12312 results for "cancer rna-seq"

in 13.87 milliseconds.

• Reference epigenome Pancreas-Islet02 h3k36me3 ChIP-Seq data generated from KEP study

  Pancreas-Islet02 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007195

• Reference epigenome IPS-Fibroblast02 h3k27ac ChIP-Seq data generated from KEP study

  IPS-Fibroblast02 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007270

• Reference epigenome IPS-Fibroblast02 input ChIP-Seq data generated from KEP study

  IPS-Fibroblast02 input ChIP-Seq paired end data

  Dataset EGAD00001007276

• Gene Expression and Biomarker Utility in Post-Mortem Samples

  The FAA Functional Genomics Team examined the feasibility of analyzing gene expression profiles using post-mortem brain, lung, muscle, and blood samples collected from aviation accident fatalities, with the goal of validating post-mortem extracted RNA for use in RNA sequencing. We compared the RNA sequencing results obtained from THC-positive and THC-negative samples to determine whether RNA sequencing on samples collected from aviation accident fatalities was possible and if any differences in gene expression associated with THC consumption were detectable post-mortem. The study population included 57 males of indeterminant age who perished in general aviation accidents and for whom post-mortem toxicological testing identified delta-9-THC or its primary or secondary metabolites, as well as negative controls. We determined that RNA sequencing on post-mortem aviation accident fatality samples is possible, and further identified genes showing differential expression in lung and muscle between THC-positive and THC-negative samples. We conclude that post-mortem tissue samples collected from aviation accident fatalities are suitable for gene expression profiling, but caution researchers that such samples have low RNA integrity numbers and some degree of microbial contamination is both probable and to be expected. Raw sequencing files (.fastq) from this study are available in dbGaP.

  Study phs003546

• Single cell RNAseq of PDAC organoids

  To study the role of WNT7B, three organoid lines were sequenced using SORT-Seq

  Study EGAS50000001544

• EM-seq converted WGS for CSF-derived cfDNA from pediatric brain tumor patients

  EM-seq converted WGS for CSF-derived cfDNA from pediatric brain tumor patients

  Dataset EGAD50000001975

• Reference epigenome DB31_N_Alpha_mRNA-Seq data generated from KEP study

  A DB31_N_Alpha_mRNA-Seq paired end data for alpha cells(PSA-NCAM(-), pancreas)

  Dataset EGAD00001003485

• Reference epigenome DB31_N_Alpha_smRNA-Seq data generated from KEP study

  A DB31_N_Alpha_smRNA-Seq single end data for alpha cells(PSA-NCAM(-), pancreas)

  Dataset EGAD00001003494

• Reference epigenome ADMSC01_smRNA-Seq data generated from KEP study

  A ADMSC01_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003867

• Reference epigenome ADMSC02_smRNA-Seq data generated from KEP study

  A ADMSC02_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003868

• Reference epigenome ADMSC03_smRNA-Seq data generated from KEP study

  A ADMSC03_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003869

• ChIP-Seq files for RMS.

  ChIP-Seq files accompanying the paper titled "Identification of Therapeutic Targets in Rhabdomyosarcoma Through Integrated Genomic, Epigenomic, and Proteomic Analyses".

  Dataset EGAD00001004312

• Patient data used in FLTseq paper

  Apply newly developed FLT-seq protocol and package FLAMES on a primary patient sample

  Study EGAS00001005597

• BLUEPRINT Bisulfite-seq and Whole Genome Sequencing of mantle cell lymphoma

  BLUEPRINT Bisulfite-seq and Whole Genome Sequencing of mantle cell lymphoma

  Dataset EGAD00001001892

• 4C-Seq datasets of EndoC-bh1

  2 Circular chromosome conformation capture (4C-Seq) datasets of the human beta cell line EndoC-bh1.

  Dataset EGAD00001005210

• Reference epigenome IPS-NPC02 h3k36me3 ChIP-Seq data generated from KEP study

  IPS-NPC02 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007286

• Reference epigenome IPS-NPC02 h3k4me1 ChIP-Seq data generated from KEP study

  IPS-NPC02 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007287

• Reference epigenome IPS-NPC02 h3k9me3 ChIP-Seq data generated from KEP study

  IPS-NPC02 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007289

• Reference epigenome IPS-NPC02 input ChIP-Seq data generated from KEP study

  IPS-NPC02 input ChIP-Seq paired end data

  Dataset EGAD00001007290

• Reference epigenome IPS-ENeuron01 h3k27ac ChIP-Seq data generated from KEP study

  IPS-ENeuron01 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007291

• Reference epigenome IPS-ENeuron01 h3k27me3 ChIP-Seq data generated from KEP study

  IPS-ENeuron01 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007292

• Reference epigenome IPS-ENeuron01 h3k36me3 ChIP-Seq data generated from KEP study

  IPS-ENeuron01 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007293

• Reference epigenome IPS-ENeuron01 h3k4me1 ChIP-Seq data generated from KEP study

  IPS-ENeuron01 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007294

• Reference epigenome IPS-ENeuron01 h3k4me3 ChIP-Seq data generated from KEP study

  IPS-ENeuron01 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007295

• Reference epigenome IPS-ENeuron01 h3k9me3 ChIP-Seq data generated from KEP study

  IPS-ENeuron01 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007296