Title: Binary contingency table method for analysing gene mutation in cancer genome

Authors: Emi Ayada; Takanori Hasegawa; Atsushi Niida; Satoru Miyano; Seiya Imoto

Addresses: Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan ' Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan ' Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan ' Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan ' Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, Japan

Abstract: Somatic mutations are considered to initiate several disorders such as cancer and neurological disease. Hence, a number of computational methods have been developed to find loci subject to frequent mutations in cancer cells. Since normal cells turn into cancer cells through the accumulation of gene mutations, the elucidation of interactive relationships among loci has great potential to reveal the cause of cancer progression; however, only a few methods have been proposed for measuring statistical significance of pairs of loci that are co-mutated or exclusively mutated. In this study, we proposed a novel statistical method to find such significantly interactive pairs of loci by employing the framework of binary contingency tables. Using Markov chain Monte Carlo procedure, the statistical significance is evaluated by sampling null matrices whose marginal sums are equal to those of the input matrix. We applied the proposed method to mutation data of colon cancer patients and successfully obtained significant pairs of loci.

Keywords: cancer genome; gene mutation; binary contingency tables; Markov chain Monte Carlo; MCMC; bioinformatics; somatic mutations; cancer cells; colon cancer.

DOI: 10.1504/IJBRA.2016.078231

International Journal of Bioinformatics Research and Applications, 2016 Vol.12 No.3, pp.211 - 226

Received: 18 Sep 2015
Accepted: 22 Jan 2016
Published online: 09 Aug 2016 *

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