March 11, 2015. Invited presentation at the University of Ontario Institute of Technology

SHARCNET Scientific Computing Seminar Series

Wednesday 11 March, 11am-12pm, ERC 1056

Peter K. Rogan, CRC (Tier I) in Genome Bioinformatics, Department of Biochemistry & Department of Computer Science, University of Western Ontario, and

Cytognomix Inc, London ON

Mutation Forecaster, a software resource for genome-scale analysis of complete genes and human genomes

Complete genome sequencing is now feasible, becoming cost effective, and increasingly an essential component of cancer discovery and patient genomic analyses. This has created a bottleneck in interpretation of gene variants, partly because the effects of most variants remain unknown (variants of unknown significance, VUS), and also because interpretation is confounded by the lack of corresponding genetic information from closely related family members.   The VUS problem is now exacerbated by the discovery of massive numbers of variants in each genome, many never before seen. Technologies that prune variants in an individual are essential to perform any large scale gene panel, exome or genome analysis.  The variant analysis approaches I will describe improves complete gene and genome sequence analyses and by detecting dysregulated biochemical pathways.  We stratify variants by mutation severity, which can suggesting or exclude particular therapeutic options (Shirley et al. 2013 <http://www.sciencedirect.com/science/article/pii/S1672022913000296>; Dorman et al. 2014 <http://www.nature.com/srep/2014/141114/srep07063/full/srep07063.html>; Mucaki et al. 2011 <http://www.ncbi.nlm.nih.gov/pubmed/21523855>; Mucaki et al. 2013 <http://onlinelibrary.wiley.com/doi/10.1002/humu.22277/full>, Viner et al. 2014 <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983938.1/>).Our patented software computes changes in information content in DNA or RNA sequences. These changes tell us which sequences disrupt the regulation of genes and how severe these changes are.   Our methods have been validated in hundreds of published studies (Caminsky et al. 2014 <http://f1000research.com/articles/3-282/v1>), and use proven information theory, one of the most important scientific advances of the last century. I will introduce a single system that amalgamates several of our software products, and which also queries existing public databases and store results for users. MutationForecaster <http://mutationforecaster.com/> provides basic capabilities offered by others, but also offers proven mutation interpretation  methods not available elsewhere. This leads to more comprehensive mutation results and ultimately, a more complete understanding of the dysregulation of disease genomes.