Linked Life Data

18767964

Source:http://linkedlifedata.com/resource/pubmed/id/18767964

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2008-9-4
pubmed:abstractText
The availability of genome-wide data provides unprecedented opportunities for resolving difficult phylogenetic relationships and for studying population genetic processes of mutation, selection, and recombination on a genomic scale. The use of appropriate statistical models becomes increasingly important when we are faced with very large datasets, which can lead to improved precision but not necessarily improved accuracy if the analytical methods have systematic biases. This review provides a critical examination of methods for analyzing genomic datasets from multiple loci, including concatenation, separate gene-by-gene analyses, and statistical models that accommodate heterogeneity in different aspects of the evolutionary process among data partitions. We discuss factors that may cause the gene tree to differ from the species tree, as well as strategies for estimating species phylogenies in the presence of gene tree conflicts. Genomic datasets provide computational and statistical challenges that are likely to be a focus of research for years to come.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1527-8204
pubmed:author
pubmed:issnType
Print
pubmed:volume
9
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
217-31
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Phylogenetic inference using whole genomes.
pubmed:affiliation
Genome Center and Department of Evolution and Ecology, University of California, Davis, California 95616, USA. bhrannala@ucdavis.edu
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't