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Virmid: accurate detection of somatic mutations with sample impurity inference.

ABSTRACT: Detection of somatic variation using sequence from disease-control matched data sets is a critical first step. In many cases including cancer, however, it is hard to isolate pure disease tissue, and the impurity hinders accurate mutation analysis by disrupting overall allele frequencies. Here, we propose a new method, Virmid, that explicitly determines the level of impurity in the sample, and uses it for improved detection of somatic variation. Extensive tests on simulated and real sequencing data from breast cancer and hemimegalencephaly demonstrate the power of our model. A software implementation of our method is available at http://sourceforge.net/projects/virmid/.

SUBMITTER: Kim S

PROVIDER: S-EPMC4054681 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Virmid: accurate detection of somatic mutations with sample impurity inference.

Kim Sangwoo S Jeong Kyowon K Bhutani Kunal K Lee Jeong J Patel Anand A Scott Eric E Nam Hojung H Lee Hayan H Gleeson Joseph G JG Bafna Vineet V

Genome biology 20130829 8

Detection of somatic variation using sequence from disease-control matched data sets is a critical first step. In many cases including cancer, however, it is hard to isolate pure disease tissue, and the impurity hinders accurate mutation analysis by disrupting overall allele frequencies. Here, we propose a new method, Virmid, that explicitly determines the level of impurity in the sample, and uses it for improved detection of somatic variation. Extensive tests on simulated and real sequencing da ...[more]

PMID: 23987214

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