11925 results for "cancer rna-seq"

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• RNA-seq cohort of non-tumorous breast tissue from BRCA1/2 carriers

  Non-tumorous breast tissues from BRCA1 or BRCA2 carriers were subject to RNA sequencing. The total number of samples is 130.

  Dataset EGAD00001006746

• Exome and RNA seq data for female patient

  Exome and RNA sequencing data for EGAS00001003776 - one female patient with neurofibroma/schwannoma hybrid nerve sheath tumor (N/S HNST)

  Dataset EGAD00001005249

• Single cell sequencing data for chronic myeloid leukemia cell lines

  This dataset contains RNA sequencing information for Chronic Myeloid Leukemia. In total 2 single-end RNA-seq tumor cell line samples are present.

  Dataset EGAD00001009736

• Exploration of coding and non-coding variants in cancer using GenomePaint.

  GenomePaint (https://proteinpaint.stjude.org/genomepaint) is a dynamic visualization platform for whole-genome, whole-exome, transcriptome, and epigenomic data, featuring a novel design that captures the inter-relatedness between DNA variations and RNA expression. Regulatory non-coding variants can be inspected and discovered along with coding variants, and their functional impact further explored by examining 3D genome and/or ChIP-seq data generated from cancer cell lines. Further, GenomePaint correlates mutation and expression patterns with patient outcomes, and can display external data such as adult cancer datasets and user-provided custom tracks. We used GenomePaint to analyze multi-omics data from 3,652 pediatric cancers representing 16 histotypes, and demonstrate the visualization features through examples, including two that led to new insights into oncogenic mechanisms in pediatric cancer. The first is the discovery of a new class of pathogenic recurrent variants that cause aberrant splicing, disrupting the RING domain of CREBBP, a driver gene frequently mutated in relapsed pediatric leukemia. The second is the cis-activation of the MYC oncogene in a subset of B-lineage acute lymphoblastic leukemia (B-ALL) via duplication of the NOTCH1-MYC enhancer (N-ME), previously discovered only in T-lineage ALL. The regulatory impact of N-ME enhancer amplification was initially confirmed by allelic imbalance in published gene expression and ChIP-seq data and verified by additional Capture-C and fluorescence in situ hybridization data generated by follow-up experiments. These examples demonstrate the power of GenomePaint in enabling not only data visualization but also integrative genomic analysis that can lead to novel biological insight for follow-up experimental validation.

  Study EGAS00001004669

• Single cell RNA-seq and ATAC-seq of CD4+ T cells from blood and tumor of NSCLC patients

  This dataset contains fastq files for paired blood-tumor scRNA-seq samples from 5 NSCLC patients and paired blood-tumor scATAC-seq samples from 2 NSCLC patients, both sequenced with NovaSeq or Illumina HiSeq - Rapid Run.

  Dataset EGAD50000000424

• 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

• 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

• RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  Study on RNA-seq data from tumor tissue samples of primary tumors of advanced clear cell renal cell carcinoma patients enrolled in the NIVOREN GETUG-AFU-26 trial who consented to and participated in the translational program. The goal of this study was to assess previously published gene expression signatures and evaluate their association with the benefit and/or resistance to nivolumab, as well as their association with circulating soluble factors.

  Study EGAS50000001057

• 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