12080 results for "cancer rna-seq"

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• HipSci - Hypertrophic Cardiomyopathy - RNA Sequencing - July 2017

  HipSci - Hypertrophic Cardiomyopathy - RNA Sequencing - July 2017

  Dataset EGAD00001003540

• HipSci - Macular Dystrophy - RNA Sequencing - July 2017

  HipSci - Macular Dystrophy - RNA Sequencing - July 2017

  Dataset EGAD00001003541

• HipSci - Usher Syndrome - RNA Sequencing - July 2017

  HipSci - Usher Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003543

• HipSci - Kabuki Syndrome - RNA Sequencing - July 2017

  HipSci - Kabuki Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003535

• HipSci - Retinitis Pigmentosa - RNA Sequencing - July 2017

  HipSci - Retinitis Pigmentosa - RNA Sequencing - July 2017

  Dataset EGAD00001003542

• HipSci - Alport Syndrome - RNA Sequencing - July 2017

  HipSci - Alport Syndrome - RNA Sequencing - July 2017

  Dataset EGAD00001003532

• RNA sequence of HUB_5 cell culture

  RNA sequence data for conditionally reprogrammed cells from patient HUB_5

  Dataset EGAD00001001923

• Circulating Tumor DNA in Intermediate Risk Rhabdomyosarcoma

  In this study, we evaluated circulating tumor DNA (ctDNA) as a biomarker in the serum of 124 patients with newly diagnosed intermediate risk rhabdomyosarcoma (IR RMS) from the Children's Oncology Group (COG) biorepository. In addition to pre-treatment serum, we also analyzed matched tumor tissue and germline in a subset of patients. We profiled samples using ultra-low passage whole genome sequencing (ULP-WGS) and a new custom hybrid-capture sequencing assay, Rhabdo-Seq, to detect copy number alterations, rearrangements, and single nucleotide variants. We found that patients with detectable ctDNA at diagnosis had significantly worse outcomes than those without detectable levels of ctDNA. Our study demonstrates that baseline ctDNA detection is feasible and prognostic in IR RMS. The ULP-WGS and targeted next-generation sequencing (Rhabdo-Seq and TranSS-Seq) data are available in this study.  

  Study phs002866

• Single cell RNA and ATAC sequencing data from GBM patients

  Glioblastoma cells infiltrate and incorporate into the normal brain parenchyma. We conduct unbiased multimodal single-cell and spatial sequencing to capture GBM cells and the surrounding tumor microenvironment using a regional sampling strategy. For each patient, we profile the peritumoral region, tumor edge, and tumor core, providing a comprehensive characterization of the transcriptional and epigenetic landscape of GBM spatial heterogeneity, with a specific focus on infiltrative cells.

  Study EGAS50000000547

• Single cell RNA sequencing of colorectal cancer patients (CRC-SG1)

  Raw sequencing reads were processed as single end sequencing, aligned to the human reference genome GRCh38 and processed using CellRanger 3.1.

  Dataset EGAD00001008555