Binary contingency table method for analyzing gene mutation in cancer genome

Emi Ayada, Atsushi Niida, Takanori Hasegawa, Satoru Miyano, Seiya Imoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Gene mutations are responsible for a large proportion of genetic diseases such as cancer. 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.

Original languageEnglish
Title of host publicationBioinformatics Research and Applications - 11th International Symposium, ISBRA 2015, Proceedings
EditorsIon Măndoiu, Yaohang Li, Robert Harrison
PublisherSpringer-Verlag
Pages12-13
Number of pages2
ISBN (Print)9783319190471
DOIs
Publication statusPublished - 2015 Jan 1
Event11th International Symposium on Bioinformatics Research and Applications, ISBRA 2015 - Norfolk, United States
Duration: 2015 Jun 72015 Jun 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9096
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th International Symposium on Bioinformatics Research and Applications, ISBRA 2015
CountryUnited States
CityNorfolk
Period15/6/715/6/10

Keywords

  • Binary contingency tables
  • Cancer
  • Gene mutation
  • Markov chain Monte Carlo

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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