Document Detail

Efficient biased estimation of evolutionary distances when substitution rates vary across sites.
MedLine Citation:
PMID:  11919295     Owner:  NLM     Status:  MEDLINE    
This paper deals with phylogenetic inference when the variability of substitution rates across sites (VRAS) is modeled by a gamma distribution. We show that underestimating VRAS, which results in underestimates for the evolutionary distances between sequences, usually improves the topological accuracy of phylogenetic tree inference by distance-based methods, especially when the molecular clock holds. We propose a method to estimate the gamma shape parameter value which is most suited for tree topology inference, given the sequences at hand. This method is based on the pairwise evolutionary distances between sequences and allows one to reconstruct the phylogeny of a high number of taxa (>1,000). Simulation results show that the topological accuracy is highly improved when using the gamma shape parameter value given by our method, compared with the true (unknown) value which was used to generate the data. Furthermore, when VRAS is high, the topological accuracy of our distance-based method is better than that of a maximum likelihood approach. Finally, a data set of Maoricicada species sequences is analyzed, which confirms the advantage of our method.
Stéphane Guindon; Olivier Gascuel
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Publication Detail:
Type:  Comparative Study; Journal Article    
Journal Detail:
Title:  Molecular biology and evolution     Volume:  19     ISSN:  0737-4038     ISO Abbreviation:  Mol. Biol. Evol.     Publication Date:  2002 Apr 
Date Detail:
Created Date:  2002-03-28     Completed Date:  2002-08-02     Revised Date:  2008-11-21    
Medline Journal Info:
Nlm Unique ID:  8501455     Medline TA:  Mol Biol Evol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  534-43     Citation Subset:  IM    
LIRMM, UMR 9928 Université Montpellier II/CNRS, 161 Rue Ada, 34392 Montpellier Cedex 5, France.
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MeSH Terms
Amino Acid Substitution / genetics*
Computer Simulation
Evolution, Molecular*
Genetic Variation / genetics*
Hemiptera / genetics*
Insect Proteins / genetics
Models, Genetic
Mutagenesis / genetics*
Reg. No./Substance:
0/Insect Proteins

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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