Binary contingency table method for analysing gene mutation in cancer genome Online publication date: Tue, 09-Aug-2016
by Emi Ayada; Takanori Hasegawa; Atsushi Niida; Satoru Miyano; Seiya Imoto
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 12, No. 3, 2016
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.
Online publication date: Tue, 09-Aug-2016
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