12000 results for "cancer rna-seq"

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• Reference epigenome Islet-derived_MSC06 miRNA-Seq data generated from KEP study

  Islet-derived_MSC06 miRNA-Seq single end data

  Dataset EGAD00001007881

• Reference epigenome CKD23_C_Mesan_smRNA-Seq data generated from KEP study

  A CKD23_C_Mesan_smRNA-Seq single end data for Mesangial cells(kidney)

  Dataset EGAD00001003497

• Reference epigenome CKD27_C_Mesan_smRNA-Seq data generated from KEP study

  A CKD27_C_Mesan_smRNA-Seq single end data for Mesangial cells(kidney)

  Dataset EGAD00001003500

• Reference epigenome CKD23_C_Mesan_mRNA-Seq data generated from KEP study

  A CKD23_C_Mesan_mRNA-Seq paired end data for Mesangial cells(kidney)

  Dataset EGAD00001003481

• Reference epigenome KNIH010 mRNA-seq data generated from KEP study

  A KNIH010 mRNA-seq paired end data for podocytes

  Dataset EGAD00001002176

• Reference epigenome KNIH011 mRNA-seq data generated from KEP study

  A KNIH011 mRNA-seq paired end data for podocytes

  Dataset EGAD00001002177

• Reference epigenome CKD27_C_Mesan_mRNA-Seq data generated from KEP study

  A CKD27_C_Mesan_mRNA-Seq paired end data for Mesangial cells(kidney)

  Dataset EGAD00001003484

• Histone marks

  EZH2, H3K4me3, H3K27ac and H3K27me3 ChIP-seq data consisting of fastq single-end reads from peripheral blood CLL cells

  Dataset EGAD00001004063

• Reference epigenome KNIH011 miRNA-seq data generated from KEP study

  A KNIH011 miRNA-seq single end data for podocytes

  Dataset EGAD00001002770

• Single cell RNA sequencing of human cord Blood CD34 Cells

  We performed single cell RNA sequencing and ATAC e valuation of human umbilical cord blood. To explore the differentiation pathway for human lymphoid lineage, our target cells contain CD34-positive cord blood. That population is evaluated by single cell RNA sequencing and single cell ATAC.

  Study JGAS000528

• Whole genome sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  Paired-end 150 basepair whole genome sequencing of 94 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. Libraries were prepared using the Illumina® TruSeq™ DNA Nano library preparation method according to the manufacturer’s instructions at The University of Melbourne Centre for Cancer Research (UMCCR) using 200ng input DNA and a 550 base pair insert size. Samples were sequenced in separate batches on the Illumina® Nova-Seq 6000 according to manufacturer’s instructions (Illumina, USA). Included in this dataset are FASTQ format files containing raw read data, CRAM format files containing reads aligned to GRCh38, and VCF format files containing germline variants calls.

  Dataset EGAD50000000502

• RNA-sequencing of tumors from 45 patients with recurrent or metastatic gastric cancer treated with immune checkpoint inhibitors

  Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this work, we used our machine learning algorithm NTriPath to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identified four molecular subtypes that were prognostic for survival. We then built a support vector machine with linear kernel and the binary classifier to generate a risk score that is prognostic for 5-year overall survival and validated the risk score using three independent datasets. We also found that the molecular subtypes predicted response to adjuvant 5-fluorouracil and platinum after gastrectomy and immune checkpoint inhibitors in patients with metastatic or recurrent disease. The 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated in a prospective manner. This EGA archive includes both St.Mary hospital cohort samples (n=28) and Yonsei immunotherapy patient samples (n=17).

  Study EGAS00001005588

• 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 EGAD00001006398

• Dataset for B-ALL scRNA-seq

  10x Genomics 5' library scRNA-seq data for 85 B-ALL patients with different subtypes

  Dataset EGAD00001011327

• Reference epigenome Fat-adipocyte04 mRNA-Seq data generated from KEP study

  Fat-adipocyte04 mRNA-Seq paired end data

  Dataset EGAD00001007158

• Reference epigenome Pancreas-Islet08 mRNA-Seq data generated from KEP study

  Pancreas-Islet08 mRNA-Seq paired end data

  Dataset EGAD00001007168

• Reference epigenome Fat-adipocyte03 mRNA-Seq data generated from KEP study

  Fat-adipocyte03 mRNA-Seq paired end data

  Dataset EGAD00001007157

• Reference epigenome Fat-adipocyte05 mRNA-Seq data generated from KEP study

  Fat-adipocyte05 mRNA-Seq paired end data

  Dataset EGAD00001007159

• Reference epigenome Islet-derived_MSC06 mRNA-Seq data generated from KEP study

  Islet-derived_MSC06 mRNA-Seq paired end data

  Dataset EGAD00001007878

• Reference epigenome SMC05 h3k9me3 ChIP-Seq data generated from KEP study

  SMC05 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007336

• Reference epigenome Pancreas-Islet07 mRNA-Seq data generated from KEP study

  Pancreas-Islet07 mRNA-Seq paired end data

  Dataset EGAD00001007167

• Reference epigenome Pancreas-Islet06 mRNA-Seq data generated from KEP study

  Pancreas-Islet06 mRNA-Seq paired end data

  Dataset EGAD00001007166

• Reference epigenome SMC01 h3k4me3 ChIP-Seq data generated from KEP study

  SMC01 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007311

• Reference epigenome OB56_N_PreA_smRNA-Seq data generated from KEP study

  A OB56_N_PreA_smRNA-Seq single end data for Preadipocytes(fat)

  Dataset EGAD00001003495

• Reference epigenome OB57_D_PreA_mRNA-Seq data generated from KEP study

  A OB57_D_PreA_mRNA-Seq paired end data for Preadipocyte(fat)

  Dataset EGAD00001003487