11768 results for "cancer rna-seq"

in 23.22 milliseconds.

• Immune-Related Adverse Events after Immune Checkpoint Blockade-Based Therapy are Associated with Improved Survival in Advanced Sarcoma

  Immune activation after immune checkpoint blockade (ICB) can lead to a unique group of adverse events (AEs), which have been associated with improved outcome in many carcinomas. The association between immune-related AEs (irAEs) and outcome in patients with sarcoma is not well studied. This study has two components: (1) a retrospective clinical study of irAEs among 131 patients treated with ICB at Memorial Sloan Kettering Cancer Center and (2) an analysis of a subset of these patients who have whole transcriptome sequencing available for analysis. In the clinical study portion, we reviewed a cohort of patients with advanced sarcoma treated on prospective clinical trials utilizing ICB-based therapy between April 2017 and January 2020. The objectives were to pool the safety data from each trial, identify irAEs, and correlate them with best overall response by RECIST 1.1, progression-free survival (PFS) and overall survival (OS). Association of irAEs with response and survival was assessed using a Cox regression model. A total of 131 patients were included. Forty-two (32%) had at least one irAE of any grade and 16 (12%) had at least one Grade ≥ 3 irAE. On Cox analysis adjusting for clinical covariates that were significant in the univariate setting, the hazard ratio (HR) for an irAE (HR 0.662, 95% CI 0.421 - 1.041) approached, but did not reach statistical significance for PFS (P = 0.074), while patients had a significantly lower HR for OS (HR 0.443, 95% CI 0.246 – 0.798; P = 0.007) compared to those without or before an irAE. Tumor samples with available RNA sequencing data were stratified by presence of an irAE to identify patterns of differential gene expression. In total, 71 unique patients had RNA sequencing available for analysis. The transcriptomes of 31 of these patients have been previously uploaded to dbGaP (phs002852), leaving 36 unique transcriptomes that have not been previously publicly shared. Three patients did not agree for their sequencing to be publicly shared. Therefore, 33 unique patient samples will be uploaded to this dbGaP study. Overall, this study found that gene expression profiling on baseline tumor samples from patients who had an irAE had higher numbers of tumor-infiltrating dendritic cells, CD8+ T cells, and regulatory T cells as well as upregulation of immune and inflammatory pathways.

  Study phs003284

• Profiles of Extracellular RNA in Cerebrospinal Fluid and Plasma from Subarachnoid Hemorrhage Patients

  Brain injury resulting from hemorrhagic stroke is clinically challenging to manage and results in high rates of morbidity and mortality. The pathophysiology of brain damage resulting from aneurysmal subarachnoid hemorrhage (aSAH) is largely unknown, and methods to treat and monitor patients are variable with no meaningful correlations to patient outcome. Prediction of patient risk for serious neurological complications is currently a significant clinical obstacle. An extracellular RNA (exRNA) biomarker to predict onset and severity of brain damage would improve patient outcomes. We sequenced plasma and CSF samples from adult patients with SAH. Samples were collected from post bleed day 1 to day 7. Total exRNA was isolated from each sample. In addition, we prepared a subset of 140 CSF samples, isolating the RNA contained within extracellular vesicles and vesicle-depleted biofluid.

  Study phs001759

• RNA Ligation Precedes U6 snRNA/LINE-1 Retrotransposition

  Long Interspersed Element-1 (L1) retrotransposons make up approximately 17% of the human genome. L1 moves throughout the genome via a copy-and-paste mechanism termed retrotransposition. L1 retrotransposition also mobilizes other cellular RNAs such as SINES, U6 snRNA and, mRNA, which for the latter results in the formation of processed pseudogenes. In this study we demonstrate that the RNA ligase RtcB can create chimeric RNAs by joining U6 snRNAs to 5'-truncated L1 or other cellular RNAs. We also show that the retrotransposition of U6/L1 chimeric RNA leads to U6/L1 pseudogene formation. In sum, our data suggests that U6 snRNA and RtcB may have biological roles in addition to their essential functions in mRNA and tRNA splicing, and that the retrotransposition of chimeric RNAs could be a mechanism to create novel genes.

  Study phs001671

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

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

  Study EGAS00001007553

• prDLBCL WXS/RNA Data Commitee

  Dac EGAC50000000284

• BIRC5 Upregulation Enhances DNMT3A-Mutant T-ALL Cell Survival and Pathogenesis

  The goal of this study was to determine how patients with T-ALL who have DNA methyltransferase 3 alpha (DNMT3A) mutations develop resistance to therapy. Since DNMT3A is a methyltransferase, we examined the effect of those mutations on epigenetic regulation using whole genome bisulfite sequencing (WGBS). We also assessed any changes in gene expression using RNA-sequencing. We found that T-ALL patients with DNMT3A mutations are resistant to apoptosis and some chemotherapies. WGBS showed that DNMT3A mutated patients clustered together by their epigenetic profile, which was associated with hypomethylation at TERT and HOX genes. RNA sequencing identified differences in JAK/STAT signaling.

  Study phs003623

• Development of hunanized mice for human hematopoisis and immunity research

  We obtained peripheral blood or bone marrow samples from 112 acute myeloid leukemia patients and examined sensitivity and resistance of the AML samples to molecular targeting drugs. By doing RNA sequencing using AML cells, we found heterogenous gene expression patterns in AML with different mutational landscapes. From the RNA sequencing, we identified anti-apoptosis, cell cycle progression, and immune-related signals as pathways up-regulated in AML cells as compared with normal CD34+ cells. From the pathway analyses, we further setup in vitro experiments to find vulnerability genes in clinically-aggressive AML. BIRC, BCL2, MCL1, AURKB, and KIF10 may be essential molecules for AML cell survival and proliferation.

  Study JGAS000253

• Meisal temporal lobe epilepsy sequencing study

  Our understanding of mesial temporal lobe epilepsy (MTLE) is one of the most common forms of drug-resistant epilepsy in humans. Using RNA- and small RNA-sequencing in parallel, we explored differentially expressed genes in the hippocampus and cortex of MTLE patients who had undergone surgical resection and non-epileptic controls. We found significant enrichment for astrocytic and microglial genes amongst up-regulated genes and down-regulation of neuron-specific genes in the hippocampus of MTLE patients. The transcriptome profile of the small RNAs reflected disease state more robustly than mRNAs, even across brain regions which show very little pathology.

  Study EGAS00001003922

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

  none

  Study EGAS00001008121

• Rapid Idiosyncratic Mechanisms of Clinical Resistance to KRAS G12C Inhibition

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

  Study phs002734

• Targeting Heterochromatin Eliminates Malignant Stem Cells in Chronic Myelomonocytic Leukemia Through Reactivation of Retroelements and Innate Immune pathways

  RNA-sequencing, ATAC-sequencing, CUT&Tag-sequencing, data from CMML patient and aged-matched healthy donor CD34+ cells. RNA-sequencing data from patient CD34+ cells after treatment for 4 days with decitabine or UNC0638 inhibitors, alone or together, or left untreated

  Dataset EGAD50000000542

• RNASeq profiles from Indian HFrEF Cohort

  The dataset contains whole transcriptomics profiling from a cohort of 49 HFrEF patients. The myocardium samples were collected from these patients during heart transplant of LVAD implantation procedure. The RNA samples were collected in RNAlater. Total transcriptome libraries were prepared using TruSeq Stranded Total RNA Library Prep with Ribo-Zero Gold kit and sequenced on Illumina HiSeq4000.

  Dataset EGAD50000001196

• Multi-omics profiling identifies two epithelioid sarcoma molecular subtypes with distinct signaling and immune characteristics

  Bulk RNA Sequencing of 33 epithelioid sarcomas (EpS) and 3 extracranial extra-renal rhabdoid tumors (EERT) Whole-exome sequencing of 30 EpS and 3 EERT Single-cell RNA Sequencing of 8 EpS Visium Spatial Transcriptomics of 3 EpS

  Dataset EGAD50000001419

• The study on genomic profiling using clinical specimens (tissue, blood, etc.) form patients with lung and thymic tumors

  The objective is to generate a comprehensive immunogenomic profiling in thymoma using RNA sequencing and TCR repertoire analysis and to evaluate the potential of immunotherapy in thymoma from multiple perspectives.

  Study JGAS000552

• Single-cell RNA sequencing on 5063 single T cells from six hepatocellular carcinoma patients

  T cells isolated from peripheral blood, tumors and adjacent normal tissues from six hepatocellular carcinoma patients. SmartSeq2 and Tang2009 protocol were used to amplify RNA from single T cells. High depth enables simultaneously expression profiling and TCR assembling.

  Dataset EGAD00001003337

• 5' single cell RNA sequencing

  Pared-end fastq files of 22 AML and 2 normal bone marrow samples were generated using 10x Genomics 5' single cell RNA sequencing following manufacturer's protocol (CG000086 User Guide RevG) for chemistry version 1.0 and targeting 10000 cells per sample. Libraries were sequenced using Illumina HiSeq 4000 using recommended cycling parameters.

  Dataset EGAD00001007672

• Single Cell RNA sequencing of Organoids from TSC2+/- patient IPSCs in H- and L-medium

  This dataset contains single cell RNA sequencing data from Organoids grown in high nutrient (H) and low nutrient (L) medium. Organoids were grown for 110 days. Organoids were grown from a patient IPS cell line with a heterozygous mutation in TSC2 (Patient 1 TSC2+/- iPSCs) and an isogenic control cell line (TSC2+/+).

  Dataset EGAD00001006332

• Dataset on keratinocytic gene expression pattern in Hidradenitis suppurativa

  Human skin samples were obtained from HS patients after informed consent (Ethical vote, University of Würzburg; No. 306/12). Lesional and perilesional were taken and epidermis and dermis separated. Isolated epidermal keratinocytes were further processed for RNA isolation. mRNA was extracted from five pairwise-matched lesional and perilesional epidermal HS pellets and RNA sequencing was performed.

  Dataset EGAD00001008005

• RNA-sequencing data of post-mortem brain tissue taken from individuals with SCA3 and controls

  Spinocerebellar ataxia type 3 (SCA3) is the most common autosomal dominant inherited ataxia worldwide, caused by a CAG repeat expansion in the Ataxin-3 gene resulting in a polyglutamine (polyQ)-expansion in the corresponding protein. Here we have RNA-sequencing data from the cerebellum of individuals with SCA3 and matched controls.

  Dataset EGAD00001009317

• Custom long non-coding RNA capture DAC

  Dac EGAC00001002198

• GLASS-NL RNA-sequencing Study

  Study EGAS00001007551

• Renal_habitat_WXS

  This project aims at correlating genetic diversity (as well as transcriptomic, metabolic and immune diversity) observed in multiple targeted tumour biopsies and circulating tumour DNA with heterogeneity on multiparametric MRI. To this end, 20 patients with RCC (15 patients with localised/locally advanced disease and 5 with mRCC) will undergo multiparametric MRI including metabolic assessment by 13C-MRSI as well as measurements of tumour perfusion, oxygenation and water diffusion. Based on unique combinations of these imaging parameters, tumour habitats will be defined through cluster mapping. Intra-operative biopsy and immediate freezing of tumour cores from different imaging habitats will be performed. Multiregional ex-vivo tumour biopsies will be spatially registered to the MR data by using 3D printed tumour moulds generated from high-resolution volumetric sequences. These moulds allow slicing tumour specimens in identical planes to the MR acquisition and increase the accuracy of tissue sampling. The biopsies will then undergo molecular profiling such as metabolomic and RNA sequencing (including mRNA immune profiling), as well as DNA sequencing to assess driver and clonal mutations in different tumour habitats and guide design of appropriate cfDNA probes. The targeted cfDNA capture panel will be employed to determine the ability of cfDNA to capture the full genetic diversity observed in the primary tumour and to relate cfDNA to various imaging habitats in both renal and pancreatic cancer. Data integration will be undertaken between imaging habitats and molecular profiles for each region.

  Study EGAS00001003703

• Single_cell_characterization_of_T_cell_lymphoma_

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas.

  Study EGAS00001005750

• H3K27ac ChIP-seq in a selected group of AML patients

  ChIP-seq data were generated for a number of selected patients to investigate changes in enhancer and promoter regions. ChIP was performed as described previously with slight modifications27. Briefly, cells were crosslinked with 1% formaldehyde for 10 minutes at room temperature and the reaction was quenched with glycine at a final concentration of 0.125 M. Chromatin was sheared using the Covaris S220 focused-ultrasonicator to an average size of 250–350 bp. A total of 2.5 µg of antibody against H3K27ac (Abcam, ab4729) was added to sonicated chromatin of 2 × 106 cells and incubated overnight at 4 °C. Protein A sepharose beads (GE healthcare) were added to the ChIP reactions and incubated for 2 h at 4 °C. Beads were washed and chromatin was eluted. After crosslink reversal, RNase A and proteinase K treatment, DNA was extracted with the Monarch PCR & DNA Cleanup kit (NEB). Sequencing libraries were prepared with the NEBNext Ultra II DNA Library Prep Kit for Illumina (NEB) according to the manufacturer’s instructions. The quality of dsDNA libraries was analyzed using the High Sensitivity D1000 ScreenTape Kit (Agilent) and concentrations were assessed with the Qubit dsDNA HS Kit (Thermo Fisher Scientific). Libraries were single-end sequenced on a HiSeq 4000 (Illumina). ChIP-seq reads were aligned to the human reference genome build hg19 with bowtie

  Dataset EGAD00001007582

• Exceptional Responders Initiative

  The Exceptional Responders Initiative is a pilot study to investigate the underlying molecular factors driving exceptional treatment responses of cancer patients to drug therapies. Study researchers will examine molecular profiles of tumors from patients either enrolled in a clinical trial for an investigational drug(s) and who achieved an exceptional response relative to other trial participants, or who achieved an exceptional response to a non-investigational chemotherapy. An exceptional response is defined as achievement of either a complete response or a partial response for at least 6 months duration in a trial or treatment where the overall response rate is < 10%. The hope is to discover underlying molecular features that can be further investigated and may eventually predict benefit from a given drug or class of drugs for a particular patient. This pilot project will successfully characterize approximately 100 cases of tumor tissue and, when available, case-matched germline DNA. All samples will undergo whole exome sequencing, and cases with sufficient nucleic acids will undergo additional analyses (e.g. whole genome sequencing, mRNA-sequencing, mi RNA sequencing, promoter methylation analysis, SNP etc). Each case will be annotated with demographic and clinical information, along with follow-up information minimally sufficient to correlate molecular profiles with response. Both retrospective and prospective collections will be considered. The project will also accept sequencing data and clinical data from patients who have had sequencing performed outside of this project. All data will be de-identified and placed in a controlled access database so other investigators may use them for additional insights. Clinically annotated tissue specimens meeting the criteria will be provided by groups participating in the Exceptional Cases Initiative to a Biospecimen Core Resource (BCR), which will perform quality control on the tissues, and will use a standard operating procedure to isolate nucleic acids. The nucleic acids will be shipped to a sequencing center to perform whole exome sequencing and analysis. These findings will be made available to the broader cancer research community in a controlled access database.

  Study phs001145

• Identification of Somatic Changes in Tumors from Fanconi Anemia Patients

  This study focused on the identification of genomic signatures present in tumors from Fanconi anemia patients. Fanconi anemia is a rare hereditary disease caused by defects in DNA interstrand crosslink repair. The primary patient phenotypes are bone marrow failure and cancer predisposition. We concentrated on squamous cell carcinomas and used whole genome Illumina sequencing (22 tumor samples and 12 normal samples) , whole exome sequencing (37 tumor samples and 33 normal samples), PacBio long-read whole-genome (nine tumor and four normal samples),10X linked-read whole-genome sequencing, 10x single-cell/nuclei 3’ RNA sequencing (three tumor samples), 10x Visium spatial transcriptomics (one tumor sample), EPIC 850K methylation array (six samples), and bulk RNAseq (six tumor samples) to identify somatic changes present in tumors. The study aimed to identify changes that drive tumorigenesis in Fanconi anemia, give insight into the early development and aggressive nature of these tumors, and suggest therapeutic avenues for these patients. Another goal was to compare the genomic changes identified in tumors from Fanconi anemia patients with sporadic head and neck cancers. This study demonstrated that the tumors from Fanconi anemia individuals are generally not driven by HPV. Instead, they acquire mutations in the p53 tumor suppressor. The main characteristic of the tumors is the presence of a high number of structural variants in the form of small deletions, unbalanced translocations, and fold-back inversions, which often form complex rearrangements. These rearrangements result in amplifications and deletions of a multitude of oncogenes and tumor suppressors, respectively. The study also shows that lack of the Fanconi anemia DNA repair pathway leads to an epithelial-to-mesenchymal transition in a mouse model and in human samples that may influence the behavior of tumors in Fanconi anemia. Finally, comparing genomic changes in Fanconi anemia and sporadic tumors of the head and neck, we propose that the structural variants present in sporadic cancer result in a functional deficiency of the Fanconi anemia DNA repair pathway.

  Study phs002652

• Automated machine-learning approach for next generation profiling of sequence alterations, mutation burden, microsatellite instability, and structural variants in human cancers

  Sequence and structural alterations together with tumor mutation burden (TMB) and microsatellite instability (MSI) have been identified as biomarkers for the determination of response to targeted and immune checkpoint inhibitor therapies. However, widespread clinical adoption of these biomarkers has historically been limited due to barriers such as evidence of clinical utility and reimbursement. We have developed 2.2 Mb targeted NGS system and an automated machine-learning analysis approach (PGDx elio™ tissue complete, ETC) that has been FDA cleared for examination of 500+ cancer-related genes and 68 mononucleotide repeats for identification of sequence and structural alterations, TMB, and MSI in solid cancers in a clinical setting. We designed and trained this approach using sequence data from 4,174 cancers and >124,000 in silico alterations and evaluated the methodology in >2,550 tumor or non-cancerous normal samples. Independent analyses of ETC sequence changes in 440 formalin fixed paraffin embedded (FFPE) tumor or cell line samples using MSK-IMPACT™, FoundationOne®, and ddPCR revealed a positive percent agreement (PPA) >97% with high sensitivity as low as 3% mutant allele fraction. We observed high concordance between panel-wide and whole-exome TMB for 307 pan-cancer FFPE tumors (Pearson r=0.95, p < 0.0001) using samples with ≥20% tumor cellularity. Comparison of the mutation context and repeat-based MSI approach in ETC with a multiplex MSI PCR assay in 223 samples revealed a PPA of 99% and negative predictive agreement (NPA) >99%. We confirmed the accuracy and precision of TMB and MSI measurements across three independent laboratories (CV of <5% and average PPA >99%, respectively). Finally, evaluation of amplifications and translocations against DNA and RNA-based approaches exhibited >98% NPA and PPA of 86% and 82% respectively. These results demonstrate high analytical performance for determination of sequence and structural changes, TMB, and MSI using a targeted NGS panel and provide a scalable and facile approach for evaluating these biomarkers in a clinical laboratory.

  Study EGAS00001005556

• EM-seq datatset of primary human thymocyte subsets

  FASTQ-files of EM-seq experiments of 6 primary human thymocyte subsets, isolated by flow-cytometry (FACS) from neonatal thymus biopsies. All samples were sorted to be negative for the expression of the lineage surface markers CD11c, CD19, CD56, CD141 and CD303 and additionally had the following surface phenotypes: DN2 (CD4-CD8-CD7+CD1a-CD161-CD38+CD3-TCRab-); DN3 (CD4-CD8-CD7+CD1a+); ISP (CD4+CD8-CD3-TCRab-CD1a+); DPE (CD4+CD8+TCRab-CD69-); DPL (CD4+CD8+TCRab+CD69+); SP4 (CD4+CD8-). Samples were sorted from 1-2 pediatric patients undergoing heart surgery.

  Dataset EGAD50000001600

• mRNA-seq data from ALL patients with NUP214::ABL1 disease

  Dataset contains mRNA-sequencing data (fastq files) from 2 patients with NUP214::ABL1 disease (one T-ALL and one B-ALL patient). Patient samples (peripheral blood or bone marrow) were taken at diagnosis (B-ALL) or relapse (T-ALL). mRNA was extracted from lymphoblasts and underwent paired-end sequencing (75bp) using the Illumina NextSeq platform. Transcriptomic data was used for identification of gene fusions, SNVs and InDels. mRNA-seq data for an additional B-ALL patient with NUP214::ABL1 disease utilised in this study has already been published (EGAS00001006460).

  Dataset EGAD50000001395

• scRNA-seq data of Anti-Her2-CAR T cells treated with immunomodulatory metabolites

  Anti-Her2-CAR T cells produced from T cells derived from healthy human donors were treated with DMSO (control) or either of the immunomodulatory metabolites indole‐3‐carboxaldehyde (ICA), valeric acid (VA) and isovaleric acid (IVA) to assess effects on CAR T cell function. scRNA-seq libraries were generated on a 10X Chromium controller with On-Chip-Multiplexing. The individual samples in a library are distinguished during analysis on the single-cell level via the cell barcode class.

  Dataset EGAD50000002012

• Investigation of chromatin accessibility in clear cell renal cell carcinoma using ATAC-seq

  To identify regions of open and accessible chromatin in clear cell renal cell carcinoma (ccRCC), we performed ATAC-seq on the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and processed narrowPeak fomats. Data were processed using the nf-core atacseq pipeline.

  Dataset EGAD50000001885

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

  ChIP-Seq data for 3 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte sample(s). 11 run(s), 11 experiment(s), 11 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 EGAD00001002445

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

  ChIP-Seq data for 3 central memory CD8-positive, alpha-beta T 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 EGAD00001002450

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

  ChIP-Seq data for 3 Germinal Center B-Cell-Like Diffuse Large B-Cell Lymphoma sample(s). 10 run(s), 10 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002506

• BLUEPRINT release August 2016, ChIP-Seq for mature conventional dendritic cell - GM-CSF_IL4_T=6_days_R848_T=24hrs, on genome GRCh38

  ChIP-Seq data for 3 mature conventional dendritic cell - GM-CSF_IL4_T=6_days_R848_T=24hrs sample(s). 20 run(s), 19 experiment(s), 19 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 EGAD00001002462

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

  ChIP-Seq data for 2 effector memory CD8-positive, alpha-beta T cell, terminally differentiated 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 EGAD00001002503

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

  ChIP-Seq data for 3 effector memory CD8-positive, alpha-beta T cell sample(s). 16 run(s), 15 experiment(s), 15 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 EGAD00001002283

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

  ChIP-Seq data for 3 central memory CD4-positive, alpha-beta T cell sample(s). 11 run(s), 9 experiment(s), 9 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 EGAD00001002439

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

  ChIP-Seq data for 1 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001503

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

  ChIP-Seq data for 1 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 4 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_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001195

• BLUEPRINT release August 2016, ChIP-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  ChIP-Seq data for 3 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 19 run(s), 18 experiment(s), 18 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 EGAD00001002362

• BLUEPRINT release August 2016, ChIP-Seq for cytotoxic CD56-dim natural killer cell, on genome GRCh38

  ChIP-Seq data for 6 cytotoxic CD56-dim natural killer cell sample(s). 34 run(s), 34 experiment(s), 34 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 EGAD00001002463

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

  ChIP-Seq data for 7 CD4-positive, alpha-beta T cell sample(s). 39 run(s), 39 experiment(s), 39 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001505

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

  ChIP-Seq data for 3 mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs) sample(s). 18 run(s), 18 experiment(s), 18 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001527

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

  ChIP-Seq data for 2 CD3-negative, CD4-positive, CD8-positive, double positive thymocyte sample(s). 7 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 EGAD00001002369

• BLUEPRINT release August 2016, ChIP-Seq for mesenchymal stem cell of the bone marrow, on genome GRCh38

  ChIP-Seq data for 2 mesenchymal stem cell of the bone marrow sample(s). 16 run(s), 14 experiment(s), 14 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002381

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

  ChIP-Seq data for 2 effector memory CD4-positive, alpha-beta T cell 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 EGAD00001002514

• scRNA-seq raw data

  scRNA-seq data of B-lineage cells from the cerebrospinal fluid of 21 patients with multiple sclerosis. The data was generated with the Smart-seq2 protocol and sequenced on Illumina NextSeq500.

  Dataset EGAD00001008481

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

  ChIP-Seq data for 10 CD14-positive, CD16-negative classical monocyte sample(s). 80 run(s), 76 experiment(s), 76 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 EGAD00001002484

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

  ChIP-Seq data for 1 central memory CD4-positive, alpha-beta T cell sample(s). 9 run(s), 7 experiment(s), 7 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001499