14977 results for "cancer studies using rna-seq"

in 35.98 milliseconds.

• Wnt Activity Reveals Context-Dependent Genetic Effects on Gene Regulation in Neural Progenitors

  In this study we aimed to identify context-dependent regulatory functions of common genetic variation after stimulation of the canonical Wnt pathway. Fetal cortical tissue between 14 and 21 gestation weeks was subjected to RNA-Sequencing (242 samples) and ATAC-Sequencing (222 samples) to profile expression and chromatin accessibility, respectively. Considering donor genotypes, we were able to identify eQTLs, caQTLs, as well as response QTLs of both categories. The dataset provided here includes 242 RNA-sequencing files in bam format and 222 ATAC-sequencing files in bam format. We also provide 83 donor genotypes in VCF format (hg38).

  Study phs003642

• Molecular Genetics of Heroin Dependence in China

  Our principal goal was to determine the chromosomal locations of genetic variations associated with increased vulnerability to heroin dependence. This goal was attained by identifying specific DNA markers that are genetically linked to heroin dependence. We collected blood and diagnostic information (using a structured diagnostic interview) from 1230 people (sib-pairs) having DSM-IV defined heroin dependence as well as from their parents and other affected and unaffected siblings, when possible. Genotype and clinical data was archived using database software. We conducted a multipoint linkage analysis using the guidelines of Lander and Kruglyak to assert statistical significance, and followed up on regions of interest with a dense set of markers to evaluate candidate genes.

  Study phs001213

• GA4GH

  Standards The EGA is a long-standing supporter of the Global Alliance for Genomics & Health (GA4GH) to enhance responsible sharing of human genetic data through the development of interoperable global standards for human data access. The EGA is one of the founding GA4GH Driver Projects and has contributed to the development and implementation of several GA4GH standards and APIs. Below is a list of the GA4GH standards and APIs that are currently available or planned for implementation at EGA. TechnicalStandards Purpose SpecificationVersion SupportedVersion Implementation Large Scale Genomics htsget A protocol for secure, efficient, and reliable access to sequencing read and variation data. V1.3.0 V1.0.0 Specification Documentation Endpoint Read File Formats (SAM/BAM/CRAM) Specifications for storing next-generation sequencing read data. V3.0.0 V3.0.0 Implementation Example of Usage Variation File Formats (VCF/BCF) The specifications for Variant Call Format Files (VCF) and its binary counterpart BCF. V4.0.0 V2.0.0 V4.0.0 V2.0.0 Implementation Example of Usage Crypt4GH v1.0 Enables direct byte-level compatible random access to encrypted genetic data stored in community standards (e.g. CRAM, VCF) V1.0 V1.0 Specification Documentation Endpoint refget API Enables access to reference sequences using an identifier derived from the sequence itself. V1.2.6 NA Specification RNAget API v1 Provides a means of retrieving data from several types of RNA experiments including (i) feature-level expression data from RNA-seq type measurements and (ii) coordinate-based signal/intensity data similar to a bigwig representation via a client/server model. V1.0.0 NA Documentation Discovery Beacon v2 Supports discovery of genomic variants, phenotypes, and individuals V1.0.1 V0.3 Web UI API Source Code Service Info API v1 The Service Info API is an endpoint for describing GA4GH service metadata, designed for extension and inclusion in other APIs. Service info is used to describe a single service, while Service Registry is used to describe multiple services. V1.0.0 NA Documentation Service Registry API v1 provides information about other GA4GH services, primarily for the purpose of organizing services into networks or groups and service discovery across organizational boundaries. V1.0.0 NA Documentation Data Use Researcher Identities Data Use Ontology (DUO) Allow users to semantically tag genomic datasets with usage restrictions, allowing them to become automatically discoverable based on a health, clinical, or biomedical researcher’s authorisation level or intended use. 2021-02-23 2021-02-23 Specification Documentation Endpoint Authentication & Authorization Infrastructure (AAI) The GA4GH AAI specification leverages OpenID Connect (OIDC) Servers for use in authenticating the identity of researchers desiring to access clinical and genomic resources from data holders adhering to GA4GH standards, and to enable data holders to obtain security-related attributes of those researchers. V1.2.0 V1.2.0 API URI: ega.ebi.ac.uk:8443 Documentation Repository Researcher IDs (passport, visa) Specify the collection of researchers that may access a dataset at any given time, and the credentials they must supply. V1.0.1 V1.0.1 Specification Documentation Endpoint Cloud Tool Registry Service API TRS is a standard API for exchanging tools and workflows to analyze, read, and manipulate genomic data. V2.0.1 NA Documentation Repostiory Data Repository Service API ​DRS API is a standard for building data repositories and adapting access tools to work with those repositories, works with other approved APIs from the GA4GH Cloud Work Stream to allow researchers to discover algorithms across different cloud environments and send them to datasets they wish to analyse. V1.0.3 NA Documentation Repostiory Workflow Execution Service API This API lets users run a single workflow (defined using CWL or WDL) on multiple different platforms, clouds, and environments, and be confident that it will work the same way. The API provides methods to request that a workflow be run, pass parameters to that workflow, get information about running workflows, and cancel a running workflow. V1.0.1 NA Documentation Repostiory Genomic Knowledge Standards Variation Representation v1 Provides a flexible framework of computational models, schemas, and algorithms to precisely and consistently exchange genetic variation data across communities. V1.3.0 EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Clin/ Pheno Data Capture Phenopackets Provides information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged. V2.0.0 Included in Ongoing Submissions EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Driver Project The EGA, jointly coordinated by the EBI and the CRG, was announced, in 2017, to be one of the 15 Driver Projects for GA4GH. Driver Projects are international genomic data initiatives, focussed on real projects and challenges that will guide the development efforts in order to accelerate and enable completely responsible and standarised data sharing by 2022. All chosen Driver Projects make a cross-sectional effort by playing an important role across the different workstreams. Thomas Keane, Jordi Rambla, Mallory Freeberg, and Aina Jené have been named Driver Project Champions for the EGA. All Driver Project Champions will be leading this ambitious initiative for the following years.

  Documentation about/projects-and-funders/ga4gh

• Adaptive long-read and transcriptome sequencing detail a submicroscopic inv(15)(q14q15), generating two fusion transcripts and MEIS2 and NUSAP1 haploinsufficiency

  Study an inversion affecting MEIS2 using ONT adaptive sequencing.

  Study EGAS50000000632

• Transcriptome analysis of Hepatitis B for drug discovery and clinical applications

  We analyzed blood transcriptome of HBV positive untreated patients (men) using the CAGE technology.

  Study JGAS000053

• Targeted sequencing using SPET for Mesothelioma.

  Targeted sequencing using SPET for Mesothelioma.

  Dataset EGAD00001001916

• Profiling of childhood neuroblastoma and the immune microenvironment by single-cell sequencing of RNA and TCR

  Neuroblastoma tumor cells and their tumor microenvironment are studied by single-cell RNA sequencing of primary neuroblastoma tumors and neuroblastoma-infiltrated tissues/metastases. Both diagnostic samples, taken pre-treatment and samples taken after induction chemotherapy at surgical resection and biopsies from relapse samples are included.  For a number of patients single-cell RNA sequencing of blood samples (controls) are included and additionally we performed single-cell T cell receptor sequencing (TCR) on the tumor and blood samples. With this study, we will focus on identifying differences in tumor cells and their (immune) microenvironment 1) before and after treatment or at relapse and 2) between primary tumors and infiltrated tissues/metastases. Moreover, with TCR sequencing we aim to unveil immune cell dynamics in patients with neuroblastoma.

  Study EGAS00001006823

• A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome

  We have carried out complete sequencing of the genome of the human male maligant melanoma cell line COLO-829 using the Illumina Genome Analyzer II. We generated a sequencing library with a median insert size of ~200 bp following random fragmentation and gel fractionation of the genomic DNA. We sequenced 75 bases from both ends of these templates to cover the COLO-829 genome to an average depth of more than 40x. We have carried out purity-filtering (PF) to remove mixed reads, where two or more different template molecules are close enough on the surface of the flow-cell to form a mixed or overlapping cluster. No other filtering of the data has been carried out prior to submission. We have also submitted sequence data for a lymphoblastoid control cell line COLO-829BL from the same individual.

  Study EGAS00000000052

• CNS Embryonal tumors

  The dataset represents a total of 58 DNA samples from 16 male and 12 female pediatric patients affected with embryonal central nervous system tumors. The samples were subject to whole genome sequencing, WGS, [48 samples, (representing 12 male and 11 female individuals)] and whole exome sequencing, WES, [10 samples, (representing 4 male and 1 female individuals)]. One tumor tissue sample and one peripheral blood sample were analyzed from each of 26 patients, whereas two tumor tissue samples and one peripheral blood sample were analyzed from two patients. The WGS samples were sequenced 2x150 bp paired-end on an Illumina HiSeqX v2.5 instrument, and the WES samples were sequenced 2x100 bp paired-end on an Illumina HiSeq 2500 instrument. The FASTQ files generated were aligned to the human reference genome sequence GRCh38/hg38 using bwa-mem, with the ALT-aware option turned on. Sorting of reads and marking of PCR duplicates was performed with GATK. Base quality score recalibration and joint realignment of reads around insertions and deletions (indels) were conducted using GATK tools. The dataset consists of 58 files in the CRAM format (lossless compression) with a total file size of ~8,8 TB. All CRAM files but one, are derived from one sequence run and one sample. P4551_227N_P4552_112N is a CRAM file where 2 sequence runs (P4551_227N and P4552_112N) from peripheral blood samples from the same individual, P019, were aligned into one single CRAM file. Additional genomic and molecular data (FASTQ, BAM, IDAT, and VCF files) and limited clinical data can be requested by ethically approved projects conducting research in the field of pediatric cancer.

  Dataset EGAD50000000298

• Immediate Postoperative Minimal Residual Disease Detection with MAESTRO Predicts Recurrence and Survival in Head and Neck Cancer Patients Treated with Surgery

  We selected 24 patients with locally advanced head and neck squamous cell carcinoma (HNSCC) who were surgically treated. MAESTRO, our ultrasensitive, tumor-informed, mutation enrichment sequencing assay, was applied in a pooled format (MAESTRO-Pool) to plasma samples collected from these patients at baseline (pre-op) and postoperatively. We show that detection of circulating tumor DNA (ctDNA) 1 to 9 days after surgery is associated with significantly worse survival. Many plasma samples also had tumor fractions detected below 100 parts-per-million, the detection limit for first-generation commercial assays, highlighting the need for more sensitive ctDNA assays. Here we provide whole genome sequencing of matched tumor biopsy and normal germline DNA from 24 patients that were used to identify somatic single nucleotide variants (SNVs) to be tracked using our MAESTRO-Pool assay.

  Study phs003981

• Effective screening strategy for deafness using a new-genetation sequencing platform: a consecutive analysis

  The diagnosis of the genetic etiology of deafness contributes to the clinical management of patients. We performed the following four genetic tests in three stages for 52 consecutive deafness subjects in one facility. We used the Invade assay and Sanger sequencing for the GJB2 gene or SLC26A4 gene in the first stage test, TaqMan genotyping assay in second stage test, and targeted exon sequencing using the massively parallel DNA sequencing in third stage test. Overall, we identified the genetic cause in 40% (21/52) of patients. The diagnostic rates of the first-, second- and third-stage genetic testing were 17%(9/52), 9%(4/43) and 21% (8/39), respectively. The combination approach using these genetic tests appears to be useful as a diagnostic tool for deafness patients. We recommended that genetic testing for the screening of common mutations in deafness genes using the Invader assay or TaqMan genotyping assay be performed as the initial evaluation. For the remaining undiagnosed cases, targeted exon sequencing using MPS is clinically and economically beneficial. This data set was MPS reads data (fastq) for 39 sensorineural hearing loss patients.

  Study JGAS000032

• Chromatin accessibility analysis of epidermal keratinocytes from psoriatic, clinically healed, and healthy control skin

  This study uses ATAC-seq to analyze epidermal keratinocytes from psoriatic lesions, clinically healed skin of the same patients, and healthy control skin. The aim is to elucidate chromatin accessibility changes associated with psoriasis pathogenesis and remission from 6 lesional, 6 healed, and 5 control samples.

  Study JGAS000844

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_T=24hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_T=24hrs sample(s). 7 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002474

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_LPS_T=24hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_LPS_T=24hrs 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002388

• BLUEPRINT release August 2016, ChIP-Seq for conventional dendritic cell, on genome GRCh38

  ChIP-Seq data for 1 conventional dendritic cell sample(s). 4 run(s), 4 experiment(s), 4 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002310

• BLUEPRINT release August 2016, ChIP-Seq for unswitched memory B cell, on genome GRCh38

  ChIP-Seq data for 1 unswitched memory B cell sample(s). 7 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002282

• BLUEPRINT release August 2016, ChIP-Seq for CD8-positive, alpha-beta thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD8-positive, alpha-beta thymocyte 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002494

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - T=0days, on genome GRCh38

  ChIP-Seq data for 2 monocyte - T=0days sample(s). 7 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002491

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=1hr, on genome GRCh38

  ChIP-Seq data for 2 monocyte - RPMI_BG_T=1hr sample(s). 6 run(s), 6 experiment(s), 6 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002297

• BLUEPRINT release August 2016, ChIP-Seq for inflammatory macrophage, on genome GRCh38

  ChIP-Seq data for 9 inflammatory macrophage sample(s). 58 run(s), 58 experiment(s), 58 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002515

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=24hrs_RPMI_T=5days, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=24hrs_RPMI_T=5days sample(s). 7 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002517

• BLUEPRINT release August 2016, ChIP-Seq for germinal center B cell, on genome GRCh38

  ChIP-Seq data for 4 germinal center B cell sample(s). 24 run(s), 22 experiment(s), 22 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002442

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_T=1hr, on genome GRCh38

  ChIP-Seq data for 2 monocyte - RPMI_T=1hr sample(s). 4 run(s), 4 experiment(s), 4 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002453

• BLUEPRINT release August 2016, ChIP-Seq for band form neutrophil, on genome GRCh38

  ChIP-Seq data for 4 band form neutrophil sample(s). 26 run(s), 23 experiment(s), 23 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002454

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MS-275 (20h), on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MS-275 (20h) sample(s). 5 run(s), 5 experiment(s), 5 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002493

• BLUEPRINT release August 2016, Bisulfite-Seq for CD3-positive, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  Bisulfite-Seq data for 2 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte sample(s). 29 run(s), 2 experiment(s), 4 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002325

• BLUEPRINT release August 2016, ChIP-Seq for segmented neutrophil of bone marrow, on genome GRCh38

  ChIP-Seq data for 4 segmented neutrophil of bone marrow sample(s). 24 run(s), 23 experiment(s), 23 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002390

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - Attached_T=1hr, on genome GRCh38

  ChIP-Seq data for 3 monocyte - Attached_T=1hr sample(s). 8 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002415

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=4hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=4hrs 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002368

• BLUEPRINT release August 2016, ChIP-Seq for immature conventional dendritic cell - GM-CSF_IL4_T=6_days, on genome GRCh38

  ChIP-Seq data for 3 immature conventional dendritic cell - GM-CSF_IL4_T=6_days sample(s). 20 run(s), 20 experiment(s), 20 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002485

• BLUEPRINT release August 2016, ChIP-Seq for memory B cell, on genome GRCh38

  ChIP-Seq data for 1 memory B cell sample(s). 1 run(s), 1 experiment(s), 1 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002510

• BLUEPRINT release August 2014, ChIP-Seq for CD14-positive, CD16-negative classical monocyte

  ChIP-Seq data for 9 CD14-positive, CD16-negative classical monocyte sample(s). 59 run(s), 55 experiment(s), 55 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000913

• Comparison of protocols for deriving pancreatic progenitors from hPSCs (ATAC-seq)

  This dataset contains 27 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared ATAC-seq libraries for the 27 samples, and sequenced them on Illumina HiSeq4000.

  Dataset EGAD00001004824

• BLUEPRINT release August 2016, Bisulfite-Seq for effector memory CD8-positive, alpha-beta T cell, terminally differentiated, on genome GRCh38

  Bisulfite-Seq data for 2 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 34 run(s), 3 experiment(s), 4 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002346

• BLUEPRINT release August 2016, ChIP-Seq for regulatory T cell, on genome GRCh38

  ChIP-Seq data for 2 regulatory 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002293

• BLUEPRINT release August 2016, ChIP-Seq for Activated B-Cell-Like Diffuse Large B-Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 3 Activated B-Cell-Like Diffuse Large B-Cell Lymphoma sample(s). 12 run(s), 12 experiment(s), 12 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002307

• BLUEPRINT release August 2016, ChIP-Seq for mature neutrophil, on genome GRCh38

  ChIP-Seq data for 10 mature neutrophil sample(s). 105 run(s), 86 experiment(s), 86 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002449

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs sample(s). 7 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002512

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days sample(s). 7 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002448

• BLUEPRINT release August 2015, ChIP-Seq for CD38-negative naive B cell, on genome GRCh38

  ChIP-Seq data for 6 CD38-negative naive B cell sample(s). 20 run(s), 20 experiment(s), 20 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001594

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_T=6days_LPS_T=4hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_T=6days_LPS_T=4hrs sample(s). 8 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002495

• BLUEPRINT release August 2016, ChIP-Seq for CD38-negative naive B cell, on genome GRCh38

  ChIP-Seq data for 9 CD38-negative naive B cell sample(s). 48 run(s), 44 experiment(s), 44 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002524

• BLUEPRINT release January 2015, ChIP-Seq for CD4-positive, alpha-beta T cell

  ChIP-Seq data for 7 CD4-positive, alpha-beta T cell sample(s). 46 run(s), 45 experiment(s), 45 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001147

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

  ChIP-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 11 run(s), 11 experiment(s), 11 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001559

• BLUEPRINT release January 2015, ChIP-Seq for endothelial cell of umbilical vein (resting)

  ChIP-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 10 run(s), 10 experiment(s), 10 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001183

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_LPS_T=1hr, on genome GRCh38

  ChIP-Seq data for 2 monocyte - RPMI_LPS_T=1hr sample(s). 8 run(s), 6 experiment(s), 6 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002376

• BLUEPRINT release August 2016, ChIP-Seq for alternatively activated macrophage, on genome GRCh38

  ChIP-Seq data for 7 alternatively activated macrophage sample(s). 50 run(s), 49 experiment(s), 49 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002317

• BLUEPRINT release August 2016, ChIP-Seq for class switched memory B cell, on genome GRCh38

  ChIP-Seq data for 3 class switched memory B cell sample(s). 21 run(s), 21 experiment(s), 21 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002430

• BLUEPRINT release August 2014, ChIP-Seq for CD4-positive, alpha-beta T cell

  ChIP-Seq data for 3 CD4-positive, alpha-beta T cell sample(s). 21 run(s), 21 experiment(s), 21 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000925

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days_LPS_T=4hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_LPS_T=24hrs_RPMI_T=5days_LPS_T=4hrs sample(s). 7 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002296

• BLUEPRINT release August 2016, ChIP-Seq for CD4-positive, alpha-beta thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD4-positive, alpha-beta thymocyte sample(s). 3 run(s), 3 experiment(s), 3 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002386

• BLUEPRINT release August 2016, ChIP-Seq for adult endothelial progenitor cell, on genome GRCh38

  ChIP-Seq data for 2 adult endothelial progenitor cell sample(s). 16 run(s), 14 experiment(s), 14 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002487

• BLUEPRINT release August 2015, ChIP-Seq for germinal center B cell, on genome GRCh38

  ChIP-Seq data for 2 germinal center B cell sample(s). 12 run(s), 11 experiment(s), 11 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001502

• BLUEPRINT release August 2015, ChIP-Seq for mature neutrophil, on genome GRCh38

  ChIP-Seq data for 9 mature neutrophil sample(s). 48 run(s), 45 experiment(s), 45 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001508

• BLUEPRINT release January 2015, ChIP-Seq for central memory CD4-positive, alpha-beta T cell

  ChIP-Seq data for 1 central memory CD4-positive, alpha-beta T cell sample(s). 6 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001144

• BLUEPRINT release January 2015, ChIP-Seq for CD14-positive, CD16-negative classical monocyte

  ChIP-Seq data for 10 CD14-positive, CD16-negative classical monocyte sample(s). 73 run(s), 69 experiment(s), 69 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001179

• BLUEPRINT release August 2016, ChIP-Seq for endothelial cell of umbilical vein (proliferating), on genome GRCh38

  ChIP-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 14 run(s), 14 experiment(s), 14 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002424

• BLUEPRINT release January 2015, ChIP-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  ChIP-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001182

• BLUEPRINT release August 2015, ChIP-Seq for CD8-positive, alpha-beta thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD8-positive, alpha-beta thymocyte 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001568

• BLUEPRINT release January 2015, ChIP-Seq for effector memory CD8-positive, alpha-beta T cell

  ChIP-Seq data for 2 effector memory CD8-positive, alpha-beta T cell sample(s). 10 run(s), 10 experiment(s), 10 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001127

• BLUEPRINT release August 2015, Bisulfite-Seq for effector memory CD8-positive, alpha-beta T cell, terminally differentiated, on genome GRCh38

  Bisulfite-Seq data for 1 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 15 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_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001541

• BLUEPRINT release August 2014, ChIP-Seq for CD8-positive, alpha-beta T cell

  ChIP-Seq data for 2 CD8-positive, alpha-beta T cell sample(s). 13 run(s), 13 experiment(s), 13 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000936

• BLUEPRINT release January 2015, ChIP-Seq for CD8-positive, alpha-beta T cell

  ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 28 run(s), 28 experiment(s), 28 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001154

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

  ChIP-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 12 run(s), 12 experiment(s), 12 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001487

• BLUEPRINT release August 2015, ChIP-Seq for band form neutrophil, on genome GRCh38

  ChIP-Seq data for 4 band form neutrophil sample(s). 18 run(s), 17 experiment(s), 17 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001511

• BLUEPRINT release August 2015, ChIP-Seq for alternatively activated macrophage, on genome GRCh38

  ChIP-Seq data for 4 alternatively activated macrophage sample(s). 22 run(s), 22 experiment(s), 22 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001514

• BLUEPRINT release August 2015, ChIP-Seq for CD4-positive, alpha-beta thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD4-positive, alpha-beta thymocyte 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001584

• BLUEPRINT release August 2015, ChIP-Seq for inflammatory macrophage, on genome GRCh38

  ChIP-Seq data for 7 inflammatory macrophage sample(s). 36 run(s), 36 experiment(s), 36 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001589

• Tapestri snDNA-seq data along with matched bulk data for validation

  Files from Tapestri snDNA-seq of archival tissue samples from 16 pancreatic ductal adenocarcinoma (PDAC) patients. Matched bulk sequencing (whole-exome, whole-genome, MSK-IMPACT) data are attached for a subset of the patients.

  Dataset EGAD00001009735

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

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

  Dataset EGAD00001011820

• BLUEPRINT release January 2015, ChIP-Seq for endothelial cell of umbilical vein (proliferating)

  ChIP-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 13 run(s), 13 experiment(s), 13 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001136

• BLUEPRINT release January 2015, ChIP-Seq for cytotoxic CD56-dim natural killer cell

  ChIP-Seq data for 4 cytotoxic CD56-dim natural killer cell sample(s). 16 run(s), 16 experiment(s), 16 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001158

• BLUEPRINT release January 2015, ChIP-Seq for CD38-negative naive B cell

  ChIP-Seq data for 4 CD38-negative naive B cell sample(s). 14 run(s), 14 experiment(s), 14 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001207

• BLUEPRINT release August 2015, ChIP-Seq for naive B cell, on genome GRCh38

  ChIP-Seq data for 6 naive B cell sample(s). 34 run(s), 28 experiment(s), 28 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001519

• BLUEPRINT release August 2015, ChIP-Seq for adult endothelial progenitor cell, on genome GRCh38

  ChIP-Seq data for 1 adult endothelial progenitor cell sample(s). 8 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001554

• BLUEPRINT release August 2015, ChIP-Seq for macrophage, on genome GRCh38

  ChIP-Seq data for 12 macrophage sample(s). 49 run(s), 49 experiment(s), 49 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001576

• BLUEPRINT release August 2015, ChIP-Seq for segmented neutrophil of bone marrow, on genome GRCh38

  ChIP-Seq data for 4 segmented neutrophil of bone marrow sample(s). 20 run(s), 19 experiment(s), 19 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001588

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - T=10day_RANK_M-CSF, on genome GRCh38

  ChIP-Seq data for 1 monocyte - T=10day_RANK_M-CSF 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002420

• BLUEPRINT release August 2016, ChIP-Seq for naive B cell, on genome GRCh38

  ChIP-Seq data for 15 naive B cell sample(s). 67 run(s), 59 experiment(s), 59 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002466

• BLUEPRINT release August 2016, ChIP-Seq for endothelial cell of umbilical vein (resting), on genome GRCh38

  ChIP-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 13 run(s), 13 experiment(s), 13 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002488

• Combining dasatinib and IFN-α in CML – immunomodulatory effects linked to treatment response and adverse events

  We pooled 100,000 cells from the 12 scRNA+TCRab-seq samples from peripheral blood from three time points (n=4, samples at 0, 3, and 12 months) to understand the landscape of immune subsets in CML during the course of dasatinib+IFN-α treatment

  Study EGAS00001005049

• PEDS-PLAN - Pediatric Precision Laboratory Advanced Neuroblastoma Therapy

  A multi-center clinical trial for newly diagnosed high-risk neuroblastoma patients. Molecular tumor boards selected one of six targeted agents based on tumor-normal whole exome sequencing and tumor RNA sequencing data.

  Study phs002303

• Effects of GATA4-inhibiting compound 3i-2012 on HB-243 hepatoblastoma cells

  In order to study the effects of GATA4 inhibition, HB-243 hepatoblastoma cells were treated with GATA4-inhibiting compound 3i-2012 for 24 hours. Total RNA was extracted and sequenced.

  Study EGAS50000000999

• RNA sequencing and whole-genome mate-pair sequencing of osteosarcoma

  This data set includes 72 mate pair sequenced osteosarcomas (36 as part of a discovery cohort and 36 as part of a validation cohort). It also includes RNA-sequencing data on 67 osteosarcomas (mostly overlapping with the above mate pair sequenced cases) and 13 osteoblastomas used as controls for gene expression levels.

  Dataset EGAD00001005307

• Illumina 5'end RNA sequencing

  The dataset contains 200 fastq files of Illumina 5'end RNA sequencing data of 50 PBMC samples. The paired-end data includes 100 fastq files (R1 and R2) of 50 full-length cDNA sequencing libraries and 100 fastq files (R1 and R2) of 50 HLA amplicon sequencing libraries.

  Dataset EGAD00001006838

• RNA data for medulloblastoma samples (ICGC)

  RNA sequencing data for 170 medulloblastoma tumor samples

  Dataset EGAD00001003279

• 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

• Blood and skin fibroblasts PSA study

  This dataset contains RNA-sequencing of blood samples from Healthy Controls (n=7), PSA patients (n=27) and RA patients (n=9). It also contains RNA-sequencing data of skin fibroblasts from healthy controls (n=3) and PSA patients (n=3).

  Dataset EGAD00001009069

• Single-cell RNA sequencing of chronic-phase chronic myeloid leukemia patients

  Single-cell RNA sequencing of viably frozen cells from 12 samples from four chronic-phase chronic myeloid leukemia patients. The raw data is available as fastq files.

  Dataset EGAD00001009086

• Ovarian Carcinosarcoma DNA and RNA sequencing of patient samples in the UK cohort.

  Ovarian Carcinosarcoma DNA and RNA sequencing of patient samples in the UK cohort (n=18).

  Dataset EGAD00001011068

• 3D-GSC_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG-derived glioma stem cell (GSC) models. Twenty-two primary GSC models derived from biopsies collected at diagnosis were cultured in an ECM-mimicking compound before for RNA extraction and subsequent rRNA-depletion and sequencing .

  Dataset EGAD00001011079

• RNA sequencing data from children with febrile illness and multisystem inflammatory syndrome in children (MIS-C)

  RNA sequencing data from children with febrile illness and multisystem inflammatory syndrome in children (MIS-C). Samples used were Whole Blood. Febrile illness controls include children with bacterial and viral infections and healthy controls. This dataset contains samples from patients recruited into the DIAMONDS study.

  Dataset EGAD00001011134

• Chromatin Landscape of BET Inhibitor-Treated CD8+ T-cells from Chronic Lymphocytic Leukemia Patients

  The pan-BET (bromodomain and extra-terminal) inhibitor, OPN-51107 (OPN5) was found to alleviate features of T-cell exhaustion in models of chronic lymphocytic leukemia (CLL). To evaluate if OPN5 treatment could relieve fixed chromatin states associated with terminal T-cell dysfunction, ATAC-sequencing was performed on CLL patient T-cells. Peripheral blood mononuclear cells (PBMCs) from 4 treatment-naïve CLL patients were treated ex vivo with 0.5 μM OPN5 or equivalent vehicle (DMSO) in the presence of T-cell activating stimuli (10 μg/mL anti-CD3 and 5 μg/mL anti-CD28) for 16 hours. Live CD8+ T-cells were then isolated via fluorescence-activated cell sorting, and approximately 100,000 viable CD8+ T-cells were subjected to ATAC-sequencing. Libraries were prepared using the Active Motif ATAC-seq kit and underwent paired-end sequencing (2 x 50 bp, 100 cycles) on an Illumina NovaSeq 6000 SP sequencer. Analysis of this data revealed that OPN5 treatment induces a unique chromatin landscape in CLL patient T-cells that is less like that of terminally exhausted T-cells and more like that of effector and memory T-cells. In particular, OPN5 treatment reduced chromatin accessibility at promoter regions of terminal exhaustion-associated genes (e.g., CD101, CCR5, LAG3, BATF3) and increased chromatin accessibility at promoter regions of genes associated with progenitor T-cell function (e.g., TCF7, IL2, CXCR5, IFNG). Individual raw sequencing (fastq) files and processed bigwig files (aligned to the hg38 human reference genome), as well as bigwig files for grouped OPN5- and vehicle-treated samples (aggregate of all 4 patient samples per treatment group) are available via authorized access request through dbGaP.

  Study phs003613

• H3K4me3, IgG, and Input ChIP-seq in overexpression of pLV Control, CS-FL and CS-ΔEx4 in SW1116 cells.

  none

  Study EGAS00001008121

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Uzbeks (DNA samples from the Institute of Immunology, Uzbek Academy of Sciences, Tashkent, Uzbekistan; Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology, Tashkent, Uzbekistan)

  Whole genome sequencing of 100 unrelated Uzbeks in order to impute genotypes into PE cases and controls from Uzbekistan and to provide genetic data and infrastructure for future genetic studies in Uzbekistan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This dataset is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology.

  Dataset EGAD00001005466

• University of Illinois at Chicago (UIC) Autism Centers of Excellence (ACE) Exome Sequencing Analysis

  Autism spectrum disorder (ASD) is highly heritable with recent sibling recurrence risk estimates of 19% overall and 26% in males. The heritable phenotype of hyperserotonemia, or elevated levels of platelet serotonin (5HT), in ~35% of people with ASD is a well-established biomarker. The efficacy of drugs like risperidone and potent serotonin transporter inhibitors at treating behaviors related to Insistence on Sameness, along with evidence of the contribution of hyperserotonemia to autism susceptibility collectively support the hypothesis that dysfunction in the 5HT system is a significant etiological target for investigation of the genetic component to autism. ASD genetic architecture is complex; common variants of large effect do not contribute substantially to overall ASD risk, but there are clearly common variants with small effects and rare genetic/genomic variation of larger effect among ASD genetic risk factors. The NIH ARRA Autism Sequencing Consortium, including Dr. Sutcliffe and Dr. Cook among others, has initiated exome sequencing studies to identify more of the rare variants contributing to ASD. Data from our group and others reveal numerous rare de novo and inherited sequence mutations, and the number of de novo and other functional mutations that are found to affect molecules encoding 5HT signaling and its regulation further reinforces our hypothesis that regulation of serotonin levels is important in autism genetic susceptibility. Integrin receptor signaling pathways were prominently featured among identified de novo mutations, thus defining a set of interrelated gene networks that control 5HT signaling. We propose to extend our findings to date by conducting exome sequencing on ACE subjects, for whom we also have 5HT biochemical data, to identify rare variants (including CNVs) in 5HT-related gene networks. In total we propose to have exome sequencing completed on 523 samples. The purpose of the proposed research is two-fold: 1) we will conduct more extensive investigations to determine the support for the hypothesis that genetic variation at genes regulating platelet serotonin levels affect susceptibility to ASD and 2) we will combine the exome sequence data from these studies with sequence data for autism being accumulated in a variety of other research projects to further the goal of identifying and characterizing the genetic component to ASD.

  Study phs000712

• The Atherosclerosis Risk in Communities (ARIC) Study

  The Atherosclerosis Risk in Communities (ARIC) Study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective epidemiologic study conducted in four U.S. communities. The four communities are Forsyth County, NC; Jackson, MS; the northwest suburbs of Minneapolis, MN; and Washington County, MD. ARIC is designed to investigate the etiology and natural history of atherosclerosis, the etiology of clinical atherosclerotic diseases, and variation in cardiovascular risk factors, medical care and disease by race, gender, location, and date. ARIC includes two parts: the Cohort Component and the Community Surveillance Component. The Cohort Component began in 1987, and each ARIC field center randomly selected and recruited a cohort sample of approximately 4,000 individuals aged 45-64 from a defined population in their community. A total of 15,792 participants received an extensive examination, including medical, social, and demographic data. These participants were reexamined every three years with the first screen (baseline) occurring in 1987-89, the second in 1990-92, the third in 1993-95, and the fourth and last exam was in 1996-98. Follow-up occurs yearly by telephone to maintain contact with participants and to assess health status of the cohort. In the Community Surveillance Component, currently ongoing, these four communities are investigated to determine the community-wide occurrence of hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years. Hospitalized stroke is investigated in cohort participants only. Starting in 2006, the study conducts community surveillance of inpatient (ages 55 years and older) and outpatient heart failure (ages 65 years and older) for heart failure events beginning in 2005. ARIC is currently funded through January 31, 2012. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to atherosclerosis and cardiovascular disease through large-scale genome-wide association studies of well-characterized cohorts of adults in four defined populations. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000090

• UK10K RARE COLOBOMA

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. Ocular coloboma is the most common significant developmental eye defect with an incidence of ~1 in 5,000 live births. It results from failure of optic fissure closure during embryogenesis. The position and extent of the fusion failure dictates the clinical appearance and functional effect. ~30% of coloboma cases are associated with other systemic malformations. These UK10K samples will mostly comprise isolated coloboma cases without systemic involvement (aka non-syndromal coloboma). There is strong evidence from family studies that coloboma has a major genetic component with autosomal dominance being the most common pattern of inheritance. However, many cases are isolated or show complex patterns of familial clustering. The genes responsible for isolated coloboma are largely unknown, but in a small number of families mutations in SHH, CHX10, and PAX6 have been identified indicating marked genetic heterogeneity. Thus in addition to the clinical benefits of achieving a molecular diagnosis there are also major scientific advantages to identifying coloboma genes, as these are likely to provide insights into the complex process of optic fissure closure, that is critical to normal eye development. In the longer term, understanding the molecular basis of the disease may provide clues to therapeutic strategies.For further information with regard to this cohort please contact David Fitzpatrick (david.fitzpatrick@ed.ac.uk).

  Study EGAS00001000127

• RNA Sequencing of Surgically Resected Colorectal Liver Metastases

  Dac EGAC00001000904

• RNA sequencing of sorted human RCC immune populations

  Dac EGAC00001002861