11925 results for "cancer rna-seq"

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• WGS and RNA-Seq data from a GBM patient PT-PD6881

  WGS and RNA-Seq data from a GBM patient PT-PD6881

  Dataset EGAD00001004255

• WGS and RNA-Seq data from a GBM patient PT-LC3356

  WGS and RNA-Seq data from a GBM patient PT-LC3356

  Dataset EGAD00001004250

• WGS and RNA-Seq data from a GBM patient PT-EV3071

  WGS and RNA-Seq data from a GBM patient PT-EV3071

  Dataset EGAD00001004234

• WGS and RNA-Seq data from a GBM patient PT-SK0976

  WGS and RNA-Seq data from a GBM patient PT-SK0976

  Dataset EGAD00001004260

• WGS and RNA-Seq data from a GBM patient PT-LC6372

  WGS and RNA-Seq data from a GBM patient PT-LC6372

  Dataset EGAD00001008522

• Human tumor bulk RNA-seq

  We profiled 7 patient neuroblastoma-FOXR2 tumor samples by bulk RNA-seq. The raw fastqs are provided.

  Dataset EGAD00001010901

• RNA-seq data from 195 pediatric BCP-ALL cases

  RNA-seq data from 195 pediatric BCP-ALL cases. Alignment: TopHat 2.0.7. Reference genome: hg19.

  Dataset EGAD00001002112

• Single-cell RNA and ATAC sequencing data analysis of human postmenopausal fallopian tube and ovary

  In this study, we used a combination of technologies, including Drop-seq, 10X single-cell RNA-seq (scRNA-seq), and single-cell assay on transposase accessible chromatin (scATAC-seq) to generate  a high-quality cell atlas that consists of four tissue sites from the reproductive tract of postmenopausal women. This atlas, by far the most comprehensive map of the postmenopausal female reproductive system to date, will pave the way to a better understanding of the pathophysiology of many diseases affecting older women.

  Study EGAS00001006780

• Discovery of Non-ETS Gene Fusions in Human Prostate Cancer using Next Generation RNA Sequencing

  Half of prostate cancers harbor gene fusions between TMPRSS2 and members of the ETS transcription factor family. To date little is known about the presence of non-ETS fusion events in prostate cancer. We employed next-generation transcriptome sequencing (RNA-Seq) in order to explore the whole transcriptome of 25 human prostate cancer samples for the presence of chimeric fusion transcripts. We generated more than 1 billion sequence reads and used a novel computational approach (FusionSeq) in order to identify novel gene fusion candidates with high confidence. In total, we discovered and characterized seven new cancer-specific gene fusions, two involving the ETS genes ETV1 and ERG, and five involving non-ETS genes such as CDKN1A (p21), CD9 and IKBKB (IKK-beta), genes known to exhibit key biological roles in cellular homeostasis or assumed to be critical in tumorigenesis of other tumor entities, as well as the oncogene PIGU and the tumor suppressor gene RSRC2. The novel gene fusions are found to be of low frequency but interestingly, the non-ETS fusions were all present in prostate cancer harboring the TMPRSS2-ERG gene fusion. Future work will focus on determining if the ETS rearrangements in prostate cancer are associated or directly predispose to a rearrangement prone phenotype.

  Study phs000310

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Dataset EGAD00001007872