9931 results for "cancer rna-seq"

in 62.57 milliseconds.

• Single-cell RNA sequencing of blood immune cells before and after interleukin-2 immunotherapy

  Single-cell RNA sequencing of flow cytometry sorted human CD45+ immune cells from 3 systemic lupus erythematosus patients (SLE_002, SLE_004, and SLE_006) collected at baseline (day 0, before interleukin-2 immunotherpay) and day 5 (after 1 treatment cycle of interleukin-2 immunotherapy). Sorted immune cells were hash tagged and then stained with TotalSeq Human Universal Cocktail (Biolegend) before further processing for single-cell RNA sequencing using the 10X-Genomics platform. Samples from all 3 patients were pooled and loaded on 3 lanes of the chromium controller, resulting in 1 raw sequncing file for each lane.

  Dataset EGAD50000000662

• RNA sequencing of undifferentiated sarcomas

  Dac EGAC00001001055

• Human Biofluid RNA Atlas DAC

  Dac EGAC00001001338

• A capture methyl-seq protocol with improved efficiency and cost-effectiveness using pre-pooling and enzymatic conversion

  The opportunities for sequencing-based methylome analysis of clinical samples are increasing. To reduce its cost and the amount of genomic DNA required for library preparation, we aimed to establish a capture methyl-seq protocol, which adopts pre-pooling of multiple libraries before hybridization capture and TET2/APOBEC-mediated conversion of unmethylated cytosine to thymine. We compared a publicly available dataset generated by the standard Agilent protocol of SureSelect XT Human Methyl-Seq Kit and our dataset obtained by our modified protocol, EMCap, that adopted sample pre-pooling and enzymatic conversion. We confirmed that the quality of DNA methylation data was comparable between the two datasets. As our protocol, EMCap, is more cost-effective and reduces the amount of input genomic DNA, it would serve as a better choice for clinical methylome sequencing.

  Study JGAS000605

• Optimisation of CITE-seq on liquid and solid tissues

  Study EGAS00001005849

• Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A - Data Access Committee

  Dac EGAC00001003049

• MeDIP-seq data in the Peri/postnatal Epigenetics Twins Study (PETS)

  Dac EGAC00001000596

• EMBL genome biology research group for structural variation (Strand-seq application)

  Dac EGAC00001001091

• METHYLATION_TUMOR

  Methylation data from tumor tissue

  Dataset EGAD00010001674

• Atrial appendage miRNA-seq in non-, paroxysmal and persistent atrial fibrillation

  Study EGAS00001005296

• Peripheral clonal expansion of T cells (scRNA-seq)

  Study EGAS00001003993

• Epigenomic atlas of organoid development

  To investigfate the epigenomic basis of fate decisions in the central nerveous system, we recorded a epigenomic timecourse of human brain organoid development using Cut&Tag with paired scRNA-seq. We further performed perturbation experiment inhibiting EED and profiled the response with scRNA-seq and Cut&Tag. Finally, we profiled a sample of the developing human brain using multiome sequencing and Cut&Tag. In our study, we uncover epigenomic switches during brain region diversification and show that epigenetic activation precedes gene expression during neurogenesis in organoids and in primary tissue. Lastly, we show that transcriptional repression by H3K27me3 is required to stabilize neuroectoderm induction from pluripotency.

  Study EGAS50000000155

• prDLBCL WXS/RNA Data Commitee

  Dac EGAC50000000284

• GLASS-NL RNA-sequencing Study

  Study EGAS00001007551

• Identification of gene mutations and fusion genes in patients with Sézary Syndrome

  Sezary syndrome (SS) is a leukemic form of cutaneous T-cell lymphoma (CTCL) with an aggressive clinical course. The goal of our study is to understand the genetic basis of the disease by looking for driver gene mutations and fusion genes in 15 erythrodermic patients with circulating Sezary cels, fourteen of them fulfilling the diagnostic criteria of SS. Peripheral blood samples were collected for each patient and CD4+ T-lymphocytes and Granulocytes were isolated. DNA and RNA was extracted for matched normal and tumor materials. Whole exome sequencing was performed on matched normal and tumor tissues of 12 patients and RNA sequencing was performed on 10 patients. For 7 of these patients, we have both exome as well as RNA sequencing data. In this study, we present a complex genomic landscape of Sezary syndrome with several point mutations, copy number variations and fusion events which could contribute to the pathogenesis of SS.

  Study EGAS00001001706

• Whole genome DNA sequencing for two long-lived humans.

  Two long-lived human samples were sequenced to a mean 20x coverage genome wide. Sequencing was done using the Illumina hi-seq platform, alignment to GRCh37/hg19 reference genome was done using the BWA alignment tool.

  Study EGAS00001000877

• BLUEPRINT release August 2014, Bisulfite-Seq for precursor lymphocyte of B lineage

  Bisulfite-Seq data for 1 precursor lymphocyte of B lineage sample(s). 8 run(s), 1 experiment(s), 1 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000910

• BLUEPRINT release August 2014, Bisulfite-Seq for hematopoietic multipotent progenitor cell

  Bisulfite-Seq data for 1 hematopoietic multipotent progenitor cell sample(s). 8 run(s), 1 experiment(s), 1 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000917

• BLUEPRINT release January 2015, Bisulfite-Seq for precursor lymphocyte of B lineage

  Bisulfite-Seq data for 1 precursor lymphocyte of B lineage sample(s). 8 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001134

• BLUEPRINT release January 2015, ChIP-Seq for Acute promyelocytic leukemia

  ChIP-Seq data for 6 Acute promyelocytic leukemia sample(s). 25 run(s), 23 experiment(s), 23 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 EGAD00001001138

• BLUEPRINT release January 2015, Bisulfite-Seq for hematopoietic multipotent progenitor cell

  Bisulfite-Seq data for 1 hematopoietic multipotent progenitor cell sample(s). 8 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001141

• BLUEPRINT release January 2015, Bisulfite-Seq for alternatively activated macrophage

  Bisulfite-Seq data for 4 alternatively activated macrophage sample(s). 64 run(s), 4 experiment(s), 4 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001143

• BLUEPRINT release January 2015, Bisulfite-Seq for class switched memory B cell

  Bisulfite-Seq data for 1 class switched memory B cell sample(s). 20 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001176

• BLUEPRINT release January 2015, ChIP-Seq for Chronic lymphocytic leukemia

  ChIP-Seq data for 3 Chronic lymphocytic leukemia 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 EGAD00001001187

• BLUEPRINT release January 2015, ChIP-Seq for Acute myeloid leukemia

  ChIP-Seq data for 7 Acute myeloid leukemia sample(s). 23 run(s), 23 experiment(s), 23 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 EGAD00001001188

• ATAC-SEQ MAIN - PHASE 1

  This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001001320

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

  Bisulfite-Seq data for 2 erythroblast sample(s). 35 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_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001484

• BLUEPRINT release August 2015, Bisulfite-Seq for memory B cells, on genome GRCh38

  Bisulfite-Seq data for 1 memory B cells 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_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001494

• BLUEPRINT release August 2015, Bisulfite-Seq for mature eosinophil, on genome GRCh38

  Bisulfite-Seq data for 1 mature eosinophil 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 EGAD00001001507

• BLUEPRINT release August 2015, Bisulfite-Seq for plasma cell, on genome GRCh38

  Bisulfite-Seq data for 2 plasma cell sample(s). 17 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_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001522

• BLUEPRINT release August 2015, Bisulfite-Seq for precursor B cell, on genome GRCh38

  Bisulfite-Seq data for 1 precursor B cell sample(s). 6 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 EGAD00001001529

• BLUEPRINT release August 2015, Bisulfite-Seq for Acute Myeloid Leukemia - CTR, on genome GRCh38

  Bisulfite-Seq data for 1 Acute Myeloid Leukemia - CTR sample(s). 18 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 EGAD00001001530

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

  Bisulfite-Seq data for 1 naive B cell sample(s). 5 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 EGAD00001001556

• BLUEPRINT release August 2015, Bisulfite-Seq for monocytes - T=0days, on genome GRCh38

  Bisulfite-Seq data for 1 monocytes - T=0days 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 EGAD00001001565

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

  Bisulfite-Seq data for 8 macrophage sample(s). 117 run(s), 8 experiment(s), 8 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001575

• FASTQ files of the Exome-Seq data for the study "Genomic landscape of lung adenocarcinoma in East Asians"

  FASTQ files of the Exome-Seq data for both the normal and tumor samples for the study "Genomic landscape of lung adenocarcinoma in East Asians". For mutations and copy number variants called by this study, please download from https://src.gisapps.org/OncoSG_public/study/summary?id=GIS031 by clicking the download icon next to the dataset title.

  Dataset EGAD00001004422

• BLUEPRINT release August 2016, Bisulfite-Seq for Acute Lymphocytic Leukemia, on genome GRCh38

  Bisulfite-Seq data for 7 Acute Lymphocytic Leukemia sample(s). 132 run(s), 9 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002313

• BLUEPRINT release August 2016, Bisulfite-Seq for T-cell Prolymphocytic Leukemia, on genome GRCh38

  Bisulfite-Seq data for 3 T-cell Prolymphocytic Leukemia sample(s). 45 run(s), 3 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002303

• BLUEPRINT release August 2016, Bisulfite-Seq for neutrophilic myelocyte, on genome GRCh38

  Bisulfite-Seq data for 3 neutrophilic myelocyte sample(s). 31 run(s), 3 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002331

• BLUEPRINT release August 2016, Bisulfite-Seq for Acute Myeloid Leukemia - CTR, on genome GRCh38

  Bisulfite-Seq data for 2 Acute Myeloid Leukemia - CTR sample(s). 28 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 EGAD00001002333

• BLUEPRINT release August 2016, Bisulfite-Seq for Type 1 diabetes mellitus, on genome GRCh38

  Bisulfite-Seq data for 4 Type 1 diabetes mellitus sample(s). 32 run(s), 4 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002392

• BLUEPRINT release August 2016, Bisulfite-Seq for monocyte - None, on genome GRCh38

  Bisulfite-Seq data for 2 monocyte - None sample(s). 70 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002395

• BLUEPRINT release August 2016, Bisulfite-Seq for Chronic Lymphocytic Leukemia, on genome GRCh38

  Bisulfite-Seq data for 6 Chronic Lymphocytic Leukemia sample(s). 84 run(s), 6 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002396

• BLUEPRINT release August 2016, Bisulfite-Seq for Acute Promyelocytic Leukemia - CTR, on genome GRCh38

  Bisulfite-Seq data for 2 Acute Promyelocytic Leukemia - CTR sample(s). 27 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 EGAD00001002407

• BLUEPRINT release August 2016, Bisulfite-Seq for thymocyte, on genome GRCh38

  Bisulfite-Seq data for 1 thymocyte sample(s). 14 run(s), 1 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002440

• BLUEPRINT release August 2016, Bisulfite-Seq for Acute Myeloid Leukemia, on genome GRCh38

  Bisulfite-Seq data for 19 Acute Myeloid Leukemia sample(s). 338 run(s), 32 experiment(s), 38 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 EGAD00001002419

• BLUEPRINT release August 2016, Bisulfite-Seq for erythroblast, on genome GRCh38

  Bisulfite-Seq data for 2 erythroblast sample(s). 35 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 EGAD00001002423

• BLUEPRINT release August 2016, Bisulfite-Seq for osteoclast, on genome GRCh38

  Bisulfite-Seq data for 2 osteoclast sample(s). 88 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002427

• BLUEPRINT release August 2016, Bisulfite-Seq for Acute Promyelocytic Leukemia - ATRA, on genome GRCh38

  Bisulfite-Seq data for 1 Acute Promyelocytic Leukemia - ATRA sample(s). 9 run(s), 1 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002472

• BLUEPRINT release August 2016, Bisulfite-Seq for neutrophilic metamyelocyte, on genome GRCh38

  Bisulfite-Seq data for 3 neutrophilic metamyelocyte sample(s). 32 run(s), 3 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002497

• BLUEPRINT release August 2016, Bisulfite-Seq for Mantle Cell Lymphoma, on genome GRCh38

  Bisulfite-Seq data for 5 Mantle Cell Lymphoma sample(s). 65 run(s), 5 experiment(s), 10 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 EGAD00001002505

• Chromatin 3D interactions mediate genetic effects on gene expression (ChIP-seq)

  ChIP-seq data for Lymphoblastoid Cell Lines (LCL) and Fibroblasts (FIB) from the Gencord Cohort: - 160 LCLs assayed for H3K27ac, H3K4me1 and H3K4me3, - 78 FIB assayed for H3K4me3 and 79 FIB assayed for H3K27ac and H3K4me1 This dataset was generated as part of the following study: Delaneau et al (2019). Chromatin 3D interactions mediate genetic effects on gene expression.

  Dataset EGAD00001004871

• scRNA-seq raw data

  This dataset contains scRNA-seq fastq files (trimmed for quality and adapters using Trim Galore) for 3739 intestinal plasma cells of known or unknown antigen specificities from in total 12 individuals (4 untreated coeliac disease patients, 3 treated coeliac disease patients, 5 controls). The data was generated using the Smart-seq2 protocol and sequenced on the Illumina NextSeq500 platform with 75 bp paired-end reads.

  Dataset EGAD00001006436

• Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation

  Raw sequencing files from scRNA-seq dataset used in Schmassmann et al. 2023. Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation. Elife 12 (https://elifesciences.org/articles/92678) Dataset content: 14 samples from 5 donors File type: paired-end fastq files Technology: Illumina sequencing Experimentation used: scRNA-seq using the 10X technology

  Dataset EGAD50000000434

• Paired-end Whole Exome-seq analysis of the Hypermutation and Malignant Progression in Low-grade Glioma Patients

  113 DNA samples were derived from the tumors of the low grade glioma patients and sequenced using Illumina WES (exome seq) paired-end technology. Dataset contains 113 BAM files aligned to hg19 using BWA v.0.5.9. After mapping duplicated reads were removed, reads were re-aligned around InDels and read base quality score was re-calibrated.

  Dataset EGAD00001005386

• Single-cell RNA-seq analysis for COVID19 patients

  While SARS-CoV-2 infection causes mild respiratory disease in most individuals, a small group of patients develops severe COVID-19. Dysfunctional innate immune responses have been identified to contribute to differences in COVID-19 severity, but the key regulators are still unknown. Here, we present an integrative single-cell epigenetics, transcriptomic, and genetics analysis of peripheral blood mononuclear cells from hospitalized and convalescent COVID-19 patients. In classical monocytes, we identified 41.3% of significantly up-regulated genes in hospitalized COVID-19 patients potentially induced by differential chromatin accessibility. Sub-clustering and motif-enrichment analyses of monocytes reveal disease condition-specific regulation by transcription factors, such as C/EBPs and SPI1, and their targets, including a long-noncoding RNA LUCAT1, which further regulates interferon responses and is associated with the need for oxygen supply of COVID-19 patients. The interaction between C/EBPs and LUCAT1 was validated through loss-of-function experiments. Finally, we investigated genetic risk variants that exhibit allele-specific open chromatin (ASoC) in promoters/enhancers of COVID-19 patients. Integrating our data with publicly available expression quantitative trait loci and chromosomal interactions indicates that ASoC SNP rs6800484-C is associated with lower expression of CCR2, which may contributeto higher viral loads in lungs and higher risk of COVID-19 hospitalization. Altogether, our study highlights the diverse genetic and epigenetic regulators that contribute to the innate immune responses of different COVID-19 patients.

  Study EGAS00001006560

• Presence of bacterial infection in brains of patients with Huntington's disease (HD)

  Bacterial isolation in infected brains in patients with Huntington's disease. Here we used next generation sequencing of 16S ribosomal RNA gene PCR amplicons (NGS 16S amplicon analysis)

  Study EGAS00001003678

• Presence of bacterial infection in brains of patients with Parkinson's disease (PD)

  Isolation of bacteria in infected brains in patients with Parkinson's disease. Here we used next generation sequencing of 16S ribosomal RNA gene PCR amplicons (NGS 16S amplicon analysis).

  Study EGAS00001003643

• A method for multiplexed full-length single-molecule sequencing of the human mitochondrial genome

  Here we describe a method to target, multiplex and sequence full-length, native single-molecule the human mitochondrial genome utilizing the RNA-guided DNA endonuclease Cas9.

  Study EGAS00001006203

• Small molecule screen reveals synergy of cell cycle checkpoint kinase inhibitors with DNA-damaging chemotherapies in medulloblastoma (methylation dataset)

  human medulloblastoma xenograft isolated from mouse brain was frozen and genomic DNA or RNA was extracted. Bisulfite converted DNA was processed and hybridised to illumina EPIC or 450K arrays using standard protocols. RNAseq was performed on total RNA.

  Dataset EGAD00001006583

• Single cell RNA-sequencing of treatment naïve PDAC patient samples

  Single cell RNA-sequencing of treatment naïve PDAC patient samples. We have 10 samples, sequenced using the 10X genomics chromium platform with 3 prime chemistry. We are submitting FASTQ files representing the index files (I1), Read1 (R1) and Read2 (R2).

  Dataset EGAD00001008961

• Single-cell RNA-sequencing of peripheral blood mononuclear cells from patients with achalasia

  The data published here contains single-cell RNA-sequencing (scRNAseq) data as obtained using the 3' scRNAseq using Chromium Single Cell 3’ Reagent from 10X Genomics on peripheral blood mononuclear cells (PBMC) from patients with achalasia. Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000250

• RNA Sequencing of AD OM cells exposed to traffic-related air pollutants

  Total RNA sequencing of olfactory mucosa (OM) cells derived from individuals diagnosed with Alzheimer's disease exposed to traffic-related ultrafine particles (UFPs) for 24-h and 72-h in submerged cultures. The UFPs used for exposures were: A0, A20 and Euro6. Exposures were compared to the corresponding blank samples.

  Dataset EGAD50000000648

• Primary_DIPG_expression_profiles

  In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG. Seventeen primary tumor samples stereotactically biopsied at diagnosis by neurosurgeons in the Necker-Enfants Malades hospital (Paris, France) and snap-frozen for RNA extraction and subsequent poly-A mRNA purification.

  Dataset EGAD00001011080

• RNA-seq analysis of transcriptome variation with human ESC subclones

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ .

  Dataset EGAD00001004266

• Human and rat skeletal muscle multiomic profiling sequencing data

  Illumina sequencing data (fastq files) representing single-nucleus (sn) ATAC-seq, snRNA-seq, bulk ATAC-seq, and snATACseq+snRNAseq multiomics data from human and rat skeletal muscle samples (19 libraries total). Includes a README file that describes the relationship between libraries, samples, and files.

  Dataset EGAD00001008323

• scRNA-seq of total bone marrow mononuclear cells and CD3+ T cells of multiple myeloma patients and healthy donors

  The study includes 50 scRNA-seq samples of bone marrow aspirates of 11 multiple myeloma patients and 3 healthy donors generated with the 10x Genomics platform (Chromium Single Cell 3’ Solution v2). For the multiple myeloma patients, paired longitudinal samples are available from initial diagnosis and long-term surivor state. For each patient and timepoint, total bone marrow mononuclear cells and CD3+ T cells have been sequenced separately.

  Study EGAS00001006980

• snRNA-seq in white matter post-mortem tissue from MS and controls - DAC

  Dac EGAC00001001105

• whole exome seq

  whole exome sequencing data

  Dataset EGAD00001004464

• Exome

  Exome Seq for EGAS00001001845

  Dataset EGAD00001002160

• Comprehensive molecular profiling of ETMR

  ETMR RIPSeq

  Dataset EGAD00001004802

• Adipocytes Regulate Fibroblast Function and Their Loss Contributes to Fibroblast Dysfunction in Inflammatory Diseases

  We profiled live synovial cells from 16 individuals with no diagnosed arthritis using single-cell RNA sequencing. Our study was designed to provide a reference single cell RNA sequencing dataset for researchers interested in studying arthritic synovium, providing sequencing data on healthy synovial cells for comparison to cells from diseased synovial tissues. Synovial tissue was collected post-mortem from three different sources between 2019-2021: the National Disease Research Interchange, a collaboration with Rush University and the Gift of Hope, and the Brigham and Women's Hospital Autopsy Department. To be included in the study, patients had to be between the ages of 18 to 72 and have no diagnosed arthritis or autoimmune diseases. Additionally, this study includes bulk RNA sequencing data of cultured primary synovial fibroblasts isolated from three rheumatoid arthritis patents. Cells were stimulated with either cortisol, fat conditioned media, TGFβ, TNFα, fat conditioned media with mifepristone, TGFβ with fat conditioned media, or TNFα with fat conditioned media. Cells were harvested 4 or 22 hours later and lysates collected for sequencing. Data from this study submitted to the Gene Expression Omnibus (GEO) may be accessed via accession number GSE233504.

  Study phs003304

• Custom long non-coding RNA capture DAC

  Dac EGAC00001002198

• Exploiting immune cell receptor information to quantify index switching in single cell transcriptome sequencing experiment

  By offering high sequencing speed and ultra-high-throughput at a low price, Illumina next-generation sequencing platforms has been widely adopted in recent years. However, an experiment with multiplexed library could be at risk of molecular recombination, known as “index switching”, which causes certain amount of reads to be assigned to an incorrect library. It is reported that a new advance, exclusion amplification (ExAmp) in conjunction with the patterned flow cell technology introduced on HiSeq 3000/HiSeq 4000/HiSeq X sequencing systems, potentially suffers from a higher rate of index switching than conventional bridge amplification. We took advantage of the diverse but highly cell-unique expression of immune cell receptors to quantify index switching on single cell RNA-seq data that were sequenced on HiSeq 3500 and HiSeq 4000. By utilizing the unique T-cell receptor (TCR) expression, we could quantify the spread-of-signal from many different wells (n=51 from total three batches) due to index switching. We used TraCer to reconstruct full-length TCR from all samples, and then used Kallisto to quantify TCR gene expression. We found index switching in all three batches of experiments investigated. The median percentage of incorrectly detected markers was estimated to be 4.2% (interquartile range (IQR): 2.0%-8.7%). We did not detect any consistent pattern of certain indices to be more prone for switching than others, suggesting that index switching is a stochastic process. We confirm that index switching is a problem that affects all samples run in multiplexed libraries on Illumina HiSeq 3500 and HiSeq 4000 platforms.

  Study EGAS00001002911

• Identification of the dismal subtype of B-ALL with dysregulation of CDX2 and UBTF

  PURPOSE: Advance in the knowledge of genomic basis of B-cell acute lymphoblastic leukemia (B-ALL) has changed the treatment approaches and diagnostic assays and improved their outcome. Despite the recent development of next generation sequencing approaches, there are still some cases that their drivers are unknown. We aimed to define and describe the characteristics of an additional B-ALL subtype by integrating genomic, transcriptomic, and epigenomic approach. METHODS: More than 2,000 B-ALL cases of RNA-seq data from from Eastern Cooperative Oncology Group (ECOG) and the American College of Radiology Imaging Network (ACRIN) (n=764), the Children's Oncology Group (COG), Munich Leukemia Laboratory (MLL) (n=280), and other several collaborators were analyzed to identify the new subtype. Whole genome sequence was performed to detect mutations, stractural variants, and copy number alterations. The tridimentional analysis of chromatin was performed with HiChIP. RESULTS: We identified the new high-risk B-ALL subtype “CDX2/UBTF” that exhibited unique gene expression profiles, which is enriched in female (77.3%), adolescents and young adults (52.6%), and relapse cohort (3.3%). CD10 negativity and IgM positivity are hallmarks of this subtype with NTRK3 expression that can be an effective marker at diagnostic approach and a potential targeted therapy with TRK and mulkinase inbitors, larotrectinib and entrectinib. Genetically, two different alterations define CDX2/UBTF. One is UBTF-ATXN7L3 fusions caused by deletion of 17q21.31, and the other is extopic CDX2 expression through the enhancer hijacking mechanism induced by deletion of 13q12.2. Other genomic features include gain of 1q and PAX5 rearrangement (PAX5-ZCCHC7), might induce upregulation of histone cluster genes and PAX5. CONCLUSION: We described the novel B-ALL subtype “CDX2/UBTF” that has unique clinical and genomic characteristics.

  Study EGAS00001005863

• Monocyte and macrophage lipid accumulation results in downregulated type-I interferon responses

  Macrophages are critical components of atherosclerotic lesions and their pro- and anti-inflammatory responses influence atherogenesis. Type-I interferons (IFNs) are cytokines that play an essential role in antiviral responses and inflammatory activation and have been shown to promote atherosclerosis. Although the impact of type-I IFNs on macrophage foam cell formation is well-documented, the effect of lipid accumulation in monocytes and macrophages on type-I IFN responses remains unknown. Here we examined IFN stimulated (ISG) and non-ISG inflammatory gene expression in mouse and human macrophages that were loaded with acetylated LDL (acLDL), as a model for foam cell formation. We found that acLDL loading in mouse and human macrophages specifically suppressed expression of ISGs and IFN-β secretion, but not other pro-inflammatory genes. The downregulation of ISGs could be rescued by exogenous IFN-β supplementation. Activation of the cholesterol-sensing nuclear liver X receptor (LXR) recapitulated the cholesterol-initiated type-I IFN suppression. Additional analyses of murine in vitro and in vivo generated foam cells confirmed the suppressed IFN signalling pathways and suggest that this phenotype is mediated via downregulation of interferon regulatory factor binding at gene promoters. Finally, RNA-seq analysis of monocytes of familial hypercholesterolemia (FH) patients also showed type-I IFN suppression which was restored by lipid-lowering therapy and not present in monocytes of healthy donors. Taken together, we define type-I IFN suppression as an athero-protective characteristic of foamy macrophages. These data provide new insights into the mechanisms that control inflammatory responses in hyperlipidaemic settings and can support future therapeutic approaches focusing on reprogramming of macrophages to reduce atherosclerotic plaque progression and improve stability.

  Study EGAS00001005955

• Low mutation burden and frequent loss of CDKN2A/B and SMARCA2, but not PRC2, define pre-malignant neurofibromatosis type 1-associated atypical neurofibromas

  Neurofibromatosis type 1 (NF1) is a tumor-predisposition disorder caused by germline mutations in NF1. NF1 patients have an 8-16% lifetime risk of developing a malignant peripheral nerve sheath tumor (MPNST), a highly aggressive soft-tissue sarcoma, often arising from pre-existing benign plexiform neurofibromas (PN) and atypical neurofibromas (ANF). ANF are distinct from both PN and MPNST, representing an intermediate step in malignant transformation. In the first comprehensive genomic analysis of ANF, we performed tumor/normal exome sequencing (ES) of 16 ANFs. In addition, we conducted ES of three MPNSTs, copy-number meta-analysis of 26 ANF and 28 MPNST, and whole transcriptome RNA-seq analysis of five ANF and five MPNST. We identified low mutation burden (median 1, range 0-5) in the exomes of ANF (only NF1 somatic mutations were recurrent), and frequent deletions of CDKN2A/CDKN2B (69%) and SMARCA2(42%) loci. We determined that polycomb repressor complex 2 (PRC2) genes EED or SUZ12 were frequently mutated, deleted or downregulated in MPNST but not in ANF. Our gene expression study revealed upregulated NRAS, MDM2, CCND1/CCND2/CCND3 and CDK4/CDK6 in both ANF and MPNST, and overexpression of EZH2 in MPNST only. We conclude that the PN-ANF transition is primarily driven by the deletion of CDKN2A/CDKN2B in addition to already present inactivated NF1. Further progression from ANF to MPNST likely involves broad chromosomal rearrangements and frequent inactivation of the PRC2 genes, loss of the DNA repair genes, and copy-number increase of signal transduction, cell cycle and pluripotency self-renewal genes.

  Study phs001993

• The PEMDAC phase 2 study of pembrolizumab and entinostat in patients with metastatic uveal melanoma

  Patients with metastatic uveal melanoma (UM) have an abysmal prognosis. Preclinical studies have suggested that epigenetic therapy could enhance immunogenicity of cancer cells. Here we test if epigenetic therapy would enhance PD-1 immunotherapy in patients with metastatic UM. We report the results of the PEMDAC phase 2 clinical trial (n=29; NCT02697630) where the HDAC inhibitor entinostat was combined with the PD-1 inhibitor pembrolizumab in patients with metastatic UM. The primary endpoint was objective response rate (ORR), and was met with an ORR of 14%. The clinical benefit rate at 18 weeks was 28%, median progression free survival was 2.1 months and the median overall survival was 13.4 months. Toxicities were manageable, and there were no treatment-related deaths. Extensive genomics studies were performed using DNA/RNA and single cell sequencing and flow cytometry. Objective responses and prolonged survival were seen in three patients with BAP1 wildtype tumors, and in one patient with an iris melanoma that exhibited a UV signature. Longer survival also correlated with low baseline ctDNA levels or LDH. In conclusion, HDAC inhibition and anti-PD1 immunotherapy results in durable responses in a subset of patients with metastatic UM. Further exploration of combined immunotherapy and epigenetic therapy in metastatic UM is warranted.

  Study EGAS00001005478

• Longitudinal evaluation of serum microRNAs as biomarkers for neuroblastoma burden and therapeutic p53 reactivation

  Accurate assessment of treatment response and residual disease is indispensable for the evaluation of cancer treatment efficacy. However, performing tissue biopsies for longitudinal follow-up poses a major challenge in the management of solid tumours like neuroblastoma. In the present study, we evaluated whether circulating miRNAs are suitable to monitor neuroblastoma tumour burden and whether treatment-induced changes of miRNA abundance in the tumour are detectable in serum. We performed small RNA sequencing on longitudinally collected serum samples from mice carrying orthotopic neuroblastoma xenografts that were exposed to treatment with idasanutlin or temsirolimus. We identified 57 serum miRNAs to be differentially expressed upon xenograft tumour manifestation, out of which 21 were also found specifically expressed in the serum of human high-risk neuroblastoma patients. The murine serum levels of these 57 miRNAs correlated with tumour tissue expression and tumour volume, suggesting potential utility for monitoring tumour burden. In addition, we describe serum miRNAs that dynamically respond to p53 activation following treatment of engrafted mice with idasanutlin. We identified idasanutlin-induced serum miRNA expression changes upon one day and 11 days of treatment. By limiting to miRNAs with a tumour-related induction, we put forward hsa-miR-34a-5p as a potential pharmacodynamic biomarker of p53 activation in serum.

  Study EGAS00001006678

• Stratifying and Targeting Pediatric Medulloblastoma through Genomics

  In this project, genomic analyses of pediatric medulloblastoma samples, obtained through the international medulloblastoma consortium, will be performed. RNA and miRNA expression profiles of 1000 samples, representing all four subgroups (Wnt, Shh, Group C, and D), will be studied to identify novel subtypes within each subgroup. The resulting subtype-specific expression profiles will support the development of reliable and robust biomarkers to more accurately and reliably classify medulloblastomas for treatment in clinical trials. For that purpose, two assays will be developed: an antibody-based immunohistochemical assay and an orthogonal nucleic acid-based hybridization assay. Additional genomic DNA analysis of the 300 high risk subgroup cases will support the discovery of subgroup specific somatic mutations in order to inform current clinical trials of targeted therapies, and to identify genes and pathways already targeted in other diseases. Such therapies could be rapidly transitioned to Phase II trials in medulloblastoma. Furthermore, the discovery of somatic mutations could be used for developing as well as validating specific biomarkers. The project team will also try to identify risk factors that predispose children to this type of cancer.

  Study EGAS00001000273

• Ewing and Ewing-like-sarcoma tumoroid biobank reveals distinct drug sensitivities: translocation makes the difference

  Ewing sarcoma (ES) and Ewing-like sarcomas (ELS) are highly aggressive tumors found in soft tissues and bone of mostly children and young adults. Despite being different in many aspects, including genetics, possible cell-of-origin, and pathology, patients with any of these entities all receive the same therapeutic regimen. Currently, there is a lack of preclinical cell models that can predict drug response of these entities in vitro. Here, we describe a pediatric ES and ELS tumor organoid (tumoroid) biobank containing tumoroids with different translocations, including EWSR1::FLI1, EWSR1::ERG, CIC::DUX4, and BCOR-rearrangements. Using histology, whole genome sequencing and RNA sequencing, we demonstrate that these tumoroids retain key properties of their matching patient tumors. In addition, we traced tumor subclones in the tumoroids across patient-matched longitudinal samples, which showed that cellular heterogeneity was maintained. We subsequently performed drug screening on the tumoroid models, which unveiled entity-specific drug sensitivity to various cytotoxic compounds and targeted compounds, including MCL-1 inhibitors for CIC::DUX4 sarcomas. Taken together, this newly established ES and ELS patient-derived tumoroid biobank generates a unique source of material for future basic cancer research and drug-screening.

  Study EGAS00001007941

• Identification of Long Non-coding RNA Biomarker of Human Lupus Nephritis Disease Activity

  Total RNA sequencing was performed on whole blood samples from 74 Lupus nephritis (LN) patients and 20 healthy controls. Differential expression analysis and weighted gene co-expression network analysis were performed to characterise expression changes of long non-coding RNAs (lncRNAs) in LN and identify lncRNAs with a key role in disease activity that could be used as potential blood-based biomarkers.

  Study EGAS00001007117

• Epitope-linked Ig-seq of self-reactive plasma cells in celiac disease

  Study EGAS00001003658

• ChIP-seq of plasma cell-free nucleosomes identifies cell-of-origin gene expression programs

  Dac EGAC00001001875

• EGFR Mutant SCLC transformed exome seq

  Dataset EGAD00001001436

• Exome

  Exome Seq for Study EGAS00001001844

  Dataset EGAD00001002159

• Exome

  Exome Seq from EGAS00001001846

  Dataset EGAD00001002162

• ATRT ChIPSeq H3K27ac

  ATRT ChIPSeq H3K27ac

  Dataset EGAD00001004836

• ChIP_PEAKS

  ChIP-seq narrowPeaks. Software: MACS2 v2.1.2

  Dataset EGAD00010001923

• Asthma in the Lives of Families Today (ALOFT)

  Social interactions and the overall psychosocial environment have a demonstrated impact on health, particularly for people living in disadvantaged urban areas. Here we investigated the effect of psychosocial experiences on gene expression in peripheral blood immune cells of 251 children with asthma in Metro Detroit. Participants were included from an ongoing longitudinal study Asthma in the Lives of Families Today (ALOFT; recruited from November 2010-July 2018. The ALOFT project was established to identify the behavioral and biological pathways through which family social environments impact youth with asthma. In version 1 we used RNA-sequencing and a new machine learning approach to identify transcriptional signatures of 19 variables including psychosocial factors, blood cell composition and asthma symptoms. Using longitudinal data collected from a subset of the participants we showed that transcriptional signatures track the longitudinal changes in measured phenotypes. Importantly, we found 169 genes associated with asthma that are regulated by psychosocial factors, and 344 significant gene-environment interactions for gene expression levels. These results demonstrate that immune gene expression mediates the link between negative psychosocial experiences and asthma risk. In version 2, we focused on pubertal development. We identified substantial gene expression changes associated with age and pubertal development. We showed that genetic effects on gene expression change dynamically during pubertal development. Gene expression changes during puberty are correlated with gene expression changes associated with asthma and may explain sex differences in prevalence. Our results show that molecular data used to study the genetics of early onset diseases should consider pubertal development as an important factor that modifies the transcriptome. Version 3, uses single cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated Peripheral Blood Mononuclear Cells from 96 African American children. We employed novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we demonstrated that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and demonstrated widespread genetic regulation of the transcriptional dynamics of the gene expression response.

  Study phs002182

• Human Biofluid RNA Atlas Project - raw data

  Study EGAS00001003917

• RNA Sequencing of Surgically Resected Colorectal Liver Metastases

  Dac EGAC00001000904

• RNA sequencing of sorted human RCC immune populations

  Dac EGAC00001002861

• Genomic landscape of IG-MYC positive Burkitt lymphoma with precursor B-cell immunophenotype.

  As part of the ICGC, the ICGC MMML-Seq project performed whole genome sequencing of a rare Burkitt lymphoma subtype with precursor B-cell immunophenotype. Analysis were performed in concordance with the guidelines of the ICGC.

  Study EGAS00001002968

• BLUEPRINT release August 2014, ChIP-Seq for mature eosinophil

  ChIP-Seq data for 1 mature eosinophil 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_chipseq_analysis_ebi_20140811

  Dataset EGAD00001000906

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

  Bisulfite-Seq data for 6 CD14-positive, CD16-negative classical monocyte sample(s). 86 run(s), 6 experiment(s), 6 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000941

• BLUEPRINT release August 2014, ChIP-Seq for inflammatory macrophage

  ChIP-Seq data for 3 inflammatory macrophage 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 EGAD00001000940

• BLUEPRINT release August 2014, ChIP-Seq for alternatively activated macrophage

  ChIP-Seq data for 4 alternatively activated macrophage sample(s). 29 run(s), 28 experiment(s), 28 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 EGAD00001000938

• BLUEPRINT release August 2014, Bisulfite-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  Bisulfite-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 14 run(s), 1 experiment(s), 1 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000932

• BLUEPRINT release August 2014, ChIP-Seq for mature neutrophil

  ChIP-Seq data for 7 mature neutrophil sample(s). 68 run(s), 50 experiment(s), 50 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 EGAD00001000930