How to identify oncogenic driver mutations: a review of bioinformatics approaches

Screen Shot 2014-07-16 at 5.51.18 AMRecently, at least three articles have reviewed the ensemble of bioinformatics tools developed in the past few years to understand the alterations that plague the genome and transcriptome of tumor cells. The first one (in chronological terms), published in Nature Methods one year ago –co-authored by us within the ICGC mutations consequence and pathways working subgroup– focused on the annotation of cancer variants and the tools aimed at the identification of driver mutations and driver genes. The next two, appeared in Genome Medicine and Nature Reviews Genetics covered tools involved across the whole process of cancer mutations analysis, from the calling of somatic mutations to the analysis of significantly mutated pathways or gene modules within genes interactions networks.

 

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Mutual exclusion statistics and data events in Gitools

We’re pleased to announce another incremental release of Gitools, version 2.2. Amongst the many improvements (listed at the bottom of this post) we’d like to highlight the effort that we put into improving performance, specifically with genomic data: mutual exclusion and co-occurrence statistics coupled with a new feature called “data events” – which helps to get a quick grasp of the data.

Low expression events ordered by mutual exclusion

Low expression data events events ordered by mutual exclusion

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