MixClone: a mixture model for inferring tumor subclonal populations.

ABSTRACT:

Background

Tumor genomes are often highly heterogeneous, consisting of genomes from multiple subclonal types. Complete characterization of all subclonal types is a fundamental need in tumor genome analysis. With the advancement of next-generation sequencing, computational methods have recently been developed to infer tumor subclonal populations directly from cancer genome sequencing data. Most of these methods are based on sequence information from somatic point mutations, However, the accuracy of these algorithms depends crucially on the quality of the somatic mutations returned by variant calling algorithms, and usually requires a deep coverage to achieve a reasonable level of accuracy.

Results

We describe a novel probabilistic mixture model, MixClone, for inferring the ce

SUBMITTER: Li Y 

PROVIDER: S-EPMC4331709 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature