12040 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

• MDACC Lymphoma & Myeloma The function of LAMP5 in multiple myeloma

  This dataset includes Fastq files from bulk RNA seq from myeloma cell lines (MM.1S and NCI-H929) expressing a DOX-inducible LAMP5 shRNA, S1 (CACTTCAAAGACGCAGTCAGT) or S5 (GCACACAGAATACAACCTCAT), or a scramble control treated with DOX during 48h.

  Dac EGAC50000000495

• DynaTag for efficient profiling of transcription factors in small samples and single cells

  The dataset included Dynatag data for the occupancy of transcription factors and single nuclei RNA-seq data. Corresponding metadata is provided for both experiments.

  Dataset EGAD50000001562

• RNA-Seq soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001008467

• Single cell RNA seq of the developing human embryo brain

  The study aims at identifying the cell types and lineages of the developing human brain.

  Study EGAS00001004107

• preinvasive LUAD

  Whole-exome sequencing coupled with RNA-seq of preinvasive (n=98) and invasive (n=99) lung adenocarcinoma samples.

  Dataset EGAD00001005479

• PDAC organoid genomic heterogeneity

  Two primary tumor-derived PDAC organoids were subjected to SNP array, RNA-seq, and single-cell WGS.

  Dataset EGAD00001009741

• NASH RNA-seq data

  This dataset includes transcriptome sequencing of 17 paired NAFLD-HCC samples and adjacent normal tissues. All the experiments were performed on Illumina HiSeq 2000 platform with raw reads stored in fastq format.

  Dataset EGAD00001004326

• 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

• RNA sequencing of follicular T cell lymphoma

  Study EGAS00001004646