Employing tree bisection and reconnection rearrangement for parsimony inference in MPBoot

Abstract

The approximation technique in MPBoot effectively addresses the problem of maximum parsimony phylogenetic bootstrapping, an essential task in bioinformatics with diverse applications in evolutionary biology. In this paper, we investigate integrating the tree bisection and reconnection (TBR) rearrangement to MPBoot to increase its sampling performance in the search space, and we describe the MPBoot-TBR algorithm. Since the size of the TBR neighborhood is cubic in the number of taxa, we offer algorithmic strategies for swiftly evaluating a TBR move, searching quickly in the neighborhood of a specified remove-branch, and hill-climbing using TBR. Furthermore, the framework’s stopping condition is adjusted because compared to the subtree pruning and regrafting, TBR requires fewer search iterations to converge to an acceptable MP score. In terms of bootstrap accuracy, MPBoot-TBR is comparable to MPBoot. In terms of MP score and computation time on real datasets, MPBoot-TBR outperforms the original MPBoot. We have implemented the proposed methods in the MPBoot-TBR program, the source code of which is accessible at https: //github.com/HynDuf7/mpboot/tree/Huynh_Tien_Dung.