9296 results for "cancer rna-seq"

in 40.49 milliseconds.

• Histone and transcriptome profiling of glioblastoma initiating cells

  ChIP-seq and RNA-seq of glioblastoma initiating cells and their differentiated counterparts with and without inhibition/knockdown of KDMs.

  Dataset EGAD00001005124

• Pseudogene_RNAseq

  RNA sequencing to validate findings of somatic pseudogenes acquired during cancer development

  Study EGAS00001000606

• FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls.

  FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls. The POP study placental biopsies were collected within 30 minutes of birth and flash frozen in RNAlater (ThermoFisher). For each biopsy, total placental RNA was extracted from approximately 5 mg of tissue using the “mirVana miRNA Isolation Kit” (Ambion) followed by DNase treatment (“DNA-free DNA Removal Kit”, Ambion). RNA quality was assessed with the Agilent Bioanalyzer and all the samples with RIN values ≥ 7.0 were used in the downstream experiments. RNA-libraries were prepared from 1g of total placental RNA with the TruSeq Stranded mRNA Library Prep Kit (Illumina) which captures polyA-tailed transcripts by oligo-dT beads, then pooled and sequenced (single-end, 50bp) using a Single End V4 cluster kit and Illumina HiSeq2500

  Dataset EGAD00001006304

• Comparison of transcriptional response of induced pluripotent stem (iPS) cell-derived and monocyte-derived macrophages to bacterial lipopolysaccharide stimulation

  In the first part of this project, we will differentiate IPS cells from 5 human donors into macrophages, and extract RNA from unstimulated and LPS stimulated macrophages to perform RNA sequencing. We will also extract RNA before and after stimulation in blood- derived macrophages from 5 additional, unrelated healthy samples. In the second part of the project, RNA-seq data will be analysed to compare LPS response of these two macrophage populations. In summary, we will perform 75bp PE RNA-seq on 20 samples (10 pre and post stimulus), on the HiSeq 2500 platform. Samples will be multiplexed at 5 samples / lane, so we will require 4 flow cells in total.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 EGAD00001001106

• An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases

  At 5' ends of RNAs, there is a unique "cap signature" derived from a 7-methylguanosine cap. By leveraging this signature, we developed ReapTEC (read-level pre-filtering and transcribed enhancer call), a method for simultaneously profiling gene expression and enhancer activities using 5'-end single-cell RNA sequencing (5' scRNA-seq). We applied ReapTEC and single-nucleus ATAC-seq to a total of ~1 million single human CD4+ T cells.

  Study JGAS000689

• Epigenome of sorted human muscle stem cell

  This dataset contain RNA-seq, ChIP-seq, WGBS and ATAC-seq of 1 human muscle stem cell sample. NCAM+ITGB1+ CD31−CD45−CD34− were used as the sorting strategy for the sample. H3K27ac, H3K27me3, H3K4me1, H3K4me3, H3K36me3 and H3K9me3 are the targets of ChIP-seq.

  Dataset EGAD00001008686

• Celiac disease-specific intestinal T cells analyzed with HLA-class II tetramers, RNA-seq and mass cytometry have a narrow, autoimmune-associated phenotype

  Celiac disease (CD) is an HLA-DQ2/8-associated autoimmune enteropathy driven by activation of gluten-specific CD4+ T lymphocytes upon gluten consumption. Much less is known about the phenotype and function of these cells or their correlation, if any, to disease-relevant cells in other autoimmune disorders. Here we use mass cytometry and RNA seq to show that gluten-specific blood and gut T cells occupy a small and phenotypically distinct T-cell subset.

  Study EGAS00001003017

• Blood RNA-seq from Mexican DMD patients and healthy controls

  These data are part of a study that aimed to assess the potential of blood RNA-seq to track non-invasively disease progression for DMD. In particular, here we focus on a study designed to compare gene expression in blood from DMD patients to that of healthy controls. These data are analysed in the following manuscript: Signorelli, M., Ebrahimpoor, M. et al. (accepted). Peripheral blood transcriptome profiling enables monitoring disease progression in dystrophic mice and patients. To appear in EMBO Molecular Medicine.

  Study EGAS00001004907

• Whole genome sequence and RNA-seq data from paired tumour and germline samples from mesothelioma patients.

  Malignant pleural mesothelioma (MPM) has a poor overall survival with few treatment options. Whole genome sequencing (WGS) combined with RNA sequencing (RNA-seq) analysis of the immune features of MPM offers the prospect of identifying changes that could inform future clinical trials. We analysed somatic mutation and RNA-seq data from 229 MPM samples, including 58 MPM samples that had undergone WGS from our own institutions, together with other published data. This combined analysis identified somatic driver genes, including newly identified candidate genes. Whole genome doubling was a frequent event that correlated with shorter survival. Mutational signature analysis revealed dominant signatures and showed that defects in homologous recombination repair were infrequent in our cohort. Within the tumour immune environment we identified high M2 macrophage infiltrate linked with MMP2, MMP14, TGFB1 and CCL2 expression, representing an immunosuppressive environment. A small subset of samples had a higher proportion of CD8 T cells and a high cytolytic score, suggesting a ‘hot’ immune environment which is independent of the somatic mutations. We propose that our findings on genomic changes and subtypes of immune microenvironments may influence therapeutic planning in the future.

  Study EGAS00001005196

• Single-cell RNA-seq data from 3 HGSOC patient-derived organoids and corresponding tumor or ascites

  Study EGAS00001006246