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Open Access Highly Accessed Methodology article

Identifying cancer mutation targets across thousands of samples: MuteProc, a high throughput mutation analysis pipeline

Alireza Hadj Khodabakhshi*, Anthony P Fejes, Inanc Birol and Steven JM Jones

Author Affiliations

Genome Sciences Centre, BC Cancer Agency, Suite 100 - 570 West 7th Ave, Vancouver, British Columbia, V5Z 4S6, Canada

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BMC Bioinformatics 2013, 14:167  doi:10.1186/1471-2105-14-167

Published: 28 May 2013



In the past decade, bioinformatics tools have matured enough to reliably perform sophisticated primary data analysis on Next Generation Sequencing (NGS) data, such as mapping, assemblies and variant calling, however, there is still a dire need for improvements in the higher level analysis such as NGS data organization, analysis of mutation patterns and Genome Wide Association Studies (GWAS).


We present a high throughput pipeline for identifying cancer mutation targets, capable of processing billions of variations across thousands of samples. This pipeline is coupled with our Human Variation Database to provide more complex down stream analysis on the variations hosted in the database. Most notably, these analysis include finding significantly mutated regions across multiple genomes and regions with mutational preferences within certain types of cancers. The results of the analysis is presented in HTML summary reports that incorporate gene annotations from various resources for the reported regions.


MuteProc is available for download through the Vancouver Short Read Analysis Package on Sourceforge: Instructions for use and a tutorial are provided on the accompanying wiki pages at webcite.