3930 results for "RNA AND sequencing OR transcriptome"

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• Data set for pan.met study

  The dataset referenced by EGA Study ID EGAS00001004208 includes 20 human exome sequencing data and 11 human RNA sequencing data from tumor or normal tissues. Each sequencing data includes two pair-end short read files in fastq format.

  Dataset EGAD00001005957

• ResolveCRPS study - Transcriptomics

  Transcriptome profiling of CRPS-affected skin using low-input total RNA-seq (paired-end mode with 54 and 68 nt read length for R1 and R2 respectively, Illumination NextSeq2000). 42 snap-frozen skin biopsies were analyzed together with longitudinal clinical data. The dataset contains FASTQ files, the processed read count matrix, and the corresponding clinical metadata.

  Dataset EGAD50000001545

• RNA-Seq data from tumor samples collected from 12 UTSW translocation renal cell carcinoma (tRCC) patients.

  This study investigates differentially expressed genes associated with the progression of translocation renal cell carcinoma (tRCC) by analyzing RNA-Seq data from 23 tumor samples obtained from 12 patients. The samples were collected from affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital and Children’s Medical Center. RNA isolated from tumor samples was sequenced using the Illumina platform.

  Dataset EGAD50000000172

• fibroblast RNAseq from a GINS3 patient and two parents

  RNA-seq was performed from 3 separate GINS3 patient fibroblast cultures and 1 replicate of fibroblasts derived from each of the two parents. RNA-seq libraries were generated with NEBNext Ultra II Directional RNA library prep for Illumina with NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs) and sequenced on Illumina NextSeq500 with paired-end 150 bp read length. SIRV Set 3 (Lexogen) spike-ins were added. Two fastq files are provided for each RNAseq sample.

  Dataset EGAD00001008571

• Single cell RNA sequencing and Whole Genome Sequencing on different cells from the same sample for a triple negative patient derived xenograft and ovarian cancer cell lines.

  Measuring gene expression of genomically defined tumour clones at single cell resolution would associate functional consequences to somatic alterations, as a prelude to elucidating pathways driving cell population growth, resistance and relapse. In the absence of scalable methods to simultaneously assay DNA and RNA from the same single cell, independent sampling of cell populations for parallel measurement of single cell DNA and single cell RNA must be computationally mapped for genome-transcriptome association. Here we present clonealign, a robust statistical framework to assign gene expression states to cancer clones using single-cell RNA-seq and DNA-seq independently sampled from an heterogeneous cancer cell population. We apply clonealign to triple-negative breast cancer patient derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either DNA-Seq or RNA-Seq alone.

  Study EGAS00001003387

• Identification of differentially expressed protein-coding genes in HCC and adjacent non-cancerous tissues

  Twenty samples were collected in pairs, i.e., HCC tissue and adjacent non-cancerous tissue. The collected tissue samples were stored in liquid nitrogen. First, 50 mg of tissue was lysed in TRIzol (Invitrogen) to extract RNA following the manufacturer’s instructions. Next, ribosomal RNA was depleted using a RiboZero Gold kit (Epicentre Bio-technologies). RNA integrity was assessed with an Agilent Bioanalyzer 2100. An RNA-Seq library was generated with the rRNA-depleted samples using an Illumina standard RNA Sample Prep kit according to the manufacturer’s instructions. The library was subsequently sequenced on an Illumina HiSeq2500 as 125-bp paired-ends with approximately 300-bp size selection.

  Dataset EGAD00001003397

• Bulk RNA sequencing data of peripheral blood mononuclear cells obtained from 7 ATL patients and 9 HTLV-1-infected asymptomatic carriers.

  Bulk RNA sequencing (RNA-seq) data of peripheral blood mononuclear cells (PBMCs) obtained from 7 ATL patients (9 samples) and 9 HTLV-1-infected asymptomatic carriers.

  Dataset EGAD00001007018

• Single-cell Transcriptome Analysis of Plasma Cells Across the Disease Spectrum of Multiple Myeloma

  This dataset includes FastQ files of single-cell RNA sequencing data of 5' GEX and VDJ libraries from CD138+ plasma cells enriched from 72 bone marrow aspirates from patients diagnosed with a monoclonal gammopathy from the multiple myeloma spectrum, including MGUS (n=13), SMM (n = 22), NDMM (n = 17), RRMM (n = 15) and PCL (n = 2); and 3 controls.

  Dataset EGAD50000001179

• Colorectal adenomas, carcinomas and adjacent normal NKI-AvL TGO series NGS-ProToCol

  Cancer is caused by changes in the genome of cells, resulting in aberrant transcripts and proteins. In order to understand why normal cells become cancer cells and how we can identify and destroy them, the CTMM-NGS-ProToCol project aimed to understand prostate and colorectal cancer through DNA and RNA molecular profiling, to further improve diagnosis, prognosis and treatment.The state-of-the-art within the field of genome sequencing makes it possible to identify all the modifications in our genome that encode for RNA and of the transcripts themselves. The latest development in RNA sequencing is that if one does not select for polyA RNA, but first removes rRNA from the total RNA and then performs ‘random’ RNA sequencing, 30-60% of the reads are intronic. Since about 40% of the genome consists of genes (and only 1.6% is exonic), deep RNA sequencing will cover not only the exons, but also a large portion of the introns and therefore much of the genome. The power of the combined sequencing of genome and transcriptome is the full view of copy number aberrations (CNA), exon mutations and the consequence and relevance of the mutations at the RNA level in the form of differential gene expression, alternative splicing, alternative promoter usage, novel transcripts, fusion transcripts, read-through transcripts and mutations. For the colorectal (tumor) tissue dataset, we applied molecular profiling to 30 colorectal adenomas, 30 colorectal carcinomas and 18 normal adjacent colon tissues.

  Study EGAS00001002854

• RNA sequencing of genetically modified human iPSCs modeling patients with autism spectrum disorders (ASD)

  We generated two genetically modified iPSC lines. In each line, a single promoter variant identified in a patient with autism spectrum disorder (ASD) was introduced by using the CRISPR/Cas9 system. These mutant lines were analyzed by RNA-seq together with control lines to assess the impact of the introduced variant.

  Study JGAS000651