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IntOGen-mutations identifies cancer drivers across tumor types

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TLDR
The IntOGen-mutations platform provides support to cancer researchers, aids the identification of drivers across tumor cohorts and helps rank mutations for better clinical decision-making.
Abstract
The IntOGen-mutations platform (http://www.intogen.org/mutations/) summarizes somatic mutations, genes and pathways involved in tumorigenesis. It identifies and visualizes cancer drivers, analyzing 4,623 exomes from 13 cancer sites. It provides support to cancer researchers, aids the identification of drivers across tumor cohorts and helps rank mutations for better clinical decision-making.

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Genomic analyses identify molecular subtypes of pancreatic cancer

Peter Bailey, +128 more
- 03 Mar 2016 - 
TL;DR: Detailed genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing.
Journal ArticleDOI

The landscape of genomic alterations across childhood cancers

Susanne Gröbner, +185 more
- 15 Mar 2018 - 
TL;DR: The data suggest that 7–8% of the children in this cohort carry an unambiguous predisposing germline variant and that nearly 50% of paediatric neoplasms harbour a potentially druggable event, which is highly relevant for the design of future clinical trials.
Journal ArticleDOI

Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap

TL;DR: This protocol describes pathway enrichment analysis of gene lists from RNA-seq and other genomics experiments using g:Profiler, GSEA, Cytoscape and EnrichmentMap software, and describes innovative visualization techniques.
Journal ArticleDOI

The whole-genome landscape of medulloblastoma subtypes

Paul A. Northcott, +95 more
- 19 Jul 2017 - 
TL;DR: The application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma.
References
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Journal ArticleDOI

The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data

TL;DR: The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.
Journal ArticleDOI

A method and server for predicting damaging missense mutations.

TL;DR: A new method and the corresponding software tool, PolyPhen-2, which is different from the early tool polyPhen1 in the set of predictive features, alignment pipeline, and the method of classification is presented and performance, as presented by its receiver operating characteristic curves, was consistently superior.
Journal ArticleDOI

Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm.

TL;DR: This protocol describes the use of the 'Sorting Tolerant From Intolerant' (SIFT) algorithm in predicting whether an AAS affects protein function.
Journal ArticleDOI

Mutational heterogeneity in cancer and the search for new cancer-associated genes

Michael S. Lawrence, +96 more
- 11 Jul 2013 - 
TL;DR: A fundamental problem with cancer genome studies is described: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds and the list includes many implausible genes, suggesting extensive false-positive findings that overshadow true driver events.

Mutational heterogeneity in cancer and the search for new cancer genes

TL;DR: The MutSigCV method as mentioned in this paper applies mutational heterogeneity to exome sequences from 3,083 tumour-normal pairs and discovers extraordinary variation in mutation frequency and spectrum within cancer types, which sheds light on mutational processes and disease aetiology.
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