Distance measures for tumor evolutionary trees.

ABSTRACT:

Motivation

There has been recent increased interest in using algorithmic methods to infer the evolutionary tree underlying the developmental history of a tumor. Quantitative measures that compare such trees are vital to a number of different applications including benchmarking tree inference methods and evaluating common inheritance patterns across patients. However, few appropriate distance measures exist, and those that do have low resolution for differentiating trees or do not fully account for the complex relationship between tree topology and the inheritance of the mutations labeling that topology.

Results

Here, we present two novel distance measures, Common Ancestor Set distance (CASet) and Distinctly Inherited Set Comparison distance (DISC), that are specifically desi

SUBMITTER: DiNardo Z 

PROVIDER: S-EPMC7141873 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature