12310 results for "cancer rna-seq"

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• scRNA-seq of bulk and sorted NK

  Here we performed single-cell RNA sequencing to characterize NK cell subsets. Sorted NK cell subsets representing discrete stages of NK cell differentiation as well as bulk NK cells were sequenced.

  Dataset EGAD50000000020

• RNA-Seq soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001008467

• Covacta RNAseq counts

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes read counts per gene. Read counts were generated for the Gencode v27 annotation using the summarize Overlaps method from bioC in mode “IntersectionStrict”

  Dataset EGAD00001011164

• Single-cell RNA sequencing of Small Intestinal Neuroendocrine Tumors (SI-NET)

  Single-cell RNA sequencing (scRNA-seq) was performed on cells isolated from intestinal mucosa and small intestinal neuroendocrine tumors (SI-NETs) to compare their transcriptomic profiles. Tumor and adjacent normal tissues were collected from two SI-NET patients, enzymatically dissociated, and processed into single-cell suspensions. Single-cell libraries were generated using the Chromium Single Cell 3′ Reagent Kit v3 and sequenced on an Illumina platform to produce FASTQ files for downstream analysis.

  Dataset EGAD50000002265

• RNA-seq after drug perturbation of primary lymphoma samples

  3'-end low-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule inhibitors (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). Sequencing was performed on the Illumina HiSeq4000. The dataset contains FASTQ files.

  Dataset EGAD50000002166

• Human glioblastoma single cell RNA-seq from two patient, sampled at different positions within as well as outside tumor

  We performed deep single-cell RNA sequencing of two rare glioblastoma cases where tissue could be sampled from tumor core to macroscopically normal cortex. We processed two to three replicates per sample with the 10X Genomics V3.1 kits. Deep sequencing was performed to about 100,000 reads per cell on the Illumina NovaSeq 6000 platform, resulting in a total of 37 BAM files.

  Dataset EGAD50000001500

• WGS,RNA data of patients with multiple myeloma (MM) refractory to immunomodulatory agents (IMiDs) and proteasome inhibitors (PIs)

  Paired WGS and RNA-Seq data of patients with multiple myeloma (MM) refractory to immunomodulatory agents (IMiDs) and proteasome inhibitors (PIs). We performed whole genome and transcriptome sequencing of 39 heavily pretreated RRMM patients with at least double refractoriness revealing complex structural changes and a high mutational load.

  Dataset EGAD00001006189

• Paired RNA-Seq data from 17 samples of different tumors

  Paired RNA sequencing data (21 runs/ 17 samples) of different tumors. The samples were prepared using the Illumina TruSeq stranded mRNA Kit. The sequencing was done on Illumina HiSeq 4000.

  Dataset EGAD00001009706

• RNA-Seq of GM adipose tissue samples

  This dataset contains 210 fastq files (RNA sequencing was performed in two centers) from 105 individuals (106 files in subcutaneous tissue and 104 files in visceral tissue). Of the 210 fastq files, 129 files are in PEx100 mode (appeared in a single fastq file) and 81 files are in PEx49bp mode (appeared in two separate fastq files). Sequencing was done on the Illumina HiSeq2000 platform.

  Dataset EGAD00001010253

• Perturb-seq dataset

  We performed a systematic, genome-wide investigation of enhancer regions in colorectal cancer (CRC). We identified 12,117 putative enhancer regions using H3K27ac and H3Kme1 ChIP-seq and ATAC-seq. We performed scRNA-seq in HT29 and SW480 (MSS CRC cell lines) using the Parse Biosciences WT-mega kit with CRISPRi/dCas9 inhibition of these regions (Perturb-seq). The Parse split-pipe pipeline was used to demultiplex the raw fastq files into the processed files (mtx files for genes and gRNA) for each cell line.

  Dataset EGAD50000000375