Genome-Wide Survival Analysis of Somatic Mutations in Cancer
Motivation. Next-generation DNA sequencing technologies now enable the measurement of exomes, genomes, and mRNA expression in many samples. The next challenge is to interpret these large quantities of DNA and RNA sequence data. In many human and cancer genomics studies, a major goal is to discover associations between an observed phenotype and a particular variable from genome-wide measurements of many such variables. In this work we consider the problem of testing the association between a DNA sequence variant and the survival time, or length of time that patients live following diagnosis or treatment. This problem is relevant to many cancer sequencing studies, in which one aims to discover somatic variants that distinguish patients with fast-growing tumors that require aggressive treatment from patients with better prognosis .
KeywordsPolynomial Time Approximation Scheme Somatic Variant Fully Polynomial Time Approximation Scheme Permutational Distribution Ovarian Serous Adenocarcinoma
- 2.Mantel, N., Haenszel, W.: Statistical aspects of the analysis of data from retrospective studies of disease. Journal of the NCI 22(4), 719–748 (1959)Google Scholar
- 4.The Cancer Genome Atlas Research Network: Integrated genomic analyses of ovarian carcinoma. Nature 474(7353), 609–615 (2011)Google Scholar