MCT

MCT (Multiple Consensus Trees) is a software tool to summarize a set of cancer phylogenies by simultaneously clustering them and inferring a consensus tree for each cluster. The main features and results of MCT are:

1. Motivation: Cancer phylogenies are crucial for studying tumorigenesis and have clinical implications. However, current methods identify a large solution space of plausible phylogenies due to cancer's heterogeneous nature and sequencing technology limitations. MCT aims to summarize these candidate phylogenies accurately.

2. Problem definition: The Multiple Consensus Tree (MCT) problem is introduced to cluster a set of cancer phylogenies and infer a consensus tree for each cluster simultaneously. The authors prove that MCT is NP-hard.

3. Algorithms: The authors present two algorithms to solve the MCT problem:
a. An exact algorithm based on mixed integer linear programming (MILP).
b. A heuristic algorithm that efficiently identifies high-quality consensus trees, recovering all optimal solutions identified by the MILP in simulated data at a fraction of the time.