Our paper, “Interpretation of mRNA splicing mutations in genetic disease: review of the literature and guidelines for information-theoretical analysis,” and video,  “Interpreting genomic variants in rare and common diseases,” have been highlighted by F1000Research on their home page.

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.

Since our release of the Mutation Forecaster system in January, we have been gratified to see the level of interest by the biomedical and clinical research communities. There have been 32 registrants from 18 countries.  One subscription has been activated, and others are in progress.

Our fees are reinvested to improve and expand this resource.  For example, we are developing a completely automated workflow for genome scale coding and splicing mutation analysis, and which will automatically prepare written report summaries. Our plans for this product will meet your future needs for mutation interpretation.