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• SAFIR02_Agilent

  Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_agilent)

  Dataset EGAD00010002243

• AS_genotyping

  AS genotyping data for lead SNPs using Illuminia Global Array V2.0

  Dataset EGAD00010002476

• DAC for the study molecular biomarkers associated with the diagnosis and severity of genetic and diseases from PAIDI-BIO354 GENYO-UGR)

  Dac EGAC00001003090

• WES for cell lines UWB1.289 and COV362

  exon 11 mutated UWB1.289 and COV362 cell lines

  Dataset EGAD50000000189

• DAC for BCP-LBL Kiel

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

  Dac EGAC50000000181

• DAC for study involving the spatial transcriptomics analysis of HPV-dependent and HPV-independent vulval squamous cell carcinoma at Imperial College London.

  Dac EGAC00001003515

• Structural and Non-Coding Variants Increase the Diagnostic Yield of Clinical Whole Genome Sequencing for Rare Diseases

  Study EGAS00001007575

• Human embryo ATAC+RNA single cell sequencing samples DAC (Linnarsson)

  DAC for human embryo ATAC+RNA single cell sequencing samples

  Dac EGAC50000000657

• Linnarsson lab general data access committe

  Committee that handles the majority of policies for the Linnarsson Lab at Karolinska Institutet

  Dac EGAC50000000835

• DAC for datasets from study 'Single-nucleus multi-omic sequencing of the human motor cortex in ALS/ALS-FTD'

  Dac EGAC50000000856

• Complete Genomics dataset for study EGAS00001002275.

  TBD

  Dataset EGAD00001003187

• FGFP_16S

  Firs 1106 16S rDNA data for the Flemish Gut Flora Project

  Dataset EGAD00001001936

• Aggregated count table

  RNA-seq count matrix for 296 bulk pre-treatment tumors from IMblaze370

  Dataset EGAD00001008552

• ICGC_Pedbrain_WGBS_Pilocytic_Astrocytoma

  18 WGBS lanes for 9 samples of pilocytic astrocytoma.

  Dataset EGAD00001005504

• A Genome-Wide Association Analysis in Angiotensin-Converting Enzyme (ACE) Inhibitor-Associated Angioedema and ACE Inhibitor-Exposed Controls; A Collaboration between the NIH Pharmacogenomics Research Network and the RIKEN Yokohama Center for Genomic Medicine

  The purpose of this study is to identify genetic predictors of ACE inhibitor-associated angioedema. In addition to preventing the formation of the pressor angiotensin II, ACE inhibitors prevent the carboxyl-terminal degradation of the vasoactive substances bradykinin and substance P. Angioedema is hypothesized to result from defective amino-terminal degradation of bradykinin or substance P in patients in whom ACE is inhibited. For example, activity of dipeptidyl peptidase IV (DPP-IV), the enzyme responsible for the inactivation of substance P when ACE is inhibited, is decreased in patients with angioedema. In preliminary studies, we have identified SNPs in the DPP4 gene that associate with DPP-IV activity and, in blacks, with risk of angioedema. This project will use genome-wide genotyping to compare 250 cases and 568 ACE inhibitor-exposed control subjects (131 cases and 288 controls ascertained at Vanderbilt and 70 cases and 280 controls ascertained at the Marshfield Clinic). We plan a 2-stage analysis of associations between SNPs and angioedema - first, we will study DPP4 SNPs for association with angioedema and, second, we will explore associations using the full GWAS data set. Depending on the platform, additional DPP4 SNPs will be used to fully tag common genetic variants in both African American and European American samples. Based on the HapMap data, there are 14 tagging SNPs in people of European descent and 34 in Yoruba (selection criteria MAF>0.05 and r2>0.8). Cases were defined as having ACE inhibitor-associated angioedema if they had had swelling of the lips, throat, tongue or face while taking an ACE inhibitor but had never had angioedema while not taking an ACE inhibitor. For simplicity, intestinal edema was excluded. Control subjects were treated for at least 6 months with an ACE inhibitor without angioedema. Because black Americans are known to be overrepresented among patients with ACE inhibitor-associated angioedema, control subjects were prespecified to be 50% black American, 50% white American, and 50% female. At Vanderbilt, the medical history, including the history of angioedema, was confirmed by a research nurse or physician using a detailed case report form. Characteristics of Vanderbilt cases appear in the Table. At Marshfield, medical history will be confirmed by chart review. The Marshfield cohort is 98% white American and 57% female with a mean age of 47.2 years.

  Study phs000438

• DNA methylomes of monozygotic twins clinically discordant for multiple sclerosis

  Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system. Although genetic susceptibility is important, a modest concordance rate for MS in monozygotic (MZ) twins suggests that interaction with other risk factors is required to develop clinical symptoms. In this study, we examined whether DNA methylation differences contribute to the discordant clinical manifestation of MS in MZ twins, and studied the impact of MS treatments on the DNA methylome. Genome-wide DNA methylation profiles of peripheral blood mononuclear cells (PBMCs) of 45 MZ twins clinically discordant for MS were generated using the Illumina HumanMethylationEPIC array. Repetitive element methylation and selected differentially methylated positions (DMPs) were validated using targeted deep bisulfite sequencing (TDBS). In addition, we performed whole genome bisulfite sequencing (WGBS) to profile CD4+ memory T-cells of a subset of four MS discordant MZ twins. Our results show that interferon treatment causes robust DNA methylation changes and several epigenetic biomarkers for interferon treatment response were identified. However, overall the PBMC-based methylomes of the MS discordant MZ twins were highly similar, since large systematic methylation differences (>5%) were absent in the data. This suggests that previously reported large methylation changes are probably caused by genetic rather than epigenetic differences. In addition, our data does not support the hypothesis that the observed maternal parent-of-origin effect in MS is due to genomic imprinting errors, and no evidence was found that copy number variations explain the discordant phenotype in these MZ twins. Although not genome-wide significant, a couple of DMPs associated with the MS phenotype were identified and successfully technically replicated using TDBS, including a differentially methylated region (DMR) in the promoter of the transmembrane protein encoding gene TMEM232. Another MS-associated DMP, located in an enhancer in the gene body of the transcription factor ZBTB16, was also associated with medium-term glucocorticoid treatment history. WGBS analysis confirmed this DMP as a promising epigenetic biomarker for glucocorticoid treatment. In conclusion, this epigenome-wide association study (EWAS) in genetically identical twins identified a DMR in the TMEM232 promoter as a candidate loci associated with the clinical manifestation of MS. In addition, epigenetic biomarkers for MS treatments were identified, revealing that not only short-term, but also medium-term treatment effects are detectable in immune cells, which should be taken into account in future EWAS designs.

  Study EGAS00001003147

• NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai

  The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises >42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants are enrolled through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a "data-broker" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry. BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers a great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden. Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individuals with COPD (62% women) and 1800 individuals as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included.

  Study phs001644

• DMET Genes, Nicotine Metabolism and Prospective Abstinence

  This study (DA033813; PI: Andrew W Bergen; PMID:26132489) includes samples from two laboratory studies of nicotine metabolism. The Pharmacokinetics of Nicotine Metabolism in Twins study (PKTWIN; PI: Gary E Swan; PMID: 15527659) was based on recruitment from a twin registry (PMID: 23084148). The Integrated Research Project on Tobacco Use and Dependence (IRP; PI: Gary E Swan; PMID: 14578134) was based on recruitment from a pedigree-based longitudinal study of risk factors for substance use, the Smoking in Families study (SMOFAM; DA03706; PI: Hy Hops). These two laboratory studies (PKTWIN and IRP/SMOFAM) served as the Stage I dataset to interrogate Drug Metabolizing Enzyme and Transporter genes with a targeted SNP array for association with the Nicotine Metabolite Ratio (NMR, ratio of trans-3'-hydroxycotinine and cotinine), an established biomarker of nicotine metabolism. In addition to the laboratory studies, samples from eight RCTs (PMID: 23249876) with the NMR and smoking-related measures used to test SNPs identified in Stage I (PMID: 26132489). In a third stage, a lung cancer meta-analysis database (PMID: 24880342) was used to assess association of SNPs identified in Stage II with lung cancer. The objectives of the study were to identify novel genes and SNPs contributing to nicotine metabolism (Stage I), and to validate PK SNPs associated with the NMR from individuals participating in a clinical laboratory protocol with the NMR obtained from treatment-seeking smokers, and then to investigate association with prospective smoking cessation (Stage II). This study built upon existing studies of nicotine metabolism and randomized trials of smoking cessation therapies. Enhanced knowledge of the genes influencing nicotine metabolism and prospective abstinence may help personalize smoking cessation treatment and risk assessment for smoking-related diseases. For Stage I, both subject [fixed-dose NMR, covariates (age, BMI, ethnicity, sex, smoking status, and hormone use), and pedigree relationships] and sample (common DMET SNP genotype, genotyping quality control) data are available in this accession. The analysis protocol, quality control summaries, summary genotype, summary phenotype, and analysis results are available for Stage I, II and III samples (PMID: 26132489). Extensive discussion of the prior CYP2A6 association literature with the NMR, abstinence, smoking heaviness and lung cancer risk is available (PMID: 26132489). The NMR has previously been associated with CYP2A6 activity, response to smoking cessation treatments, and cigarette consumption. We searched for drug metabolizing enzyme and transporter (DMET) gene variation associated with the NMR and prospective abstinence in 2,946 participants of laboratory studies of nicotine metabolism and of clinical trials of smoking cessation therapies. Stage I was a meta-analysis of the association of 507 common single nucleotide polymorphisms (SNPs) at 173 DMET genes with the NMR in 449 participants of two laboratory studies. Nominally significant associations were identified in ten genes after adjustment for intragenic SNPs; CYP2A6 and two CYP2A6 SNPs attained experiment-wide significance adjusted for correlated SNPs (CYP2A6 PACT=4.1E-7, rs4803381 PACT=4.5E-5, rs1137115, PACT=1.2E-3). Stage II was mega-regression analyses of 10 DMET SNPs with pretreatment NMR and prospective abstinence in up to 2,497 participants from eight trials. rs4803381 and rs1137115 SNPs were associated with pretreatment NMR at genome-wide significance. In post-hoc analyses of CYP2A6 SNPs, we observed nominally significant association with: abstinence in one pharmacotherapy arm; cigarette consumption among all trial participants; and lung cancer in four case:control studies. CYP2A6 minor alleles were associated with reduced NMR, CPD, and lung cancer risk. We confirmed the major role that CYP2A6 plays in nicotine metabolism, and made novel findings with respect to genome-wide significance and associations with CPD, abstinence and lung cancer risk. Additional multivariate analyses with patient variables and genetic modeling will improve prediction of nicotine metabolism, disease risk and smoking cessation treatment prognosis.

  Study phs000931

• SC_DDD-G-5

  Post-QC (pre-imputation) genotype data for N=2,166, a subset of trios described in EGAD00010001602. These data form N=722 complete trios in which the proband has a neurodevelopmental phenotype (Niemi et al. Nature 2018). Includes HPO phenotype terms for patients. Samples were genotyped on the Illumina HumanOmniExpress BeadChip

  Dataset EGAD00010001606

• Clones derived from early passage tumoroids of colorectal cancer

  We obtained different clones from early passage CRC tumoroids to study mutational signatures specific for truncal or private somatic alterations. These whole genome sequences are part of a larger study on the heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer.

  Study EGAS50000000107

• Bulk Iso-Seq from brain tissue and exosomes isolated from brain tissue using long-read PacBio sequencing of poly-adenylated transcripts

  Human brain sEVs were isolated from postmortem human brain tissue. RNA was extracted from both the source brain tissue and sEVs and prepared for long-read sequencing. cDNA was sequenced on the PacBio Sequel II. The data provided have undergone processing using the tool ccs (v6.0.0) to generate circula consensus reads. For further processing, it is recommended to follow the guidelines at https://isoseq.how/, starting with using lima to remove cDNA primers.

  Dataset EGAD50000000043

• Whole Genome Sequencing of Two Family Trios with 22q.11.2 Deletion Syndrome

  Two subjects with 22q11.2 deletion syndromes (22q11DS) and their parents were recruited for a whole genome sequencing study to identify candidate genetic modifiers of the various phenotypes seen in 22q11DS. Both probands had a typical 3 megabase deletion on chromosome 22q11.2 but discordant phenotypes.

  Study phs000837

• Understanding the Biology of Language Impairment through Whole Genome Sequencing

  This study involves the whole genome sequencing of a cohort of 390 individuals assessed for language ability, IQ, and behavior as schoolchildren. The primary goal of the study is to identify genes, regulatory elements, and pathways which may underlie variation in language ability within an average population. 

  Study phs002255

• Human Responses to Influenza Vaccination

  The data consist of the DNA sequences of antibody gene rearrangements from peripheral blood human B cells of subjects vaccinated with trivalent seasonal influenza or monovalent pandemic H1N1 vaccine. Multiple replicate libraries of immunoglobulin heavy chain gene rearrangements were prepared from each subject for each time point.

  Study phs000760

• Genetics of Fuchs Corneal Dystrophy

  This grant proposal continues to expand our understanding of the clinical presentation of Fuchs corneal dystrophy, and its underlying genetic basis, which will lead to the development of better therapeutic models and treatment for a common corneal dystrophy that affects 4% of the US population over age 40.

  Study phs001834

• Genome-Wide Association Study on Calcific Aortic Valve Stenosis in Quebec (QUEBEC-CAVS)

  Calcific aortic valve stenosis (CAVS) is a common and life-threatening heart disease with no drug that can stop or delay its progression. A genome-wide association study (GWAS) on 1,009 cases and 1,017 ethnically-matched controls was performed to identify susceptibility genes for CAVS.

  Study phs001492

• Bulgarian Trio Sequencing Study to Identify de Novo Mutations in Schizophrenia

  The primary aim of this study is to whole exome sequence complete Bulgarian trios to identify de novo mutations in schizophrenic probands. We are investigating the rate of de novo mutations in probands as well as looking for enrichment among previously implicated genes and synaptic gene sets.

  Study phs000687

• RNAseq of Sjögren's Syndrome and Healthy Volunteers' Salivary Glands

  Mechanistic genetic and inflammatory endpoints were studied to gain insight into the molecular mechanisms of Sjögren's syndrome. Transcriptomic studies allowed the exploration of molecular alterations that might cause or influence the studied salivary gland pathology and potentially elucidate druggable pathways for intervention.

  Study phs001842

• Gene expression matrix for Smart-seq2 data of peripheral blood B cells

  The dataset contains scRNA-seq gene expression matrix (csv file) and metadata (csv file) after quality control filtering for data generated with the Smart-seq2 protocol. Transcript expression was quantified with Salmon v0.11.3 using cDNA sequences from GRCh38.94 and k-mer length 25, and was aggregated to gene level and transcript-length-corrected using tximport v1.8.0. The dataset comprises IgA+ transglutaminase 2-specific and other IgA+ B cells from the peripheral blood of 355 cells from two untreated celiac disease patients.

  Dataset EGAD50000000338

• Genetic investigation of 12q-amplified osteosarcomas

  Further investigation and characterisation of 12q-amplified low- and high-grade osteosarcomas with MDM2 and/or CDK4 amplification focusing on SV, copy number and gene fusion analyses. In total, 25 cases (33 samples total due to multi-sampling) were included, with some form of sequencing data available for 27 samples. Mate-pair whole genome sequencing (Illumina) is available for 19 samples, longread whole genome sequencing (PacBio HiFi) on 10 samples and RNA-sequencing (Illumina Truseq) on 21 samples. Data is available as BAM files.

  Dataset EGAD50000000707

• Multi-omics analysis of CUD in the VS

  The aim was to molecularly characterize the human ventral striatum in CUD. For this, we generated epigenomic, transcriptomic, and proteomic datasets at the bulk-level, performed integrative multi-omics analyses and further analyzed CUD-associated transcriptomic changes at a cell type-specific level using snRNA-seq.

  Study EGAS50000000623

• Non-invasive prediction of immunotherapy response (NIPIT) project

  This project aims to find transcriptomic biomarkers for immunotherapy response prediction in several cancer types. So far, we have performed poly-A RNA-seq using whloe blood and peripheral blood mononuclear cells from 33 non-small cell lung cancer patients, collected before and after the start of immunotherapy.

  Study EGAS50000000266

• Base modification analysis using single molecule real-time sequencing

  This dataset was generated using single-molecule real-time sequencing for both training and testing purposes. The DNA samples isolated from human buffy coats or placenta of healthy individuals (n=4,) were prepared in a way that four types of base modifications were incorporated, including unmodified controls, 5mC, 5hmC, and 6mA. The sequence data for each sample consists of subreads produced by single-molecule real-time sequencing and stored in a bam format. Details of the specific experiments conducted in this study are outlined in our manuscript.

  Dataset EGAD50000000541

• Genome-wide array data from Eivissan and Menorcan Individuals

  22 and 20 genome-wide array data for Eivissan and Menorcan healthy unrelated volunteers, respectively. The affymetrix Human Origins array was used to genotype these individuals. The variant set was lifted over to the hg38 human genome reference. A single gziped VCF file can be found.

  Study EGAS50000000423

• Cohort A spatial transcriptomics sequencing

  Cohort A includes glioma tumors of varied grading and pathology from male and female individuals. Fresh frozen glioma tissues for each sample in cohort A were analyzed with the 10X Genomics Visium Spatial Gene Expression protocol. Processed data is available on the NCBI Gene Expression Omnibus database with accession GSE242352.

  Study EGAS50000000954

• Cohort B spatial transcriptomics sequencing

  Cohort B includes IDH-wild type, EGFR amplified, surgically derived glioblastoma tissue samples from male and female individuals. FFPE tissues for each sample in cohort B were analyzed with the 10X Genomics Visium CytAssist protocol. Processed data is available on the NCBI Gene Expression Omnibus database with accession GSE242352.

  Study EGAS50000000956

• NHLBI TOPMed: Genetic Causes of Complex Pediatric Disorders - Asthma (GCPD-A)

  The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is focused on addressing the roles of both single nucleotide variants and structural copy number variants, and their functional impact, together with gene-environment interactions and their influence on asthma drug response.

  Study phs001661

• CD79B expression in DLBCL

  This study proposes a novel association between CD79B expression and cell-of-origin subtypes of DLBCL. Integrative single-cell analyses also revealed a distinct association between germinal center B-cell physiology and the pattern of CD79B expression, which is potentially a key explanation for the variable CD79B expression in DLBCL.

  Study EGAS50000000363

• Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

  Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

  Study EGAS50000000182

• RNASeq Whole Transcriptome Expression Profiles of NFE2 and PF4 as Translational Biomarkers for BET Inhibition-Induced Thrombocytopenia in Preclinical and Clinical Studies

  Longitudinal blood samples for exploratory biomarker analysis were collected from 51 out of 83 patients enrolled in CA011-001 (NCT02419417) study of BMS-986152, totaling 425 samples collected on three different dosing schedules (A, B, and C). Whole transcriptome expression profiling was performed on the collected blood samples using RNASeq, with Illumina TruSeq library preparation and paired sequencing. Gene expression data was quantified as transcripts per million (TPM).

  Dataset EGAD50000001659

• Genomic analysis of high-risk prostate cancer.

  Whole genome sequencing analysis of high risk localised primary prostate cancer samples including metastatic samples was performed across 153 tumour samples with matching germline sequencing (whole blood). Samples were all fresh frozen frozen section confirmed tumour specimens and associated clinical and pathological metadata is available for these specimens.

  Study EGAS00001003088

• WES of tumor samples from patients with renal medullary carcinoma (RMC)

  The dataset, in .bam file format, consists of whole exome sequencing (WES) data of tumors from patients (n=24) with Renal Medullary Carcinoma (RMC), generated using Illumina NovaSeq 6000 sequencing technology. DNA was extracted from FFPE solid tumor samples using the AllPrep DNA FFPE Kit (Qiagen, CA). Libraries from FFPE tissue were prepared with the SureSelect XT HS2 DNA Kit (Agilent, CA) for exome capture. The All Exon V7 exome probe set (Agilent, CA) was used for hybridization and capture of DNA.

  Dataset EGAD50000001822

• Analysis of transcriptomic landscape of iPSC-derived neurons in Williams Syndrome

  To analyse the transcriptomic changes in iPSC-derived neuronal cells derived from individuals with Williams syndrome vs. controls at different stages of neuronal maturation. This was done to better understand how the deletion responsible for WS alters neuronal development thereby resulting in the characteristic WS phenotype

  Study EGAS50000001214

• RNA-seq data for proximal and distal human LHBT UZH (CH)

  This dataset contains bulk RNA-seq data from 15 patients who underwent rotator cuff repair surgery, yielding paired proximal and distal samples of the long head of the biceps tendon (30 samples total). The submission includes 90 files, consisting of R1 and R2 FASTQ files for each sample as well asprocessed .TXT files containing gene-level counts generated after genome alignment. Raw sequencing reads were generated on an Illumina platform, aligned to the human reference genome GRCh38.p13, and quantified at the gene level.

  Dataset EGAD50000002095

• Whole exome sequence analysis in sporadic amyotrophic lateral sclerosis

  To identify a susceptible gene for amyotrophic lateral sclerosis, exome sequence analysis was conducted in patients with amyotrophic lateral sclerosis and control subjects to perform whole genome association studies. In this data set, exome sequencing data of 11 patients with amyotrophic lateral sclerosis was included.

  Study JGAS000013

• Single cell RNA sequencing of human cord Blood CD34 Cells

  We performed single cell RNA sequencing and ATAC e valuation of human umbilical cord blood. To explore the differentiation pathway for human lymphoid lineage, our target cells contain CD34-positive cord blood. That population is evaluated by single cell RNA sequencing and single cell ATAC.

  Study JGAS000528

• RNA-sequencing of 82 pleural mesothelioma samples

  The dataset contains RNA-sequencing data (bam files) for 82 pleural mesothelioma samples. All the samples were sequenced on an Illumina NovaSeq 600 sequencer in paired-end mode, generating 100 nt length reads, to obtain an average of 60 million clusters for RNA. Demultiplexing was performed using Illumina bcl2fastq2. Fastq quality was assessed using fastQC (v. 0.11.8) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and low-quality reads were discarded. Sequence reads were aligned to Human reference genome (UCSC genome assembly GRCh38/hg38) using STAR (v. 2.7.0b).

  Dataset EGAD50000002131

• Fragmentomics analyses of urinary cfDNA for urologic cancers

  This dataset contains sequencing data of human urinary cell-free DNA. Whole-genome sequencing (WGS) and whole-genome bisulfite sequencing (WGBS) was performed after DNA extraction from the urine samples. All samples were pair-end sequencing on Illumina system and were aligned to human genome GRCh37 (hg19). WGS and WGBS reads were aligned by SOAP2 and Methyl-Pipe, respectively. The dataset includes samples from healthy subjects, haematuria (non-cancer), and patients of bladder, kidney, or prostate cancer. Pair-end FASTQ files were provided for all the samples mentioned above.

  Dataset EGAD50000002068

• Resolving_the_Genetic_Architecture_of_Aseptic_Loosening_After_Total_Hip_Replacement

  This is a genome-wide association scan of aseptic loosening after total hip replacement in a Norwegian population. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001883

• ESGI___Molecular_diagnosis_for_mitochondrial_disorders_

  The MITOEXME project aims to improve protocols for molecular diagnosis of patients with OXPHOS disorders with a focus on a next generation sequencing methods and to increase the knowledge of pahtophysiological mechanisms by identification of new targets and cellular studies. In this project we will sequence the exomes fo 120 patients.

  Study EGAS00001000164

• Exomes of High-risk Prostate cancer

  DNA extracted from tumoral tissue of 39 patients was used for exome sequencing. As a comparison, DNA extracted from blood was used as a non-tumoral control. DNA was captured using the EZ SeqCap v3 exome kit from Roche and sequenced using an Illumina HiSeq instrument.

  Study EGAS00001001015

• An exome sequencing pilot study of HIV elite-long term non progressors and rapid progressors

  A pilot study examining genetic determinants associated with elite long term non progression and rapid progression using exome sequencing of individuals at the extremes of the distribution of HIV control and progression. Data can only be used for HIV related research.

  Study EGAS00001000057

• Tetralogy of Fallot Exome Trios

  Exome sequencing of 30 parent-offspring trios to >50X mean depth, where the offspring has sporadic TOF, to identify potential causal de novo mutations. We will use the exome plus design for pulldown that incorporates ~6.8Mb of additional regulatory sequences in addition to the ~50Mb GENCODE exome.

  Study EGAS00001000071

• Post-zygotic germline mutations in sperm

  These data from sperm were generated to demonstrate detection of post-zygotic mutations in the male germline. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001700

• Australia_and_New_Guinea_haplotype_phasing_

  Whole-genome sequencing and phasing of admixed Aboriginal Australian genomes and Papua New Guinean genomes using 10x Genomics Chromium technology. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001853

• 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

• Bam files from Whole exome sequencing (WES, ~50x mean read depth) of metachronous bladder tumors

  In this study we characterized genomic alterations in two to five metachronous bladder tumors from 29 patients initially diagnosed with early stage disease. Fourteen patients (32 tumors) had non progressive disease (NPD) and 15 patients (34 tumors) had progressive disease (PD). Whole exome sequencing (WES, ~50x mean read depth and whole transcriptome RNA-seq was performed (RNA was not advalible for 4 tumors) Data provided here consist of 122 Bam files for WES (83 Tumors and 39 blood)

  Dataset EGAD00001002716

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

  RNA-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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002347

• 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 January 2015, RNA-Seq for endothelial cell of umbilical vein (resting)

  RNA-Seq data for 1 endothelial cell of umbilical vein (resting) sample(s). 1 run(s), 1 experiment(s), 1 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_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001142

• 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, RNA-Seq for Acute Promyelocytic Leukemia - MS-275 (20h), on genome GRCh38

  RNA-Seq data for 1 Acute Promyelocytic Leukemia - MS-275 (20h) 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002500

• 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, RNA-Seq for naive B cell, on genome GRCh38

  RNA-Seq data for 6 naive B cell 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002315

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

  RNA-Seq data for 3 CD38-negative naive B cell 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002438

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

  RNA-Seq data for 3 segmented neutrophil of bone marrow 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 EGAD00001001579

• 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

• Single cell resolution of human CNV body map (2019-10-02)

  12 tissues from the warm autopsy are selected for this project. Using 10X Chromium technology we will generate ~1000 single cell/nulei genomic libraries per tissue. Each tissue will be whole genome sequenced (~2 lanes per 1000 cells) on hiseq X10. per single cell we will generate CNV profile and we investigate the level of genomic heterogenity with in tissue and across different tissues. . This dataset contains all the data available for this study on 2019-10-02.

  Dataset EGAD00001005372

• 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, RNA-Seq for class switched memory B cell, on genome GRCh38

  RNA-Seq data for 3 class switched memory B cell 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002476

• High-throughput sequencing data of immunoglobulin gene rearrangements in acute lymphoblastic leukaemia - summary .fastq and .bcl files

  Immunoglobulin heavy chain gene high throughput sequencing of paediatric acute lymphoblastic leukaemia samples, for the purpose of MRD on the Illumina MiSeq platform. This dataset contains summary fastq files and raw bcl files from the MiSeq for this study. In the study we identify errors associated with multiplexing that could potentially impact on the accuracy of MRD analysis. We optimise a strategy combining high purity, sequence-optimised oligonucleotides, dual-indexing and an error-aware demultiplexing approach to minimise errors and maximise sensitivity.

  Dataset EGAD00001001983

• ENU-LS-411N-TripleTherapy

  BRAF V600E colorectal cancers do not respond to the only currently FDA approved targeted therapy for CRC. There is currently a trial underway in the UK recruiting V600E CRC patients for treatment with a triple therapy combination of Cetuximab, Trametinib and Dabrafenib. We have mutagenized a pool of V600E CRC cell lines and treated with this triple therapy to select out drug resistant clones. We will now sequence these drug resistant clones with the aim of identifying common point mutations engendering resistance to this new therapy.

  Dataset EGAD00001002051

• 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 2014, RNA-Seq for CD14-positive, CD16-negative classical monocyte

  RNA-Seq data for 7 CD14-positive, CD16-negative classical monocyte sample(s). 7 run(s), 7 experiment(s), 7 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_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000928

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

  RNA-Seq data for 1 endothelial cell of umbilical vein (proliferating) sample(s). 1 run(s), 1 experiment(s), 1 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_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001166

• 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, RNA-Seq for unswitched memory B cell, on genome GRCh38

  RNA-Seq data for 1 unswitched 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002414

• 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, RNA-Seq for adult endothelial progenitor cell, on genome GRCh38

  RNA-Seq data for 2 adult endothelial progenitor 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 EGAD00001002334

• BLUEPRINT release August 2016, RNA-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 2 CD8-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 EGAD00001002295

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

  RNA-Seq data for 3 germinal center B cell 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002452

• Sequencing data for oesophageal and related samples - Xiaodun Li et al (WGS, RNA)

  Data supporting: "Esophageal adenocarcinoma organoid cultures recapitulate human disease heterogeneity and provide a model for clonality studies and precision therapeutics." Li et al. WGS (BAM files) RNAseq (BAM files) Tumours, organoids, normals

  Dataset EGAD00001004007

• Sequencing data for oesophageal and related samples - ICGC DCC release 28 (WGS)

  WGS sequencing for 409 cases (832 samples) from the ICGC ESAD-UK project Tumours 50x Normals 30x HiSeq X BAM files These samples are all available in ICGC release 28

  Dataset EGAD00001004137

• The effect of anti-HER2/CD3 TDB on transcription in human CD8 T cells (bulk RNA-seq)

  RNA was isolated from purified human CD8 cells that were incubated with anti-HER2/CD3 TDB in the presence of SK-BR-3 cells. Sequencing libraries were generated and submitted for transcriptome profiling by high-throughput sequencing. Experiments were performed in triplicates for anti-HER2/CD3 TDB treatment and control. This Dataset is associated with the following ArrayExpress Experiment: E-MTAB-8211 - The effect of anti-HER2/CD3 TDB on transcription in human CD8 T cells (bulk)

  Dataset EGAD00001005187

• 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, RNA-Seq for inflammatory macrophage, on genome GRCh38

  RNA-Seq data for 6 inflammatory macrophage 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002417

• 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 January 2015, RNA-Seq for CD4-positive, alpha-beta T cell

  RNA-Seq data for 10 CD4-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_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001173

• 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

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

  RNA-Seq data for 1 CD4-positive, alpha-beta 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 EGAD00001001489

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

  RNA-Seq data for 2 conventional dendritic 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 EGAD00001002345

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

  RNA-Seq data for 3 immature conventional dendritic cell - GM-CSF_IL4_T=6_days 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002526

• 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