A weighted distance-based approach for deriving consensus tumor evolutionary trees.

ABSTRACT:

Motivation

The acquisition of somatic mutations by a tumor can be modeled by a type of evolutionary tree. However, it is impossible to observe this tree directly. Instead, numerous algorithms have been developed to infer such a tree from different types of sequencing data. But such methods can produce conflicting trees for the same patient, making it desirable to have approaches that can combine several such tumor trees into a consensus or summary tree. We introduce The Weighted m-Tumor Tree Consensus Problem (W-m-TTCP) to find a consensus tree among multiple plausible tumor evolutionary histories, each assigned a confidence weight, given a specific distance measure between tumor trees. We present an algorithm called TuELiP that is based on integer linear programming which solves t

SUBMITTER: Guang Z 

PROVIDER: S-EPMC10311318 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature