Abstract:
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We present a new algorithm, PHOG phylogenomic orthology prediction, which is
available as a web service through the PhyloFacts Phylogenomic Encyclopedias.
Ortholog detection is essential in functional annotation of genomes, with
applications to phylogenetic tree construction, prediction of
protein-protein interaction and other tasks. PHOG employs a novel algorithm
to identify orthologs using phylogenetic analysis. Results on a benchmark
dataset from the TreeFam-A manually curated orthology database show that
PHOG provides a combination of high recall and precision competitive with
both InParanoid and OrthoMCL, and allows users to target different taxonomic
distances and precision levels through the use of tree-distance thresholds.
For instance, OrthoMCL-DB achieved 76% recall and 66% precision on this
dataset; at a slightly higher precision (68%) PHOG achieves 10% higher
recall (86%). InParanoid achieved 87% recall at 24% precision on this
dataset, while a PHOG variant designed for high recall achieves 88% recall
at 61% precision, increasing precision by 37% over InParanoid. Predicted
orthologs are linked to GO annotations, pathway information and biological
literature.
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