5270 results for "*oma"

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• Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic squamous cell carcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005850

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005851

• Genome and transcriptome sequence data from a lung carcinoma patient

  Genome and transcriptome sequence data from a lung carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005853

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Oesophageal adenocarcinoma

  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, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors 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. This dataset contains all the data available for this study on 2021-09-27.

  Dataset EGAD00001006083

• Whole genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes

  The dataset comprises of an aggregate level VCF (version 4.1), containing the somatic point and indel mutations found across the glioblastoma cohort (SweGBM-1, n=38 samples). The VCF file is in accordance with the HTS format specifications (https://samtools.github.io/hts-specs/).

  Dataset EGAD00001006084

• RNA-seq of pcAECyTCL

  RNA sequencing of frozen tumor biopsies from patients with primary cutaneous CD8+ aggressive epidermotropic cytotoxic T-cell lymphoma. 6 samples. Illumina HiSeq 4000.

  Dataset EGAD00001006085

• WGS of pcAECyTCL

  Whole-genome sequencing of frozen tumor biopsies from patients with primary cutaneous CD8+ aggressive epidermotropic cytotoxic T-cell lymphoma. 12 samples. Illumina HiSeq X-Ten.

  Dataset EGAD00001006086

• Targeted panel sequencing for brainstem glioma

  Targeted panel sequencin on Illumina HiSeq X Ten of brainstem glioma primary tumor and blood samples

  Dataset EGAD00001006093

• RNAseq for brainstem glioma

  RNAseq on Illumina HiSeq X Ten of brainstem glioma primary tumor sample

  Dataset EGAD00001006094

• Glioblastoma stem cell lines RNA-seq

  RNA-seq data for three Glioblastoma stem cell (GSC) lines exposed to PRMT5 inhibitor and control samples.

  Dataset EGAD00001006095