EREM: Parameter Estimation and Ancestral Reconstruction by Expectation-Maximization Algorithm for a Probabilistic Model of Genomic Binary Characters Evolution.
Evolutionary binary characters are features of species or genes, indicating the absence (value zero) or presence (value one) of some property. Examples include eukaryotic gene architecture (the presence or absence of an intron in a particular locus), gene content, and morphological characters. In many studies, the acquisition of such binary characters is assumed to represent a rare evolutionary event, and consequently, their evolution is analyzed using various flavors of parsimony. However, when gain and loss of the character are not rare enough, a probabilistic analysis becomes essential. Here, we present a comprehensive probabilistic model to describe the evolution of binary characters on a bifurcating phylogenetic tree. A fast software tool, EREM, is provided, using maximum likelihood to estimate the parameters of the model and to reconstruct ancestral states (presence and absence in internal nodes) and events (gain and loss events along branches).
Carmel
Liran
L
Department of Genetics, The Alexander Silberman Institute of Life Sciences, Faculty of Science, The Hebrew University of Jerusalem, Edmond J. Safra Campus, Givat Ram, Jerusalem 91904, Israel.
Wolf
Yuri I
YI
Rogozin
Igor B
IB
Koonin
Eugene V
EV
Mol Biol Evol. 2004 Mar;21(3):468-88
14660683
Genome Biol. 2007;8(10):R223
17949488
BMC Evol Biol. 2007 Oct 12;7:192
17935625
Proc Natl Acad Sci U S A. 1976 Nov;73(11):4164-8
1069306
Mol Biol Evol. 2007 Aug;24(8):1586-91
17483113
Genome Res. 2007 Jul;17(7):1034-44
17495008
Mol Biol Evol. 1996 Dec;13(10):1368-74
8952081
J Mol Biol. 2002 Apr 12;317(5):753-64
11955022
Science. 1971 Jun 11;172(3988):1089-96
5574514
Genome Res. 2007 Jul;17(7):1045-50
17495009