Automatic clustering of orthologs and inparalogs shared by multiple proteomes.
BACKGROUND
The complete sequencing of many genomes has made it possible to identify orthologous genes descending from a common ancestor. However, reconstruction of evolutionary history over long time periods faces many challenges due to gene duplications and losses. Identification of orthologous groups shared by multiple proteomes therefore becomes a clustering problem in which an optimal compromise between conflicting evidences needs to be found.


RESULTS
Here we present a new proteome-scale analysis program called MultiParanoid that can automatically find orthology relationships between proteins in multiple proteomes. The software is an extension of the InParanoid program that identifies orthologs and inparalogs in pairwise proteome comparisons. MultiParanoid applies a clustering algorithm to merge multiple pairwise ortholog groups from InParanoid into multi-species ortholog groups. To avoid outparalogs in the same cluster, MultiParanoid only combines species that share the same last ancestor. To validate the clustering technique, we compared the results to a reference set obtained by manual phylogenetic analysis. We further compared the results to ortholog groups in KOGs and OrthoMCL, which revealed that MultiParanoid produces substantially fewer outparalogs than these resources.


BACKGROUND
MultiParanoid is a freely available standalone program that enables efficient orthology analysis much needed in the post-genomic era. A web-based service providing access to the original datasets, the resulting groups of orthologs, and the source code of the program can be found at http://multiparanoid.cgb.ki.se.
Alexeyenko
Andrey
A
Center for Genomics and Bioinformatics, Karolinska Institutet, S-17177 Stockholm, Sweden.
Tamas
Ivica
I
Liu
Gang
G
Sonnhammer
Erik L L
EL
D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D016000:Cluster Analysis; D017124:Conserved Sequence / Q000235:genetics; D019143:Evolution, Molecular; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods; D010802:Phylogeny; D020543:Proteome / Q000235:genetics*; D016415:Sequence Alignment / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D017386:Sequence Homology, Amino Acid
D020543:Proteome