Association Analysis Using Somatic Mutations

• Activity Number: 75 - Statistical Genomics in Cancer
• Type: Contributed
• Date/Time: Sunday, July 30, 2017 : 4:00 PM to 5:50 PM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Yang Liu* and Wei Sun and Qianchuan He
• Companies: Fred Hutchinson Cancer Research Center and Fred Hutchinson Cancer Research Center and Fred Hutch Cancer Research Center
• Keywords: Somatic mutations ; EM algorithm

Abstract

Many statistical methods have been developed for association analysis using germline genetic variants as covariates, for example, group test for rare variants or PCA analysis to reveal population stratification. The same set of methods are not suitable for somatic mutation associations because of lower sensitivity and specificity to call somatic mutations. In this paper, we present an EM-based method to estimate the association parameters in the presence of missing genotypes of somatic mutations. We further develop a likelihood ratio test to detect the associations. Simulation studies prove that the methods are powerful to reveal the associations for somatic mutations. We then apply the method to analyze some data sets available through The Cancer Genome Atlas (TCGA) and identify several mutations with impacts on gene expressions in colon cancer.