Phylogenetic inference: linear invariants and maximum likelihood.

W C Navidi, G A Churchill, A von Haeseler
Author Information
  1. W C Navidi: Department of Mathematics, University of Southern California, Los Angeles 90089-1113.

Abstract

We develop a new statistical method for inferring phylogenies, based on a likelihood ratio test. This method does not require parameter constraints but does require identical evolutionary processes in the sites considered. Another method of phylogenetic inference is the method of linear invariants, described by Cavender (1989, Molecular Biology and Evolution 6, 301-316), based on a notion of Lake (1987, Molecular Biology and Evolution 4, 167-191). We describe a sound mathematical basis for the use of linear invariants. We show that the validity of the method requires parameter constraints, but does not require that the evolutionary processes in differing sites be identical. We show that the method of linear invariants is asymptotically equivalent to a less powerful version of our likelihood ratio test, and is thus essentially a maximum likelihood technique.

MeSH Term

Animals
Base Sequence
Chlamydomonas reinhardtii
DNA
Escherichia coli
Hominidae
Humans
Mathematics
Models, Biological
Models, Statistical
Phylogeny
Probability
RNA
Species Specificity
Sulfolobus

Chemicals

RNA
DNA

Word Cloud

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