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• Whole-exome sequencing of meningiomas for integrative molecular classification.

  Exome libraries were prepared using 100ng DNA of tumor tissue or matched normal DNA. Exome capture was performed using Agilent SureSelect Human Exome Library Preparation V5 or V6 COSIMC + kits.

  Dataset EGAD00001007051

• WXS and RNA-seq raw sequence data for TG project

  WXS sequence data from 112 samples, RNA-seq sequence data from 117 samples, all sequence data are raw sequence data in fastq format, sequenced by Illumina platform.

  Dataset EGAD00001007989

• MutWP4: CRUK Grand Challenge Mutographs of Cancer: Pancreatic Organoids (2021-02-02)

  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. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006933

• sWGS of core biopsies from localized breast cancer patients

  Paired end shallow whole genome sequencing (sWGS) data for the identification of genomewide somatic copy number alterations (SCNA) and the estimation of tumor fractions.

  Dataset EGAD00001008397

• NuGen Targeted Sequencing of 574 DLBCL Cases of Non-China Cohort from Phoenix Clinical Trial

  NuGen 99-Gene-Panel Targeted Sequencing of 574 DLBCL Cases of Non-China Cohort from Phoenix Clinical Trial. Check the Associated Publication for More Experimental Details.

  Dataset EGAD00001008132

• cfDNA and CDX/PDX methylation profiling in Small Cell Lung Cancer

  This study contains methyl-binding domain sequencing and shallow whole genome sequencing from circulating free DNA (cfDNA) for 79 patients with small cell lung cancer (SCLC) and 78 non-cancer controls. We also sequence genomic DNA (both methyl-binding domain sequencing and shallow whole genome sequencing) from 30 circulating-tumour-cell derived explant models (CDXs, from 23 unique patients with SCLC), 20 patient derived explant models (PDXs, from 10 unique patients with SCLC) and 13 lung tissue samples.

  Dataset EGAD00001008673

• RNA, ATAC, ChIP datasets from Ankylosing Spondylitis patients and Healthy Controls

  This dataset consists of functional genomic data from 20 Ankylosing Spondylitis patients and 35 Healthy Controls taken from CD4+ T cells, CD8+ T cells and CD14 Monocytes. It contains 364 paired end fastq files consisting of 104 total RNA-seq samples and 116 ATAC samples, for ChIP there are 46 H3K4me3 samples, 46 H3K27ac samples and 3 H3K4me1 samples, along with 49 paired input samples. The samples were sequenced on Illumina HiSeq4000, Illumina NextSeq500 and Illumina NovaSeq 6000 platforms.

  Dataset EGAD00001008758

• Dataset for urologic_cancer-RNA

  Rare cancer sequencing data of 75 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008851

• Dataset for head_and_neck_cancer-RNA

  Rare cancer sequencing data of 92 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008861

• Dataset for soft_tissue_tumor-EXON

  Rare cancer sequencing data of 246 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008897