Algorithm of OMA for large-scale orthology inference.

Details

Serval ID
serval:BIB_2FB29FA83B67
Type
Article: article from journal or magazin.
Collection
Publications
Title
Algorithm of OMA for large-scale orthology inference.
Journal
BMC bioinformatics
Author(s)
Roth A.C., Gonnet G.H., Dessimoz C.
ISSN
1471-2105 (Electronic)
ISSN-L
1471-2105
Publication state
Published
Issued date
04/12/2008
Peer-reviewed
Oui
Volume
9
Pages
518
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
OMA is a project that aims to identify orthologs within publicly available, complete genomes. With 657 genomes analyzed to date, OMA is one of the largest projects of its kind.
The algorithm of OMA improves upon standard bidirectional best-hit approach in several respects: it uses evolutionary distances instead of scores, considers distance inference uncertainty, includes many-to-many orthologous relations, and accounts for differential gene losses. Herein, we describe in detail the algorithm for inference of orthology and provide the rationale for parameter selection through multiple tests.
OMA contains several novel improvement ideas for orthology inference and provides a unique dataset of large-scale orthology assignments.
Keywords
Algorithms, Computational Biology/methods, Evolution, Molecular, Genomics, Sequence Alignment
Pubmed
Web of science
Open Access
Yes
Create date
02/09/2015 8:16
Last modification date
06/03/2024 9:24
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