7081 results for "canc*"

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• Cancer gene panel (T200.1) sequencing analysis of adult type ovarian granulosa cell tumors (Validation cohort from Hillman, et al)

  Cancer gene panel (T200.1) sequencing data from tumor/normal pairs for adult type ovarian granulosa cell tumor sequencing project. This data set contains 55 tumor panel sequencing data and 44 matched normal panel sequencing data generated using the MD Anderson Cancer Center T200.1 cancer gene hybrid capture platform, with sequencing performed on an Illumina HiSeq 2000. This dataset contains BAM files generated by aligning paired-end reads to the hg19 reference genome.

  Dataset EGAD00001004091

• Single Cell Genome Sequence for DLP+ library A98247A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA530 passage 3 on DLP+ library A98247A

  Dataset EGAD00001009646

• Whole Exome Sequencing of Oro-Gastrointestinal tract cancers

  54 samples consisting of COAD, ESCC, GA and OSCC

  Dataset EGAD00001008455

• SPECTA Lung cancer DNA FASTQ files

  SPECTA Lung cancer DNA FASTQ files (Illumina TST170 targeted analysis)

  Dataset EGAD00001006223

• 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

• Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  Dataset EGAD00001006237

• Matched Pair Cell Line Tumour RNAseq

  In this study we will sequence the transcriptome of Verified Matched Pair Cancer Cell line tumour samples. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found.

  Dataset EGAD00001000630

• Epigenomic profile of diverse cancer

  The samples are from patients of multiple cancer types. The library preparation protocol was developed by the laboratory. The DNA libraries were then sequenced with 150bp paired-end reads.

  Dataset EGAD00001006124

• Sequencing data for the manuscript "Multi-focal sampling of de novo metastatic prostate cancer reveals complex polyclonality and enables accurate clinical genotyping"

  This submission includes targeted and whole exome paired-end fastq files.

  Dataset EGAD00001009651

• Mutation analysis of core biopsies from localized breast cancer patients

  Targeted next-generation sequencing (NGS) of 93 frequently mutated genes in breast cancer using the QIAseq Human Breast Cancer Targeted Panel (QIAGEN), which uses digital sequencing by incorporating unique molecular barcodes (UMI).

  Dataset EGAD00001008396