Close
Help





JOURNAL

Evolutionary Bioinformatics

Notes on the Statistical Power of the Binary State Speciation and Extinction (BiSSE) Model

Submit a Paper


A correction has been published

Evolutionary Bioinformatics 2016:12 165-174

Original Research

Published on 26 Jul 2016

DOI: 10.4137/EBO.S39732


Further metadata provided in PDF



Sign up for email alerts to receive notifications of new articles published in Evolutionary Bioinformatics

Abstract

The Binary State Speciation and Extinction (BiSSE) method is one of the most popular tools for investigating the rates of diversification and character evolution. Yet, based on previous simulation studies, it is commonly held that the BiSSE method requires phylogenetic trees of fairly large sample sizes (>300 taxa) in order to distinguish between the different models of speciation, extinction, or transition rate asymmetry. Here, the power of the BiSSE method is reevaluated by simulating trees of both small and large sample sizes (30, 60, 90, and 300 taxa) under various asymmetry models and root state assumptions. Results show that the power of the BiSSE method can be much higher, also in trees of small sample size, for detecting differences in speciation rate asymmetry than anticipated earlier. This, however, is not a consequence of any conceptual or mathematical flaw in the method per se but rather of assumptions about the character state at the root of the simulated trees and thus the underlying macroevolutionary model, which led to biased results and conclusions in earlier power assessments. As such, these earlier simulation studies used to determine the power of BiSSE were not incorrect but biased, leading to an overestimation of type-II statistical error for detecting differences in speciation rate but not for extinction and transition rates.



Downloads

PDF  (1.09 MB PDF FORMAT)

RIS citation   (ENDNOTE, REFERENCE MANAGER, PROCITE, REFWORKS)

Supplementary Files 1   (54.55 KB PDF FORMAT)

BibTex citation   (BIBDESK, LATEX)

XML





Quick Links


New article and journal news notification services