14980 results for "cancer studies using rna-seq"

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• RNA sequencing

  RNAseq of 45 high-grade serous ovarian cancer tumour samples. Libraries were generated using the NEB Ultra II Directional RNA library Prep kit with polyA enrichment. Libraries were sequenced as paired-end 50 or 100bp on an Illumina NextSeq or NovaSeq.

  Dataset EGAD00001009844

• Evaluation of triple negative breast cancer with heterogeneous immune infiltration

  This dataset contains the raw RNA-seq data (FASTQ files) of the samples used in the study title: "Evaluation of triple negative breast cancer with heterogeneous immune infiltration". The dataset is composed of 3 patients with 6 samples per patient (3 with high TILs and 3 with low TILs).

  Dataset EGAD00001010280

• SF11977 scRNA-Seq Primary GBM IDHR132H Wildtype Female

  SF11977 single cell RNA-seq IDHR132H Wild-type GBM Female, 61 Single Cell RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005391

• SF11979 scRNA-Seq Primary GBM IDHR132H Wild-type Female

  Single Cell-RNA Seq IDHR132H Wild-type Primary GBM Female, 76. Single Cell RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through cellranger count (10xGenomics.)

  Dataset EGAD00001005390

• SF11964 scRNA-Seq Low Grade Glioma IDHR132H mutant Male

  Single cell RNA-Seq Low Grade Astrocytoma IDHR132H mutant. Male, 64. Single Cell RNA seq from primary astrocytoma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

  Dataset EGAD00001005396

• Influence of culture media on airway differentiation at the Air-Liquid Interface

  Single-cell dataset of human airways after in vitro regeneration at the Air-Liquid Interface. Samples from 2 donors were used for the establishment of Human Bronchial Epithelial Cell cultures (HBECs) and were analyzed during proliferation, at the onset of differentiation (ALI0) and after full differentiation (ALI28), in 4 distinct culture media. Single-cell RNAseq was performed with 10x Genomics 3’ v2 RNA-seq using hashtag antibodies for multiplexing, and sequenced on a NextSeq 500. Samples from 3 additional donors were used for the establishment of Human Nasal Epithelial Cell cultures (HNECs) and were analyzed during proliferation in three distinct culture media. Single-cell RNAseq was performed with 10x Genomics 3’ v3 RNA-seq without multiplexing, and sequenced on a NextSeq 2000.

  Dataset EGAD00001011362

• RNA-seq

  RNA-seq data

  Dataset EGAD00001011376

• NCI Expanded Genome-Wide Association Study of Renal Cell Carcinoma

  The National Cancer Institute (NCI) expanded genome-wide association study (GWAS) of renal cell carcinoma (RCC) was a 2nd GWAS of this cancer performed by NCI to further investigate common genetic variants associated with RCC risk. The GWAS includes 2,781 cases and 2,940 controls of European background from 13 studies conducted in the US and Finland (10 cohorts, 2 case series, 1 hospital biorepository), scanned using the Illumina OmniExpress and Omni2.5 SNP arrays. SNP-level results from this GWAS were combined by meta-analysis with results from the earlier NCI RCC GWAS (phs000351.v1.p1; 1,311 cases and 3,424 controls) and others conducted by the International Agency for Research on Cancer (scan 1: 2,438 cases and 5,071 controls; scan 2: 2,781 cases and 2,940 controls), The University of Texas MD Anderson Cancer Center (893 cases and 556 controls) and the Institute for Cancer Research, UK (944 cases and 4,024 controls). Only data from the second NCI scan are included in this dbGaP submission. Data from 239 cases and 229 controls from this scan will be deposited in dbGaP separately under the Women's Health Initiative (phs000200).

  Study phs001736

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Pancreatic_Organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003520

• March 2017 data update (bam/fastq) (containing H3K27ac for CEMT_87, RNA-Seq for CEMT_141, CEMT_142, CEMT_145, CEMT_146, H3K27me3, H3K9me3, H3K4me3, H3K4me1, ChIP-Seq Input for CEMT_88, CEMT_90 and CEMT_91) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  March 2017 data update (bam/fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001003272