Novel multisample scheme for inferring phylogenetic markers from whole genome tumor profiles.

ABSTRACT: Computational cancer phylogenetics seeks to enumerate the temporal sequences of aberrations in tumor evolution, thereby delineating the evolution of possible tumor progression pathways, molecular subtypes, and mechanisms of action. We previously developed a pipeline for constructing phylogenies describing evolution between major recurring cell types computationally inferred from whole-genome tumor profiles. The accuracy and detail of the phylogenies, however, depend on the identification of accurate, high-resolution molecular markers of progression, i.e., reproducible regions of aberration that robustly differentiate different subtypes and stages of progression. Here, we present a novel hidden Markov model (HMM) scheme for the problem of inferring such phylogenetically significant markers

SUBMITTER: Subramanian A 

PROVIDER: S-EPMC3830698 | biostudies-literature | 2013 Nov-Dec

REPOSITORIES: biostudies-literature