Linked Life Data

20525603

Source:http://linkedlifedata.com/resource/pubmed/id/20525603

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2010-6-7
pubmed:abstractText
Several methods have recently been developed to infer multilocus phylogenies by incorporating information from topological incongruence of the individual genes. In this study, we investigate 2 such methods, Bayesian concordance analysis and Bayesian estimation of species trees. Our test data are a collection of genes from cultivated rice (genus Oryza) and the most closely related wild species, generated using a high-throughput sequencing protocol and bioinformatics pipeline. Trees inferred from independent genes display levels of topological incongruence that far exceed that seen in previous data sets analyzed with these species tree methods. We identify differences in phylogenetic results between inference methods that incorporate gene tree incongruence. Finally, we discuss the challenges of scaling these analyses for data sets with thousands of gene trees and extensive levels of missing data.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1076-836X
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
58
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
489-500
pubmed:dateRevised
2011-8-5
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Species trees from highly incongruent gene trees in rice.
pubmed:affiliation
Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721, USA. kcranston@fieldmuseum.org
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't