9296 results for "cancer rna-seq"

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• RNA-seq data for de-methylation of FOXP3-TSDR study

  22 RNA-seq samples of ex-vivo (TN and Treg), cultured Treg, TET1 and untreated mCherry-MOCK

  Dataset EGAD00001006865

• Intellance-2: TruSight Tumor 170 panel based RNA-seq

  Intellance-2: TruSight Tumor 170 panel based RNA-seq

  Dataset EGAD00001007944

• RNA-seq data for ATLAS paper (123 patients)

  RNA-seq data of multi-region samples from PLANET 123 Patient cohort

  Dataset EGAD00001009859

• Transcriptomics of Liver and PBMCs in Alcohol-Associated Liver Disease

  This study was designed to characterize the transcriptome of alcohol-associated hepatitis using RNA sequencing (RNA-seq) technology for both liver tissue biopsies and peripheral blood mononuclear cells (PBMCs) extracted from blood samples, in order to identify expressed genes that are markers of the disease. To distinguish genes that differentiate alcohol-associated hepatitis from other inflammatory liver diseases, we compared the RNA-seq data generated from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, non-alcohol-associated fatty liver disease, and healthy controls. We utilized computational approaches to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to identify a small set of gene biomarkers to distinguish between these liver diseases. The raw RNA-seq data will be available through dbGaP.

  Study phs003112

• Single RNA-Seq of CD11b Beads selected tumor associated macrophages (TAMs) of 3 gliomablastoma patients treated with small molecule inhibitors

  Single RNA-Seq of CD11b Beads selected tumor associated macrophages (TAMs) of 3 gliomablastoma patients treated with small molecule inhibitors. The sequencing was done on HiSeq 4000 with the SmarTer Ultra Low Input RNA v4 and NEBNext ChIP-Seq Kit. The TAMs were treated with GW2580, BLZ945 and PLX3397 and DMSO as control.

  Dataset EGAD00001011273

• Characterization of prostate cancer organoids

  Using models from the LuCaP series as well as those generated at the National Cancer Institute, we have established organoids for in vitro mechanistic testing, including drug screening and genetic manipulation. The major findings from these continuing studies is the durability of organoids for maintaining complex subpopulation and intratumoral heterogeneity and the parallels between in vitro testing and patient outcomes. Existing data from prior releases includes whole-exome sequencing, RNA-seq and SNP array. New data in this release is 67 whole transcriptomes from untreated models (1-5 replicates per model) prior to interventions, single-cell sequencing of three organoid models, single-cell ATAC sequencing, and whole-genome sequencing.

  Study phs001587

• Utlizing the RA signature to predict response to TNFi

  This study involves bulk RNA-seq analyses of blood cells from patients with rheumatoid arthritis who have had an inadequate response to methotrexate, collected before and 12 weeks after effective treatment with either etanercept or adalimumab. Peripheral blood mononuclear cells were stimulated with anti-CD3 for 24 hours and sorted into CD4+, CD19+, and CD4-CD19- (DN) populations for bulk RNA-seq.

  Study phs002562

• Prediction and quantification of splice events from RNA-seq data

  Analysis of splice variants from short read RNA-seq data remains a challenging problem. Here we present a novel method for the genome-guided prediction and quantification of splice events from RNA-seq data, which enables the analysis of unannotated and complex splice events. Splice junctions and exons are predicted from reads mapped to a reference genome and are assembled into a genome-wide splice graph. Splice events are identified recursively from the graph and are quantified locally based on reads extending across the start or end of each splice variant. We assess prediction accuracy based on simulated and real RNA-seq data, and illustrate how different read aligners (GSNAP, HISAT2, STAR, TopHat2) affect prediction results. We validate our approach for quantification based on simulated data, and compare local estimates of relative splice variant usage with those from other methods (MISO, Cufflinks) based on simulated and real RNA-seq data. In a proof-of-concept study of splice variants in 16 normal human tissues (Illumina Body Map 2.0) we identify 249 internal exons that belong to known genes but are not related to annotated exons. Using independent RNA samples from 14 matched normal human tissues, we validate 9/9 of these exons by RT-PCR and 216/249 by paired-end RNA-seq (2 x 250 bp). These results indicate that de novo prediction of splice variants remains beneficial even in well-studied systems. An implementation of our method is freely available as an R/Bioconductor package SGSeq.

  Study EGAS00001001026

• SF12017 scRNA-Seq Primary astrocytoma IDH mutant Male

  Single cell Primary astrocytoma G2. IDH mutant, ATRX negative. Male, 44. Single Cell RNA seq from primary astrocytoma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005395

• WGS and RNA-Seq data from a GBM patient PT-AB6372

  WGS and RNA-Seq data from a GBM patient PT-AB6372

  Dataset EGAD00001004222