11768 results for "cancer rna-seq"

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• TIRE-seq_PDN

  TIRE-seq is a novel RNA sequencing method that integrates mRNA purification directly into library preparation, eliminating separate RNA extraction. The technique demonstrated utility across three biological applications, including capturing transcriptional changes in human T cells, identifying genes driving murine dendritic cell differentiation, and analyzing the dose-response effects of temozolomide on patient-derived neurospheres. With its simplified approach and high sequencing efficiency, TIRE-seq offers a cost-effective solution for large-scale gene expression studies.

  Dataset EGAD50000001261

• 3' mRNA- sequencing bams

  This project stores bam files from 3'RNA-seq from oesophageal adenocarcinoma at different timepoints during neoadjuvant treatment (prior, during, post treatment), which were used to analyse evolutionary and phenotype dynamics in oesophageal adenocarcinoma. Samples were collected within the clinical MEMORI trial.

  Study EGAS50000000242

• Single-cell RNA-seq Libraries via 10x Genomics and Illumina NovaSeq

  This dataset contains single-cell RNA-seq libraries prepared using the Chromium Single Cell 5' Library & Gel Bead Kit v1.1 (10x Genomics). Cells were partitioned into nanoliter-scale GEMs for barcoding and reverse transcription, followed by amplification and purification of cDNAs. Libraries were sequenced on an Illumina NovaSeq 6000 using 150 bp paired-end reads, ensuring high-resolution transcriptomic profiling.

  Dataset EGAD50000001680

• Transcriptome analysis of Familial dysautonomia patient cells treated with splice-regulating compounds

  In order to investigate familial dysautonomia patient fibroblasts in response to splice-regulating compounds, cells were treated with RECTAS or TG003 and transcriptome study was conducted by RNA-seq. Splicing profiles of cells in each condition were then analyzed.

  Study JGAS000170

• Transcriptome analysis of Fabry disease iPSC-derived cardiomyocytes treated with splice-regulating compound; RECTAS

  In order to investigate transcriptome profiles in response to splice-regulating compounds, iPSC-derived cardyomyocytes were treated with RECTAS and transcriptome study was conducted by RNA-seq. Splicing profiles of cells in each condition were then analyzed.

  Study JGAS000225

• Analyses of transcriptome and epigenome in cardiac fibroblasts

  We report genome-wide bulk RNA- and ATAC-seq analysis of cardiac fibroblasts isolated from two patients. Cells were pre-treated with either KAT5 inhibitor or vehicle, and their fibrotic responses after TGF-β stimulation was measured.

  Study EGAS50000000835

• Methylation profiles in patients with blastic plasmacytoid dendritic cell neoplasm

  We added 7 additional samples to our previous cohort (EGAS00001006166). Each samples comprises RNA-seq and whole exome sequencing data. Methylation EPIC Array data have been deposited in Gene Expression Omnibus (GEO) under accession number GSE230487.

  Study EGAS00001007201

• BLUEPRINT release August 2016, RNA-Seq for granulocyte monocyte progenitor cell, on genome GRCh38

  RNA-Seq data for 3 granulocyte monocyte progenitor cell sample(s). 3 run(s), 3 experiment(s), 3 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002306

• BLUEPRINT release August 2016, RNA-Seq for hematopoietic stem cell, on genome GRCh38

  RNA-Seq data for 6 hematopoietic stem cell sample(s). 13 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002316

• Data for Paper: Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  mRNA, total RNA, small noncoding RNA, NOMe-Seq and DNase-Seq data from following samples (not every Sequencing Type for every sample): 01_HepG2_LiHG_Ct1 41_Hf01_LiHe_Ct 41_Hf02_LiHe_Ct 41_Hf03_LiHe_Ct 51_Hf03_BlCM_Ct 51_Hf04_BlCM_Ct 51_Hf03_BlEM_Ct 51_Hf04_BlEM_Ct 51_Hf03_BlTN_Ct 51_Hf04_BlTN_Ct Metadata available at deep.dkfz.de

  Dataset EGAD00001002735