9338 results for "cancer rna-seq"

in 30.23 milliseconds.

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002899

• snRNA-seq/snATAC-seq multiome of first and second trimester human gonads - HUGODECA dataset

  Comprehensive map of first- and second-trimester gonadal development in humans using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays, and imaging. ArrayExpress Accession: E-MTAB-11708

  Dataset EGAD00001009388

• Single-cell ATAC-seq of matched pediatric AML tumors

  Single-cell ATAC-seq of pediatric AML tumours from patients enrolled in the clinical trial AAML1031. Obtained using the 10X Chromium NextGEM Single Cell ATAC Reagent Kit, v1.1. A total of 64 samples were obtained from biopsies at diagnosis, remission and relapse from 25 patients.

  Dataset EGAD00001011194

• CTD-ILD BALF and blood scRNA-seq dataset

  CTD-ILD BALF and blood scRNA-seq dataset consists of single-cell transcriptome data of bronchoalveolar lavage fluid (BALF) and blood derived from 30 connective tissue disease-associated interstitial lung disease (CTD-ILD) and 12 idiopathic interstitial pneumonia (IIP) patients.

  Dataset EGAD00001011334

• EGAS00001003405 combined RNA, WES, WGS data of 16 gastrointestinal tumor patients

  50 samples of 16 individuals with Gastrointestinal Tumor. Patients were sequenced in various combinations of WGS, Exome and RNA sequencing.

  Dataset EGAD00001005113

• Single nuclei RNA-sequencing of glioblastoma tumors

  Single nuclei RNA-sequencing of snap frozen glioblastoma tumor tissue with 10x Genomics 3' expression (v2 chemistry). Aligned to GRCh38 reference genome with intron using CellRanger.

  Dataset EGAD00001006802

• Single cell RNA-sequencing of glioblastoma stem cell lines

  Single cell RNA-sequencing of glioblastoma stem cell (GSC) lines with 10x Genomics 3' expression (v2 chemistry). Aligned to GRCh38 reference genome using CellRanger.

  Dataset EGAD00001006804

• Single-cell RNA sequencing of bronchoalveolar lavages from COVID-19 patients

  Single-cell RNA sequencing of bronchoalveolar lavages from COVID-19 patients.

  Dataset EGAD00001006893

• RNA sequencing upon depletion of RAF kinases vs. MAPK inhibition in KRAS mutant cells

  RNA Sequencing upon shRNA mediated depletion of RAF kinases or treatment with Cobimetinib (GDC-0973, 250nM, 6hrs) or with pan RAFi (AZ-628, 10uM, 6hrs)

  Dataset EGAD00001008384

• Osteosarcoma capture-based RNA sequencing

  This dataset includes 23 specimens from osteosarcoma patients (primary, relapsed, metastatic). It contains bam files from RNA sequencing using a library in which coding regions of cDNA are captured and short-read, paired-end sequencing.

  Dataset EGAD00001008434

• Clear cell sarcoma dataset

  This deposit consists of DNA and RNA sequencing data from 67 CCS samples. 55 samples had tumor DNA sequencing data. 6 had matched normal sequencing data. 34 samples had tumor RNA sequencing data.

  Dataset EGAD00001008611

• RNA sequencing of adult T-cell leukemia/lymphoma

  RNA sequencing of 57 tumor samples of adult T-cell leukemia/lymphoma as well as 3 samples of HTLV-1 carrier and 3 samples of healthy volunteers.

  Dataset EGAD00001001411

• Paired RNA sequencing of 30 samples RRMM (multiple myeloma)

  Paired RNA sequencing of 30 samples RRMM using Illumina TruSeq stranded mRNA kit and either HiSeq2000 or HiSeq X Ten for sequencing.

  Dataset EGAD00001009680

• Sequencing data for oesophageal and related samples - Abbas et al (RNA)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (RNA for 197 samples)

  Dataset EGAD00001011269

• PhIP-Seq data

  Inflammatory bowel diseases (IBD), e.g. Crohn’s disease (CD) and ulcerative colitis (UC), are chronic immune-mediated inflammatory diseases. A comprehensive overview of an IBD-specific antibody epitope repertoire is, however, lacking. We leveraged a high-throughput phage-displayed immunoprecipitation sequencing (PhIP-seq) workflow to identify antibodies against 344,000 antimicrobial, immune and food antigens in 497 IBD patients.

  Study EGAS00001007054

• ChIP-seq data of H3K4me3, H3K27ac and H3K27me3 on multiple human embryonic tissues.

  The regulatory landscape of the human genome during organogenesis is undescribed for most tissues. We used ChIP-seq to survey histone modifications in 13 human embryonic tissues. We describe patterns of both common and tissue-specific marking of promoter activation and repression and use enhancer usage to infer regulatory pathways.

  Study EGAS00001003163

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  ChIP-Seq data for 172 CD14-positive, CD16-negative classical monocyte sample(s). 572 run(s), 345 experiment(s), 340 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002672

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  ChIP-Seq data for 154 CD4-positive, alpha-beta T cell sample(s). 355 run(s), 265 experiment(s), 250 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002673

• scRNA-seq dataset of patient and healthy donors

  scRNA-seq dataset on a patient (P) presenting with defects of immunity and four healthy donors (C1, C2, C3, C4). This dataset contains raw and processed files from scRNA-seq performed on samples using the 10x Genomics Chromium Controller with the Chromium Single Cell 3′ Reagent Kit (v3 chemistry). There are 15 paired-end fastq files (3 per patient/donor - I1, R1, R2) and 15 processed files generated with 10x Genomics Cell Ranger v3.0.2 software against GRCh38 human reference transcriptome (3 per patient/donor - barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz).

  Dataset EGAD00001008372

• ChIP-seq on Hodgkin lymphoma DAC

  Dac EGAC00001001007

• Henssen Lab Neuroblastoma Circle-seq Data

  Dac EGAC00001001803

• DAC for cfMethyl-Seq data

  Dac EGAC00001002534

• SCA3_RNA-Seq Data Access Committee

  Dac EGAC00001002840

• Genomic features of Helicobacter pylori-na��ve diffuse-type gastric cancer.

  Helicobacter pylori (HP) is a major etiologic driver of diffuse-type gastric cancer (DGC). However, improvements in hygiene have led to an increase in the prevalence of HP-na��ve DGC; that is, DGC that occurs independent of HP. Although multiple genomic cohort studies for gastric cancer have been conducted, including studies for DGC, distinctive genomic differences between HP-exposed and HP-na��ve DGC remain largely unknown. Here, we employed exome and RNA sequencing with immunohistochemical analyses to perform binary comparisons between 36 HP-exposed and 27 HP-na��ve DGCs from sporadic, early-stage, and intramucosal or submucosal tumor samples. Among the samples, 33 HP-exposed and 17 HP-na��ve samples had been preserved as fresh-frozen samples. HP infection status was determined using stringent criteria. HP-exposed DGCs exhibited an increased single nucleotide variant burden (HP- exposed DGCs; 1.97 [0.48���7.19] and HP-na��ve DGCs; 1.09 [0.38���3.68] per megabase; p=0.0003) and a higher prevalence of chromosome arm-level aneuploidies (p<0.0001). CDH1 was mutated at similar frequencies in both groups, whereas RHOA���ARHGAP pathway misregulation was exclusive to HP-exposed DGCs (p=0.0167). HP-exposed DGCs showed gains in chromosome arms 8p/8q (p<0.0001), 7p (p=0.0035) and 7q (p=0.0354), and losses in 16q (p=0.0167). Immunohistochemical analyses revealed a higher expression of intestinal markers such as CD10 (p<0.0001) and CDX2 (p=0.0002) and a lower expression of the gastric marker, MUC5AC (p=0.0305) among HP-exposed DGCs. HP-na��ve DGCs, on the other hand, had a purely gastric marker phenotype. This work reveals that HP-na��ve and HP-exposed DGCs develop along different molecular pathways, which provide a basis for early detection strategies in high incidence settings.

  Study JGAS000575

• T-cell receptor sequencing of tumor-infiltrating lymphocytes (TIL) in breast cancer

  The spatial distribution of tumor-infiltrating lymphocytes (TIL) predicts breast cancer outcome and response to systemic therapy, highlighting the importance of an intact tissue structure for characterizing patients’ tumors. Here, we present ST-FFPE, a spatial transcriptomics method for the analysis of formalin-fixed paraffin-embedded samples, which opens the possibility of interrogating widely available archival tissue. The method involves extraction, exome capture and sequencing of RNA from different tumor compartments microdissected by laser-capture, and can be used to study the cellular composition of various tumor environments. Focusing on triple-negative breast cancer (TNBC), we characterized T cells, B cells, dendritic cells, fibroblasts and endothelial cells in both stromal and intra-epithelial compartments. We found a highly variable spatial distribution of immune cell subsets among tumors. This analysis revealed that the immune repertoires of intra-epithelial T and B cells were consistently less diverse than those of stromal T and B cells. T-cell receptor (TCR) sequencing confirmed a reduced diversity and revealed higher clonality of intra-epithelial T cells relative to the corresponding stromal T cells. Analysis of the top ten dominant clonotypes in the two compartments showed a majority of shared but also some unique clonotypes both in stromal and intra-epithelial T cells. Hyperexpanded clonotypes were more abundant among intra-epithelial than stromal T cells. These findings validate the ST-FFPE method and suggest an accumulation of antigen-specific T cells within tumor core. Because ST-FFPE is readily applicable for analysis of previously collected tissue samples, it could be useful for rapid assessment of intratumoral cellular heterogeneity in multiple disease and treatment settings.

  Study EGAS00001007125