@inproceedings{de56fabb44294c9bbd15af8b6c37753a,
title = "Binary contingency table method for analyzing gene mutation in cancer genome",
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.",
keywords = "Binary contingency tables, Cancer, Gene mutation, Markov chain Monte Carlo",
author = "Emi Ayada and Atsushi Niida and Takanori Hasegawa and Satoru Miyano and Seiya Imoto",
year = "2015",
month = jan,
day = "1",
doi = "10.1007/978-3-319-19048-8_2",
language = "English",
isbn = "9783319190471",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "12--13",
editor = "Ion M{\u a}ndoiu and Yaohang Li and Robert Harrison",
booktitle = "Bioinformatics Research and Applications - 11th International Symposium, ISBRA 2015, Proceedings",
note = "11th International Symposium on Bioinformatics Research and Applications, ISBRA 2015 ; Conference date: 07-06-2015 Through 10-06-2015",
}
