Evaluating intraspecific "network" construction methods using simulated sequence data: Do existing algorithms outperform the global maximum parsimony approach?

132Citations
Citations of this article
320Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In intraspecific studies, reticulated graphs are valuable tools for visualization, within a single figure, of alternative genealogical pathways among haplotypes. As available software packages implementing the global maximum parsimony (MP) approach only give the possibility to merge resulting topologies into less-resolved consensus trees, MP has often been neglected as an alternative approach to purely algorithmic (i.e., methods defined solely on the basis of an algorithm) "network" construction methods. Here, we propose to search tree space using the MP criterion and present a new algorithm for uniting all equally most parsimonious trees into a single (possibly reticulated) graph. Using simulated sequence data, we compare our method with three purely algorithmic and widely used graph construction approaches (minimum-spanning network, statistical parsimony, and median-joining network). We demonstrate that the combination of MP trees into a single graph provides a good estimate of the true genealogy. Moreover, our analyses indicate that, when internal node haplotypes are not sampled, the median-joining and MP methods provide the best estimate of the true genealogy whereas the minimum-spanning algorithm shows very poor performances. Copyright © Society of Systematic Biologists.

Cite

CITATION STYLE

APA

Cassens, I., Mardulyn, P., & Milinkovitch, M. C. (2005). Evaluating intraspecific “network” construction methods using simulated sequence data: Do existing algorithms outperform the global maximum parsimony approach? Systematic Biology, 54(3), 363–372. https://doi.org/10.1080/10635150590945377

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free