4772 results for "*oma"

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• Multiple myeloma follow-up Dataset

  77 samples collected from 35 multiple myeloma patients. Each patient provided one healthy sample and one primary tumor sample and, in some cases, also samples collected after the progression of the disease.

  Dataset EGAD00001010161

• RNA-Seq data on multiple myeloma CD138positive bone marrow plasma cells

  RNA-Seq data on multiple myeloma CD138positive bone marrow plasma cells, 11 samples, sequenced on HiSeq 4000 and HiSeq X-Ten, using mostly the TruSeq stranded mRNA Kit.

  Dataset EGAD00001008619

• WGS of primary mesothelioma cell lines

  Mesothelioma is an aggressive cancer associated with previous exposure to asbestos and dismal prognosis. Since a pemetrexed/cisplatin combination was introduced for treatment of mesothelioma, no new first- or second-line therapies have been discovered. Thus, to better understand what drives mesothelioma carcinogenesis and to identify potential targets for therapy, in this project we aim at performing WGS analysis of a panel of mesothelioma cells lines.

  Dataset EGAD00001009641

• RNAseq of primary mesothelioma cell lines

  Mesothelioma is an aggressive cancer associated with previous exposure to asbestos and dismal prognosis. Since a pemetrexed/cisplatin combination was introduced for treatment of mesothelioma, no new first- or second-line therapies have been discovered. Thus, to better understand what drives mesothelioma carcinogenesis and to identify potential targets for therapy, in this project we aim at performing RNAseq analysis of a panel of mesothelioma cells lines.

  Dataset EGAD00001009642

• Single cell atlas of neuroblastoma and the human fetal adrenal gland

  Using the chromium 3' expression assay, we generated an atlas of neuroblastoma and the human fetal adrenal gland. These data were complemented with whole genome sequencing of normal and tumour DNA from the neuroblastoma samples.

  Dataset EGAD00001008345

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

  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. 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 2020-02-20.

  Dataset EGAD00001005994

• RNAseq BAM files

  RNAseq BAM files for Coding and non-coding mantle cell lymphoma driver mutations

  Dataset EGAD00001006268

• Human tumor single-cell

  We profiled 11 patient tumor samples by single-cell and single-nuclei RNA-seq using 10X Chromium 3'. These include samples from the following entities: WNT-subtype medulloblastoma (N=3), embryonal tumors with multilayered rosettes (N=3), and atypical teratoid-rhabdoid tumors (N=5). The BAM files are provided.

  Dataset EGAD00001005129

• WGS data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  WGS data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  Dataset EGAD00001008646

• Whole transcriptome sequencing of 38 follicular lymphoma tumours.

  This data set includes RNAseq from 38 follicular lymphoma tumours. All tumours were fresh frozen. Libraries were constructed by enriching for poly-A transcripts and sequenced as 75bp paired end reads on an Illumina HiSeq 2500 instrument.

  Dataset EGAD00001009650