-phenotype associations at single-cell resolution".

  Dac EGAC50000000869

• The Immune Microenvironment Shapes Transcriptional and Genetic Heterogeneity in Chronic Lymphocytic Leukemia

  Tumor microenvironment (TME) and somatic mutations drive progression of chronic lymphocytic leukemia (CLL). Integrated bulk and single-cell RNA sequencing (RNA-seq) of paired peripheral blood (PB) and lymph node (LN) samples from patients with treatment-naïve CLL showed upregulation of oncogenic processes in LN attributable to a minor population of activated tumor cells. A 10-gene tumor signature derived from this population was positively correlated with activated CD4+ T cells and M2 macrophages in the TME. Whole exome sequencing of paired PB and LN samples showed subclonal expansion in LN in some patients. In remaining patients with clonal stability between PB and LN, a T-cell inflamed TME was detected by RNA-seq. These data connect the TME with molecular events in the evolution of CLL.This cohort was later augmented with whole exome sequencing for 15 additional CLL samples. In an integrative analysis of genetic, transcriptomic, and epigenetic data, including the data from this study, we built new models to improve CLL patient prognostication.

  Study phs002297

• Whole genome sequencing data of pediatric B-other subtype acute lymphoblastic leukemia

  For a long time, approximately 70% of childhood B-ALL cases could be classified routinely, and the remaining 30% were classified into the “B-other” group lacking the known genetic features. However, more recently, new genomic tools have uncovered new subtypes among the B-other groups. Approximately 10% of B-ALL cases lack the recurrent genetic abnormalities, and are referred as "B-other". They are typically more heterogeneous than other subtypes of B-ALL, and their prognoses are more variable. In a more recent update of the B-ALL classification, 27 subtypes were identified (Arber et al., 2022). The identification of some of these subtypes is dependent on NGS methods, such as RNA sequencing, which are not routinely used in all clinical laboratories. For example, ETV6::RUNX1-like and DUX4-rearranged subtypes have been identified using RNA sequencing. For this study, subtype predictions for some of the cases is acquired from ALLIUM (Krali et al., NPJ Precis Oncol., 2023) and ALLCatchR (Beder et al., Blood, 2022) based on the RNA-seq profiles.

  Study EGAS50000001497

• RNAseq of MCL cell lines

  This study provides bulk RNA sequencing data from Mino and Jeko-1 mantle cell lymphoma (MCL) cell lines treated with CDK9 inhibitors, including the novel compound YX0798. CDK9 is a key regulator of RNA polymerase II–mediated transcription, and its inhibition disrupts transcriptional programs critical for tumor survival. The dataset captures transcriptomic changes associated with CDK9 inhibition, including downregulation of oncogenic drivers such as MYC and MCL-1. These data support mechanistic studies of transcriptional reprogramming and therapeutic vulnerability in aggressive MCL.

  Study EGAS50000001089

• Transcriptomic analysis of human hematopoietic populations sorted from umbilical cord blood.

  We isolated by fluorescence-activated cell sorting highly purified populations (long term hematopoietic stem cells (LT-HSCs), short term hematopoietic stem cells (ST-HSCs), multipotent progenitors (MPPs), common myeloid progenitor (CMPs), granulocyte and monocyte progenitors (GMPs), multilymphoid progenitors (MLPs), Myeloid-erythorid Progenitor (MEP), Granulocytes, Monocytes, B cells, T cells, Dendritic cells, Natural Killer cells and Erythrocyte Progenitors from 3 to 4 cord blood pools. We extracted RNA from 5K cells of each population and performed RNA-sequencing.

  Study EGAS00001004968

• Organoid BulkRNAseq

  Here, we aim to understand early determinants of brain organoid quality and generated a set of brain organoids from 12 different hPSC lines using an adaptation of the unguided Lancaster protocol (Lancaster & Knoblich, 2014). All cell lines were obtained from healthy donors. 12 donor hPSC lines were differentiated into brain organoids and a set of 72 individual organoids (6 per line) were randomly selected morphologically diverse organoids and subjected to bulk RNA sequencing for gene expression analysis. RNA was extracted using the RNeasy kit (Qiagen, Germany) according to the manufacturer’s instructions. A total of 1000 ng per sample was sent for RNA sequencing to Azenta Life Sciences (Genewiz Leipzig, Germany) for sequencing. Library preparation was performed using the NEBNext Ultra II RNA Library Prep Kit for Illumina following manufacturer’s instructions (NEB, Ipswich, MA, USA). mRNAs were first enriched with Oligo(dT) beads. The samples were sequenced using a 2x150 Pair-End (PE) configuration v1.5 at a depth of >20 million reads in each sample. Raw sequence data (.bcl files) generated from Illumina NovaSeq6000 was converted into fastq files and de-multiplexed using Illumina bcl2fastq program version 2.20. The raw sequence reads were aligned to the human reference genome GRCh38 using the STAR aligner (Dobin et al., 2013). Gene expression levels were quantified using the FeatureCounts tool (Liao et al., 2014).

  Study EGAS50000000659

• Chromatin accessibility maps of chronic lymphocytic leukemia identify subtype-specific epigenome signatures and transcription regulatory networks

  Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

  Dataset EGAD00001002110

• Upper cortical layer-driven network impairment in schizophrenia - 10x genomics v3 snRNA-seq and Visium spatial transcriptomics datasets

  This dataset contains 10x Genomics v3 3’ single nuclei RNA sequencing (24 human schizophrenia and control samples) and 10x Genomics Visium spatial transcriptomics (14 human schizophrenia and control samples) datasets. Files are in .bam format, output of the cellranger v3.1.0 (https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/3.1/using/count) for snRNA-seq and spaceranger v1.1.0 (https://support.10xgenomics.com/spatial-gene-expression/software/pipelines/1.1/using/count) for Visium samples. Reads were mapped against Release 97 of human genome from Ensembl (http://ftp.ensembl.org/pub/release-97/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz http://ftp.ensembl.org/pub/release-97/gtf/homo_sapiens/Homo_sapiens.GRCh38.97.gtf.gz). More details on sample processing are available in the biorXiv pre-print (https://doi.org/10.1101/2020.11.17.386458) and upcoming publication in Science Advances. BAM files can be converted to fastq files using bamtofastq tool (https://support.10xgenomics.com/docs/bamtofastq) with downstream remapping using tools and genomes of choice.

  Dataset EGAD00001009173

• Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis

  Single-cell RNA-Sequencing of three primary breast cancers, two primary prostate cancers, and a metastatic melanoma sample from Wu et al. (2021) Genome Medicine study. Each tumour was sequenced across different cryopreservation conditions including Fresh Tissue (FT), cryopreserved single-cell suspensions (CCS), cryopreserved solid tissue fragments (CT) and a cryopreserved after overnight cold storage (CO). Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq platform.

  Dataset EGAD00001007030

• DAC for BCP-LBL Kiel

  Whole exome sequencing and RNA sequencing of B-Cell Precursor Lymphoblastic Lymphoma tissue biopsies.

  Dac EGAC50000000181

• T-ALL RNA-Seq raw data files

  Bone marrow or peripheral blood samples were collected of adult patients at first diagnosis of T-precursor acute lymphoblastic leukemia. RNA was isolated from mononuclear cells and subjected to mRNA library prep using Poly-A selection and sequencing on a NovaSeq 6000 system. Obtained gene expression profiles and gene fusion calls were used to allocate samples to molecular disease subtypes.

  Study EGAS50000000213

• RNA sequencing in primary inflammatory (TPP) macrophages following deletion of a disease-associated gene desert at chr21q22, disruption of ETS2, or treatment of ETS2-edited macrophages with a HIF1α stabiliser.

  GWAS studies in five different inflammatory diseases have identified a strong genetic association at a gene desert at the chr21q22 locus. We have shown that this locus contains a monocyte/macrophage-specific enhancer that regulates ETS2 - a gene whose role in primary human monocytes/macrophages is incompletely understood. We therefore used a CRISPR-Cas9-based approach to delete the enhancer region or to disrupt ETS2, and performed RNA-sequencing to examine the transcriptional consequences. One effect of ETS2 disruption was upregulation of genes involved in aerobic respiration and oxidative phosphorylation. We therefore treated ETS2-edited inflammatory macrophages with roxadustat, a HIF1α stabiliser that can promote glycolysis via HIF1α-mediated metabolic reprogramming, and performed RNA-sequencing to determine whether this drug might rescue the transcriptional effects of ETS2 disruption.

  Study EGAS00001007553

• Genomic and epigenomic sequencing data on human samples of Institut Curie.

  Total RNA sequencing, whole exome sequencing, whole genome sequencing and whole genome bisulfite sequencing on human samples collected at Institut Curie, France.

  Dac EGAC50000000356

• DS-ALL RNA-Seq

  RNA-Seq was performed on 249 DS-ALL samples. Library preparation was carried out using TruSeq Stranded Total RNA Library Prep Kit. The libraries were sequenced on a NovaSeq platform with read length of 2×101.

  Dataset EGAD00001009403

• Dataset for leiomyosarcoma-RNA

  Rare cancer sequencing data of 87 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008849

• Dataset for head_and_neck_cancer-RNA

  Rare cancer sequencing data of 92 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008861

• RNA sequencing of primary B-cells infected with EBV virus

  Study EGAS00001007187

• Total RNA-Sequencing of patient-derived xenograft models of myxoid liposarcoma

  Study EGAS00001004901

• bulk Exome-seq of the 5 HCC patients which also have the single cell T cell RNA-seq data

  bulk Exome-seq data of the 5 HCC patinets. Single cell RNA seq data of these patients was under the accession number EGAD00001003337

  Dataset EGAD00001004149

• Microbiome cross talk, Fusobacterium n. and formate metabolite

  This data comes into 2 pairs of experiments: - RNA-seq Control versus Formate treated colorectal cancer T18 cells - Humix device, RNA-seq of control versus co-culture colorectal cancer T18 cells with Fusobacterium nucleatum

  Dataset EGAD00001008533

• Sequencing data for oesophageal and related samples - Abbas et al (RNA)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (RNA for 197 samples)

  Dataset EGAD00001011269

• Genomic and Transcriptomic Profiling of Patients with Malignant Pleural and Peritoneal Mesothelioma: The NCI Cohort

  Malignant mesothelioma is an aggressive cancer with limited treatment options and poor prognosis. Better understanding of mesothelioma genomics and transcriptomics could advance novel therapies. We performed whole-exome sequencing (WXS) of germline and tumors of 122 patients, and RNA-sequencing (RNA-Seq) of tumor samples of 100 patients with pleural, peritoneal, and tunica-vaginalis mesothelioma.The biospecimens used in this study were collected as a part of the Mesothelioma Natural History Protocol (https://clinicaltrials.gov/ct2/show/NCT01950572), wherein, samples were collected from subjects with malignant mesothelioma as listed in the eligibility criteria below and written consent from each participant was obtained before sample acquisition.

  Study phs002207

• Characterization of Prostate Cancer Organoids

  Using models from the LuCaP series as well as those generated at the National Cancer Institute, we have established organoids for in vitro mechanistic testing, including drug screening and genetic manipulation. The major findings from these continuing studies is the durability of organoids for maintaining complex subpopulation and intratumoral heterogeneity and the parallels between in vitro testing and patient outcomes. Existing data from prior releases includes whole-genome sequencing, whole-exome sequencing, single-cell and bulk RNA-seq, single-cell ATAC-seq, and SNP array. New data in this release is ChIP-seq data from three models and RNA-seq data from one model.

  Study phs001587

• Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer

  This data set includes sequence files from whole exome sequencing and RNA sequencing from serial tissue and blood biospecimens from a phase 2 clinical trial of stereotactic body radiation therapy (SBRT) followed by pembrolizumab in metastatic non-small cell lung cancer (NSCLC; NCT02492568).

  Study EGAS50000000277

• Fusion gene analysis using multiplex single primer extension-based RNA-sequencing

  The whole study comprises of two patient cohorts. Screening cohort: 40 patients of Germany; validation cohort: 40 patients from Asia. Further, bile duct and CCA cell lines have been analyzed. This dataset contains fusion gene analysis using multiplex single primer extension-based RNA-sequencing for a subset of 25 patients of the screening cohort. Data was generated on Illumina NexSeq 550 device in paired-end mode and is stored in compressed FASTQ file format.

  Dataset EGAD00001011326

• Comprehensive assay for the molecular profiling of cancer by target enrichment from formalin-fixed paraffin-embedded specimens

  Tumor molecular profiling is becoming a standard of care for patients with cancer, but the optimal platform for cancer sequencing remains undetermined. We established a comprehensive assay, the Todai OncoPanel (TOP), which consists of DNA and RNA hybridization capture-based next-generation sequencing panels. A novel method for target enrichment, named the junction capture method, was developed for the RNA panel to accurately and cost-effectively detect 365 fusion genes as well as aberrantly spliced transcripts. The TOP RNA panel can also measure the expression profiles of an additional 109 genes. The TOP DNA panel was developed to detect single nucleotide variants and insertions/deletions for 464 genes, to calculate tumor mutation burden and microsatellite instability status, and to infer chromosomal copy number. Clinically relevant somatic mutations were identified in 32.2% (59/183) of patients by prospective TOP testing, signifying the clinical utility of TOP for providing personalized medicine to cancer patients.

  Study JGAS000164

• The Finland-United States Investigation of NIDDM Genetics (FUSION) Study - Islet Expression and Regulation by RNAseq and ATACseq

  This study evaluates gene expression and its regulation in human pancreatic islets, a tissue relevant in the study of genetic risk factors contributing to diabetes. We obtained pancreatic tissue sections and purified pancreatic islets from deceased donors and processed these biological samples to generate various data types. We generated spatial transcriptomic data from pancreatic tissue samples using the 10X Genomics VISIUM technology with sequencing on the Illumina NovaSeq platform. We also generated multiple data types from the purified pancreatic islets using genome-wide SNP chips, bulk RNA-Seq, microRNA (miRNA)-Seq, whole genome sequence, DNA methylation (methyl)-Seq, cap analysis of gene expression (CAGE)-Seq, single cell RNA-seq, and single nuclei ATAC-seq approaches. These data include ATAC-seq of two islet subjects, RNA-seq of 31 additional subjects, genome-wide chip genotypes, and imputed genotypes of the 33 subjects released with phs001188.v1. For genotyping, 500-1000 islet equivalents (IEQ) were cultured as in Gershengorn (Science, 2004, PMID: 15564314); genomic DNA isolated from islet cultures. For RNA analyses, 2500-5000 IEQ from each islet source were used for bulk or single-cell RNA isolation. Messenger RNA was isolated with trizol extraction and 12-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol. Bulk RNA sequencing was performed on HiSeq2000/HiSeq2500/Hiseq4000/NovaSeq6000 sequencers using paired-end reads at the NIH Intramural Sequencing Center (NISC). miRNA libraries were prepared from total RNA from 68 samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. CAGE libraries were prepared from total RNA samples using the nAnT-iCAGE protocol at DNAFORM, Japan. CAGE libraries were sequenced at the NIH Intramural Sequencing Center (NISC) on the HiSeq2000 sequencer. Genotyping on the Illumina Omni2.5M array was performed at the NHGRI Genomics Core facility. Genotypes were imputed using the HRC.r1.1.2016 reference panel. To assess regions of open chromatin in islets, we performed bulk ATAC-seq on HiSeq2000 sequencers using paired-end reads at NISC. Single-nuclei ATAC-seq libraries were prepared using single-cell-combinatorial-indexing (sci-) ATAC-seq protocol and sequenced on Illumina NextSeq using paired-end reads. scRNA-seq libraries were generated using the 10X Genomics platform and sequenced on Illumina HiSeq3000 at the Genomics Technology Core of the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS). Greater than 90% of the loci associated with T2D through genome-wide association studies occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Therefore, there is a critical need to understand the full spectrum of genetic variation and regulatory element usage in T2D-relevant tissues. To that end, this study contains multiple genomic and transcriptomic data sets from pancreas tissue sections and pancreatic islets, a resource that will contribute to our efforts to investigate the genetic risk factors for type 2 diabetes.

  Study phs001188

• Transcriptional profiling and clonality analysis of peripheral blood B cells and small intestinal plasma cells in celiac disease

  Single-cell RNA-seq and BCR sequencing and/or inference of sorted IgA+ peripheral blood B-lineage cells and small intestinal plasma cells of untreated celiac disease patients.

  Study EGAS50000000229

• Deciphering RBP - alternative splicing networks in ALS iPSC-MN: TDP-43, NOVA1, NOVA2 and RBFOX2 eCLIP-seq

  We produced enhanced cross-linking immunoprecipitation (eCLIP) sequencing data of the RNA binding proteins (RBP) TDP-43, NOVA1, NOVA2 and RBFOX2 in iPSC motor neurons of two healthy control individuals, respectively.

  Study EGAS00001005880

• Identification of the cause of juvenile parkinsonism in a case_SYNJ1

  This study aimed to elucidate the genetic causes underlying the Juvenile Parkinsonism diagnosed in a girl using whole-exome sequencing, analysis of CAG repeats, RNA sequencing analysis on fibroblasts, and metabolite identification. As a result, a homozygous missense mutation SNP T/C (rs2254562) in SYNJ1 and alteration in metabolism were identified.

  Study EGAS00001007686

• Elucidation of the association of the HPV integration and oropharyngeal cancer

  Whole-genome sequencing was performed using tumor and blood samples from 14 patients with HPV-associated oropharyngeal cancer. Bulk RNA sequencing was performed using tumor samples from 19 patients with HPV-associated oropharyngeal cancer and 17 patients with non-HPV-associated oropharyngeal cancer and normal tonsil samples from 2 healthy controls.

  Study JGAS000751