15059 results for "cancer studies using rna-seq"

in 37.05 milliseconds.

• BLUEPRINT release August 2015, RNA-Seq for endothelial cell of umbilical vein (proliferating), on genome GRCh38

  RNA-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001535

• BLUEPRINT release August 2016, RNA-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh38

  RNA-Seq data for 8 CD14-positive, CD16-negative classical monocyte sample(s). 8 run(s), 8 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002308

• BLUEPRINT release August 2015, RNA-Seq for CD4-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 10 CD4-positive, alpha-beta T cell sample(s). 10 run(s), 10 experiment(s), 10 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001544

• BLUEPRINT release August 2015, RNA-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh38

  RNA-Seq data for 8 CD14-positive, CD16-negative classical monocyte sample(s). 8 run(s), 8 experiment(s), 8 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001506

• BLUEPRINT release August 2015, RNA-Seq for mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs), on genome GRCh38

  RNA-Seq data for 3 mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs) sample(s). 3 run(s), 3 experiment(s), 3 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001520

• BLUEPRINT release August 2015, RNA-Seq for central memory CD8-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 1 central memory CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001547

• BLUEPRINT release August 2015, RNA-Seq for endothelial cell of umbilical vein (resting), on genome GRCh38

  RNA-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001496

• BLUEPRINT release August 2015, RNA-Seq for cytotoxic CD56-dim natural killer cell, on genome GRCh38

  RNA-Seq data for 3 cytotoxic CD56-dim natural killer cell sample(s). 3 run(s), 3 experiment(s), 3 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001521

• BLUEPRINT release August 2015, RNA-Seq for CD3-positive, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001593

• BLUEPRINT release August 2015, RNA-Seq for erythroblast, on genome GRCh38

  RNA-Seq data for 7 erythroblast sample(s). 29 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001550

• BLUEPRINT release August 2016, RNA-Seq for effector memory CD4-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 2 effector memory CD4-positive, alpha-beta T cell sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002469

• BLUEPRINT release August 2015, RNA-Seq for central memory CD4-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 1 central memory CD4-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001543

• Dataset for Ewing_sarcoma_PNET-EXON

  Rare cancer sequencing data of 30 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008873

• Dataset for urologic_cancer-WHOLE_GENOME

  Rare cancer sequencing data of 36 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008903

• Childhood Cancer Data Initiative (CCDI): Comprehensive Genomic Sequencing of Pediatric Cancer Cases (CMRI/KUCC)

  This study provides paired tumor normal genomic sequencing data from ~ 200 children with cancer, including both solid tumors and leukemias, done by the Children's Mercy Research Institute (CMRI) and University of Kansas Cancer Center (KUCC). These data include whole genome sequencing (generally, ~20x), whole exome sequencing (generally, ~300x), bulk RNA sequencing (generally, ~80 million reads), and single-cell RNA and ATAC sequencing (>50,000 reads/cell). Additional phenotypic, pathologic, and genetic data, gathered clinically for these samples, are also provided.

  Study phs002529

• The aim of this study was to identify underlying hub genes and dysregulated pathways associated with the development of HCC using bioinformatics analysis.

  In the present study, we identified differentially expressed protein-coding genes from RNA transcriptional profiling performed on 11 paired cancer tissues and adjacent non-cancerous tissues. Then, we conducted GO, KEGG, PPI network and centralities analyses to study and identify changes in pathways and hub genes. The aim of this study was to improve understanding of HCC carcinogenesis by providing information concerning the genetic changes that occur during disease progression and to uncover the expression of biomarkers with potential use for clinical diagnosis, treatment, and monitoring of disease progression.

  Study EGAS00001002526

• WGS and WTS data of patient diagnosed with HSTCL

  WGS and WTS data of a single patient diagnosed with HSTCL. Whole-genome sequencing (WGS) was performed for the tumor-normal sample. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 4000 2x151 bp read length. Whole-transcriptome sequencing (WTS): Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on Illumina HiSeq 2500 with 2x101 bp read length.

  Dataset EGAD00001005229

• Single cell RNA and ATAC sequencing data from GBM patients

  Glioblastoma cells infiltrate and incorporate into the normal brain parenchyma. We conduct unbiased multimodal single-cell and spatial sequencing to capture GBM cells and the surrounding tumor microenvironment using a regional sampling strategy. For each patient, we profile the peritumoral region, tumor edge, and tumor core, providing a comprehensive characterization of the transcriptional and epigenetic landscape of GBM spatial heterogeneity, with a specific focus on infiltrative cells.

  Study EGAS50000000547

• MutWP6__CRUK_Grand_Challenge_Mutographs_of_Cancer__oncology_agents

  he Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Within Mutographs, work lead by the Sanger Institute will investigate whether detection of somatic mutations and mutational signatures in circulating white blood cells can be developed into a practical, generic system for surveying and monitoring multiple different endogenous and exogenous exposures, providing an ‘observatory’ on somatic mutational processes in humans. Whole genome sequences are generated at the Wellcome Sanger Institute (Illumina HiSeqX). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001004125

• MutWP6__CRUK_Grand_Challenge_Mutographs_of_Cancer__Botseq

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Within Mutographs, work lead by the Sanger Institute will investigate whether detection of somatic mutations and mutational signatures in circulating white blood cells can be developed into a practical, generic system for surveying and monitoring multiple different endogenous and exogenous exposures, providing an ‘observatory’ on somatic mutational processes in humans. Whole genome sequences are generated at the Wellcome Sanger Institute (Illumina HiSeqX). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001004330

• Human embryonic stem cells dopaminergic neurons scRNA-seq

  The dataset includes 2 samples of Single cell RNA-seq (10X Genomics) from Human Embryonic stem cells. 2 samples with 2 replicates of timepoints 17 and 28 of dopaminergic neuron differentiation.

  Dataset EGAD50000001592

• scMultiome

  This dataset gather scMultiomic data including RNA-seq and ATAC-seq in MM.1S in control and dex condition at 1h and 4h

  Dataset EGAD00001011140

• High-Risk Breast Cancer GWAS

  The GWAS includes High Risk Women from the following epidemiological studies of breast cancer, comprising a total of 3,719 cases and 3,642 controls (cases/controls: MEC, 0/200; ABCFR, 326/418; FCCC, 56/3; BCFR-UT, 66/32; CNIO-BC, 87/92; GESBC, 65/0; LIFE, 164/0; MARIE, 41/105; MAYO, 208/210; MNYR, 293/409; MSKCC, 310/0; NC-BCFR, 234/233; OFBCR, 553/560; POSH, 377/0; HBOC, 47/47; BBCS, 612/1333; UPENN, 280/0 This study was funded by a grant CA165038 to Christopher Haiman (University of Southern California) and John Hopper (University of Melbourne) from the National Cancer Institute, National Institute of Health. The contributing studies: Multiethnic Cohort (MEC). This study was supported by grant UM1 CA164973 from the National Cancer Institute, National Institute of Health. Ontario Familial Breast Cancer Registry, the Ontario site of the Breast Cancer Family Registry Cohort (OFBCR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Utah Breast Cancer Family Registry (BCFR-UT). This study was supported by grant UM1 CA164920 from the National Cancer Institute. New York site of the Breast Cancer Family Registry (MNYR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Northern California site of the Breast Cancer Family Registry (NC-BCFR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Australian Breast Cancer Family Registry (ABCFR). This study was supported by grant UM1 CA164920 from the National Cancer Institute. Breast Cancer Study (CNIO-BC). This study has been partially funded by The Spanish Network on Rare Diseases (CIBERER) and the Spanish National Genotyping Center (CEGEN). Genetic Epidemiologic Study of Breast Cancer (GESBC). The GESBC was supported by the Deutsche Krebshilfe e. V. [70492] and German Cancer Research Center (DKFZ). Mammary Carcinoma Risk Factor Study (MARIE). This study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH). Funding for the POSH study was provided by Cancer Research UK (grant refs A7572, A11699, C22524), the Breast Cancer Campaign (grant number: 2013MayPR044) and from 2003-2006 by a grant from The Wessex Cancer Trust. Prospective study of Outcomes in Sporadic versus Hereditary breast cancer (POSH). Funding for the POSH study was provided by Cancer Research UK (grant refs A7572, A11699, C22524), the Breast Cancer Campaign (grant number: 2013MayPR044) and from 2003-2006 by a grant from The Wessex Cancer Trust. Hereditary Breast and ovarian Cancer: Genetic and Molecular Studies (HBOC). This study was supported by National Cancer Institute grant CA58860 and The Lon V Smith Foundation: LVSF-44528. Mayo Clinic inherited breast and ovarian cancer study (MAYO). This study was supported by the Breast Cancer Research Foundation, NIH grants CA192393, CA176785, and an NIH CA116201 Specialized Program of Research Excellence (SPORE) in Breast Cancer. British Breast Cancer Study (BBCS); Mammographic oestrogens and growth factor study (MOG). The BBCS and the MOG study are funded by Cancer Research UK and Breakthrough Breast Cancer and acknowledge NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). Genotyping of non-BRCA1/2 mutation carriers (UPENN). The study is supported by the Basser Research Center at the University of Pennsylvania, Rooney Family Foundation, NIH grants CA176785 and CA192393, the Breast Cancer Research Foundation, the Susan G. Komen Foundation for the Cure and Macdonald Family Foundation. Clinical Significance of Germline BRCA Mutations (MSKCC). The study is supported by the Robert and Kate Niehaus Clinical Cancer Genetics Research Initiative, The Breast Cancer Research Foundation, and the Cancer Center Support Grant from the National Institute of Health, National Cancer Institute 5P30 CA08748-40. Women's Learning the Influence of Family and Environment (LIFE). This study was supported by grants CA17054 and CA74847 from the National Cancer Institute, National Institutes of Health, No. 4PB-0092 from the California Breast Cancer Research Program of the University of California. Philadelphia site of the Breast Cancer Family Registry at Fox Chase Cancer Center (FCCC). This study is supported by NIH grant CA164920.

  Study phs000929

• Bulk RNAseq from in vitro generated macrophages and T cells, and mUM tumour biopsies

  Monocyte derived macrophages were polarised into M1 or M2 using IFNg+ ILP or IL-4 respectively (n =4) . Pan T cells were cultured with or without IL-2 for 4 days (n=4 - 6). Pan T cells were co-cultured with THP1 tumour cells for 20 hours in the presence or absence of ImmTAC molecules and in the presence or absence of M2 macrophages. Sorted T cells and macrophage populations prior and post co-culture were analysed by bulk RNA sequencing (60 million reads per sample) using the Illumina NovaSeq system. 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 EGAC50000000518

• RNA-sequencing of a representative cohort of 209 AML cases

  Sample libraries were prepped using 500 ng of input RNA according to the KAPA RNA HyperPrep Kit with RiboErase (HMR) (Roche) using Unique Dual Index adapters (Integrated DNA Technologies, Inc.). Amplified sample libraries were paired-end sequenced (2x100 bp) on the Novaseq 6000 platform (Illumina) and aligned against the human genome (hg19) using STAR v2.5.4b2.

  Dataset EGAD00001007581

• Oncogenic FOXL2C134W has gain-of-function chromatin remodeling activity that reprograms glucocorticoid receptor occupancy to promote ovarian granulosa cell tumor growth

  This dataset contains bam files from the whole exome sequencing performed on granulosa cell tumors and 7 sequencing experiments performed on human-derived KGN granulosa cell tumor cells and isogenic cell lines. The latter include transcription factor ChIP-seq for Foxl2 as well as transcription factor ChIP-seq for Foxl2 and GR under dexamethasone treatment and untreated conditions, two ATAC-seq data sets, two RNA-seq data sets, and Histone marks ChIP-seq.

  Dataset EGAD50000000880

• English Longitudinal Study of Ageing Genome-wide genotyping using the Illumina HumanOmni2.5-8

  These data are for a Genome Wide Association Study (GWAS) in the English Longitudinal Study of Ageing (ELSA, www.ifs.org.uk/elsa), building on the existing ELSA DNA Repository (EDNAR). This will establish a valuable resource for UK and international scientists, giving them access to GWAS genotyping data. Phenotype data, available on request, includes measures of personality, attitudes, behaviours as well as detailed social and economic outcomes; high quality biomarkers and other intermediate phenotypes; a range of more distal phenotypes, such as direct assessments of health (for example, hypertension, diabetes, muscle strength and cognitive function), and the opportunity to analyse existing biological samples for additional biomarkers, including metabolomic studies. Importantly, this resource would be matched with a near identical resource established in the United States for the Health and Retirement Study (HRS), giving the potential for high quality replication studies and comparative analyses.

  Study EGAS00001001036

• CLL ATAC Seq of Untreated and IBET762 treated samples

  CLL PBMC cells were isolated using ficoll gradient. They have been treated with IBET762 or DMSO as solvent control and ATAC Seq has been performed on them.

  Dataset EGAD00001008723

• Dataset to study clonal evolution in iAMP21 patient SJBALL021901 using scWGS-seq

  scWGS-seq of flow sorted blast and normal cells from SJBALL021901 with 71 high quality cells sequenced (67 blast and 4 normal)

  Dataset EGAD00001009755

• scRNA-seq data of BALF and blood cells from COPD and control

  Chronic obstructive pulmonary disease (COPD) is ranked the third leading cause of death worldwide and hence constitutes a significant burden, both medically and financially. To date, the cellular mechanism underlying COPD is poorly understood and thus no effective therapy is currently available. To broaden the current knowledge of the immune landscape in the alveolar space, we performed scRNA-Seq of CD45-enriched bronchoalveolar lavage fluid (BALF) cells and isolated blood leukocytes obtained from COPD patients and healthy controls using both the Seq-Well and the Chromium (10x Genomics) technology.

  Study EGAS00001004369

• 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

• ExpressionPDTX

  RNA Expression using Illumina HT12 v3

  Dataset EGAD00010001032

• SF4324 Primary Wildtype GBM Female, 57.

  Single Cell RNA-Seq of Primary GBM. Gender Female, Age, 57.

  Dataset EGAD00001006017

• dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

  The National Heart, Lung, and Blood Institute (NHLBI) Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research has concluded. The NHLBI will continue to make this collection of data available to the research community.Past information regarding the Data Collection for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research is below.The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is inviting novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and "other omics" data for more than one-hundred thousand individuals. To provide challenge participants with streamlined access to data across NHLBI's numerous studies containing heart failure data, the NHLBI has created this dbGaP study collection. Data access for this collection is controlled by NHLBI's Data Access Committee. Challenge participants are required to follow the use restrictions and acknowledgement instructions from the original dataset(s). Please note that the data in this collection are not harmonized across studies or otherwise altered from the original study. The NHLBI Big Data Analysis Challenge: Heart Failure Data Collection contains all NHLBI studies currently in dbGaP that contain data that may be relevant to research on heart failure. The studies in this collection are approved for General Research Use (GRU), Health/Medical/Biomedical Use (HMB), or Disease-Specific Use (DS) that permits research on heart failure. These studies span a variety of study designs, inclusion and exclusion criteria, sample sizes, and provide a wide breadth and depth of phenotype data on study participants. The available genomic data in these studies also varies, including genotyping arrays, sequencing (targeted, exome, whole genome), and additional -omic data (e.g., RNA or metabolite profiles). Please refer to each study's individual accession page to learn more about how study data were collected. Challenge participants are reminded that in addition to dbGaP, NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) contains other studies that have collected data relevant to heart failure and may wish to utilize BioLINCC data in the development of their Solution. Please refer to the individual accession page for each study in this collection to learn more about the history of each study.

  Study phs001991

• Gene Expression Signature in Normal Mammary Gland from 83 Breast Cancer Patients Indicates Pre-tumorous Changes and Adverse Outcomes

  This study assessed the transcriptomic profiles of 242 samples from 83 breast cancer patients with unfavorable outcomes, including paired uninvolved mammary gland samples collected at varying distances from primary lesions. As a reference, control samples from 53 mammoplasty individuals without cancer history were studied. A custom panel of 634 genes linked to breast cancer progression and metastasis was employed for expression profiling (targeted RNA sequencing), followed by whole-transcriptome (RNA sequencing) verification experiments and statistical analyses to discern molecular signatures and their clinical relevance.

  Study EGAS50000000011

• CIRCLE-seq of PDAC PDO

  CIRCLE-seq was performed on a PDAC PDO to validate the presence and the structure of ecDNAs

  Study EGAS50000000194

• Pancreatic cancer RNA sequencing

  Study EGAS00001004706

• TCGA WGS Variants Across 18 Cancer Types

  Even though whole genome sequence (WGS) data has been generated and published in many studies, much of this information is not yet processed for use in down-stream analysis. This study's aim is to provide 1342 WGS normal-tumor paired single nucleotide variations (SNP) over 18 different cancer types provided by The Cancer Genome Atlas (TCGA) project. Individual level data for TCGA can be accessed by requesting access for phs000178. This data includes variations within self-reported white and African-American populations. Variations that exist within the tumor tissue but are absent in associated normal organ tissue (as compared to the human reference genome) are reported. Data published includes SNP and small insertions and deletions, which were generated through a pipeline including the VarScan2 variant calling software.

  Study phs003155

• Longitudinal monitoring of cell-free DNA methylation in ALK-positive non-small cell lung cancer patients

  Here, we performed genome-wide 5-mC profiling in plasma of metastatic ALK-rearranged non-small cell lung cancer (NSCLC) patients receiving tyrosine kinase inhibitor therapy. We established a strategy to identify ALK-specific 5-mC changes from cfDNA and demonstrated the suitability of the identified markers for cancer detection, prognosis and therapy monitoring. Longitudinal plasma samples (n = 79) of 21 ALK-positive NSCLC patients and 13 healthy donors were collected alongside 15 ALK-positive tumor tissue and 10 healthy lung tissue specimens. All plasma and tissue samples were analyzed by cell-free DNA methylation immunoprecipitation sequencing to generate genome-wide 5-mC profiles. Information on genomic alterations (i.e., somatic mutations/fusions and copy number alterations) determined in matched plasma samples were available from previous studies.

  Study EGAS00001006573

• Cell-type eQTLs for single-cell Mendelian Randomisation

  The following study mapped eQTLs in the post-mortem human brain from snRNA-seq generated on 391 individuals. Following eQTL discovery and identification of state-specific eQTLs (dynamic associations interacting with disease), colocalisation and MR was performed integrating GWAS from 42 traits, for the identification of putatively causal genes with cell-type specific context. This study contains raw sequencing data and genotype for two datasets used in this work; - The MRC 60 dataset, which contains snRNA-seq generated on post-mortem brain from 60 control individuals (104 samples total, split across prefrontal cortex and hippocampus). Samples were pooled into 27 distinct pools, each of which was split across 4 lanes. Following sequencing and mapping using cellranger, demultiplexing was done using Demuxlet using the pool-specific genotype data (which contain sample IDs). - The Roche PD dataset, which is 10X multiome data generated on on 70 PD and 22 control individuals.

  Study EGAS50000000687

• Molecular Genetic Studies of Developmental Brain Disorders

  Study 1 2R01-NS050375 (PI: DOBYNS, William B.) The genetic basis of mid-hindbrain malformations Our general goal for this project is to advance our understanding of human developmental disorders that involve the brainstem and cerebellum - brain structures derived from the embryonic midbrain and hindbrain - that affect a minimum of 2.4 per 1000 resident births based on data from the CDC. Importantly, this large class of disorders co-occurs with more common developmental disorders such as autism, mental retardation and some forms of infantile epilepsy, and shares some of the same causes. With this renewal, we propose to expand the scope of our work beyond single phenotypes and genes to focus on delineating the critical phenotype spectra to which the most common MHM belong, and defining the underlying biological networks that are disrupted. To pursue these goals, we will use our large and growing cohort of human subjects to map additional MHM loci using SNP microarrays that provide both high-resolution autozygosity and linkage data in informative families as well as detect critical copy number variants in sporadic subjects. The causative genes will be identified using traditional Sanger or new high-throughput sequencing methods as appropriate abased on size of the critical region. We will use these and other known MHM causative genes to construct and revise model biological networks of genes and proteins, and test these genes and networks in additional patients as a candidate gene or more accurately a candidate network approach. These approaches need to be supported by ongoing active subject recruitment, as studies of comparable disorders such as mental retardation and autism have benefited from even larger numbers of subjects that we have so far collected. We need to use new high-throughput sequencing methods to more efficiently test larger critical regions, and to test entire gene networks rather than individual genes in matched cohorts of subjects. At every step; phenotype analysis, CNV analysis, model network construction and high-throughput sequencing, we will need expanded bioinformatics capabilities. Finally, we need to test the biological function of new genes and networks to support our gene identification studies. We expect that these studies will contribute immediately to more accurate diagnosis and counseling, and over time will lead to development of specific treatments for a subset of these disorders. We further expect that studies of mid-hindbrain development will have broad significance for human developmental disorders generally, providing compelling evidence for a connection between cerebellar development and other classes of developmental disorders such as autism, mental retardation and epilepsy. Study 2 R01-NS058721 (PI: DOBYNS, William B.) De novo copy number variation and gene discovery in human brain malformations Project Summary/Abstract The number of recognized brain malformations and syndromes has grown rapidly during the past several decades, yet relatively few causative genes have been identified, especially for three common malformations that have been associated with numerous cytogenetically visible chromosome deletions and duplications, and that often occur together: agenesis of the corpus callosum (ACC), cerebellar vermis hypoplasia (CVH) including Dandy-Walker malformation (DWM), and polymicrogyria (PMG). We propose to perform high-resolution array comparative genome hybridization (aCGH), emerging technology able to detect small copy number variants (CNV), in 700 probands with one or more of these three malformations. Our central hypothesis states that more than 10% of patients with ACC, CVH or PMG will have de novo CNV below the resolution of routine cytogenetic analysis, but detectable by current array platforms. We therefore expect to identify 70-100 patients with small CNV. We will distinguish CNV found in normal individuals from potentially disease-associated changes, and will confirm CNV using fluorescence in situ hybridization (FISH) and microsatellite (STRP) analysis. We will give highest priority to CNV that are de novo and involve 2 or more BACs, and secondary priority to familial and smaller CNV excluding known polymorphisms. After that, we will evaluate and rank candidate genes in the critical regions using information from public databases and our own expression studies, and perform mutation analysis of the best candidate genes from well-defined critical regions by sequencing in a large panel of subjects with phenotypes that match the phenotypes of the patients whose CNV define the critical regions. Here, we will use more refined criteria to supplement our clinical classification, such as the developmental level and presence of epilepsy or other birth defects. Any abnormalities found will be analyzed using existing data regarding polymorphisms (i.e. dbSNP), cross-species comparisons, and functional assays appropriate for the specific sequence change. Study 2A In 1995, we described a novel multiple congenital anomaly syndrome associated with facial dysmorphism (congenital ptosis, high arched eyebrows, shallow orbits, trigonocephaly), colobomas of the eyes, neuronal migration malformation (frontal predominant lissencephaly) and variable hearing loss. We hypothesized from de novo mutations and used trio-based exome sequencing to identify de novo mutations in the ACTB and ACTG1 genes. Study 2B In 1997 and 2004, we and others defined two novel developmental syndromes associated with markedly enlarged brain size, or megalencephaly, and other highly recognizable features. The megalencephaly-capillary malformation syndrome (MCAP) consists of megalencephaly and associated growth dysregulation with variable asymmetry, developmental vascular anomalies, distal limb malformations, variable cortical malformation, and a mild connective tissue dysplasia. The megalencephaly-polymicrogyria-polydactyly-hydrocephalus syndrome (MPPH) resembles MCAP but lacks vascular malformations and syndactyly. We hypothesized that MCAP and MPPH result from mutations - including postzygotic events - in the same pathway, and studied them together. Using a combination of exome sequencing, Sanger sequencing, restriction-enzyme assays, and targeted ultra-deep sequencing in 50 families with MCAP or MPPH, we identified de novo germline or postzygotic mutations in three core components of the phosphatidylinositol-3-kinase/AKT pathway. These include two mutations in AKT3, a recurrent mutation in PIK3R2, and multiple mostly postzygotic mutations in PIK3CA (Rivière JB, Mirzaa GM, O'Roak BJ, Beddaoui M, Alcantara D, Conway RL, St-Onge J, Schwartzentruber JA, Gripp KW, Nikkel SM, Worthylake T, Sullivan CT, Ward TR, Butler HE, Kramer NA, Albrecht B, Armour CM, Armstrong L, Caluseriu O, Cytrynbaum C, Drolet BA, Innes AM, Lauzon JL, Lin AE, Mancini GMS, Meschino WS, Reggin JD, Saggar AK, Lerman-Sagie T, Uyanik G, Weksberg R, Zirn B, Beaulieu CL, FORGE Canada Consortium, Majewski J, Bulman DE, O'Driscoll M, Shendure J, Graham Jr. JM, Boycott KM, Dobyns WB. De novo germline and postzygotic mutations in AKT3, PIK3R2 and PIK3CA cause a spectrum of related megalencephaly syndromes. Nat. Genet. In press). Study 3 2R01-NS046616 (PI: GOLDEN, Jeffrey A) The role of ARX in normal and abnormal brain development This subcontract from the Children's Hospital of Philadelphia to the University of Chicago (UC) is intended to support research studies of the ARX and functionally related genes in human subjects with any one of several specific developmental disorders. The Co-investigator at UC (W.B. Dobyns) will identify a series of patients with mental retardation and severe infantile epilepsy, some of whom will have specific brain malformations and others who will have normal brain structure by brain imaging studies, and collect research samples from these subjects with informed consent. The studies to be performed will include mutation analysis of ARX, mutation analysis of specific downstream target genes, X inactivation studies in humans and X inactivation studies in mutant mice. The results will be analyzed to determine the significance of any changes found in the gene.

  Study phs000455

• Separation, characterization, and identification of individuals from multi-person blood mixtures with single cell ATAC-seq

  We report a deconvolution and identification strategy of scATAC-seq datasets using mixed PMBCs data. After sequencing the data were processed with the de-goulash pipeline and analyzed with aim to identify and acquire biogeogrpahical ancestry of the involved individuals. The study includes samples of biological mixtures and in silico mixtures in different mixed ration and cell volumes.

  Study EGAS00001007380

• Microbiomic and immunogenic biomarkers of adjuvant chemotherapy efficacy in stage III colorectal cancer

  The standard treatment for stage III colorectal cancer (CRC) is surgery, followed by adjuvant chemotherapy (AC). However, the efficacy of AC is limited, and approximately 30% of patients experience recurrence. Therefore, easily assessable molecular biomarkers that can predict response to AC are needed. Here, we aimed to identify predictive biomarkers of response to AC using tumor transcriptomic data. Tumor specimens from 253 patients who underwent surgery for stage III CRC between 1997 and 2019 were analyzed using RNA sequencing. Transcriptional subtyping and analyses of gut microbiome, immune cell fractions, and T-cell receptor (TCR) were performed to identify factors associated with recurrence-free survival (RFS) in patients treated with or without AC. Of 253 patients, 118 (46.6%) received AC. Twenty phyla and 799 species of the microbiomes were identified, among which Fusobacteria were identified in 247 patients (97.6%). Multivariable Cox proportional hazards regression analysis of patients who received AC showed that intratumoral Fusobacterium and M1 macrophage abundance and diversity of TCR alpha and delta (TRAD) were independently associated with RFS. Fusobacterium and M1 macrophage abundance, and TRAD diversity were associated with the response to AC, suggesting that these factors could serve as biomarkers for personalized treatment in stage III CRC.

  Study JGAS000875

• Dataset for desmoplastic small round cell tumor - RNA

  This dataset contains 32 RNA sequencing samples of patients with desmoplastic small round cell tumor. Sequencing was performed on Illumina HiSeq 2500, Illumina HiSeq 4000, Illumina HiSeq X and NovaSeq 6000 using Illumina TruSeq RNA and TruSeq Stranded RNA Kit. The sequencing was always paired.

  Dataset EGAD50000000912

• Single nucleus and spatial transcriptomic characterization of prostate cancer versus normal controls

  10x Genomics Visium and Chromium platforms were used for spatial and single-nuclei RNA-sequencing, respectively. Cohort consisted of 8 prostate cancer patients (8 prostate cancer + 8 paired non-malignant control samples, fresh-frozen)

  Study EGAS50000001143

• Characterization of genetic intratumor heterogeneity in colorectal cancer and matching patient-derived spheroid cultures.

  Patient-derived in vitro cultures of colorectal cancer (CRC) may help guide treatment strategies prior to patient treatment. However, most previous studies have been performed on a single biopsy per tumor. The purpose of this study was to analyze multiple spatially distinct biopsies from CRCs and see how well intratumor heterogeneity (ITH) was recapitulated in matching patient-derived spheroids. Three to five biopsies were collected from six CRC tumors. Each biopsy was split in two; one half was used for spheroid culturing, the other half was used for direct DNA and RNA purification. For two of the patients, lymph node metastases were analyzed. Somatic mutations were called from whole exome sequencing data. Each tumor contained multiple mutations shared across all biopsies and spheroids, including major CRC drivers such as APC, KRAS, and TP53. At the same time, all tumors exhibited ITH on both mutation and copy number level. The concordance between biopsies and spheroids ranged between 40-70% for coding mutations. For three of the patients the biopsy and spheroid from matching areas clustered together, meaning that the spheroid resembled the area of origin more than the other areas. However, all biopsies and spheroids contained private mutations. Thereby, multiple cultures from spatially distinct sites of the tumor increase the insight into the genetic profile of the entire tumor. RNA sequencing based molecular subtyping was stable and seemed independent of genetic ITH. In conclusion, all examined CRC tumors contained genetic ITH on mutation and copy number level. Spheroid cultures partly reflected this ITH, meaning that multiple cultures from distinct sites of the tumor improved the representation of the different genetic subclones in the primary tumor. This should be taken in to account when establishing patient-derived models for drug screening.

  Study EGAS00001002684

• RNA Splicing Dysregulation in the Pathogenesis of Chronic Lymphocytic Leukemia

  RNA splicing dysregulation is a hallmark of cancers, promoting the onset and progression of disease. In chronic lymphocytic leukemia (CLL), spliceosome mutations leading to aberrant splicing occurs in approximately 20% of patients. However, the underlying mechanism for splicing defects in spliceosome unmutated CLL cases remains elusive. To discover posttranscriptional regulation of RNA splicing, we performed RNA sequencing using RNA derived from B cells from 6 healthy donors and 36 CLL patients, along with MAZTER sequencing from 9 CLL patients (8 matched with RNA sequencing cohort) and B cells from 5 healthy donors. We found that CLL cells have dysregulated m6A modification sites on transcripts from splicing factors, suggesting a critical role of m6A modification in RNA splicing dysregulation.

  Study phs003191

• PDAC organoid genomic heterogeneity

  Two primary tumor-derived PDAC organoids were subjected to SNP array, RNA-seq, and single-cell WGS

  Dataset EGAD00010002408

• SF10432 Wildtype Primary GBM Female, 50

  Single Cell-RNA Seq of Wildtype Primary GBM for Female, Age 50.

  Dataset EGAD00001006019

• RNAseq data for EGAS00001004572

  Bulk RNA-seq data of tumours in EGAS00001004572.

  Dataset EGAD00001006876