Hieranoid: Hierarchical Orthology Inference

作者：Schreiber Fabian^*; Sonnhammer Erik L L

来源：Journal of Molecular Biology, 2013, 425(11): 2072-2081.

DOI：10.1016/j.jmb.2013.02.018

• Orthology inference
• inParanoid
• guide tree
• profile-profile comparison

An accurate inference of orthologs is essential in many research fields such as comparative genomics, molecular evolution, and genome annotation. Existing methods for genome-scale orthology inference are mostly based on all-versus-all similarity searches that scale quadratically with the number of species. This limits their application to the increasing number of available large-scale datasets. %26lt;br%26gt;Here, we present Hieranoid, a new orthology inference method using a hierarchical approach. Hieranoid performs pairwise orthology analysis using In Paranoid at each node in a guide tree as it progresses from its leaves to the root. This concept reduces the total runtime complexity from a quadratic to a linear function of the number of species. The tree hierarchy provides a natural structure in multi-species ortholog groups, and the aggregation of multiple sequences allows for multiple alignment similarity searching techniques, which can yield more accurate ortholog groups. %26lt;br%26gt;Using the recently published orthobench benchmark, Hieranoid showed the overall best performance. Our progressive approach presents a new way to infer orthologs that combines efficient graph-based methodology with aspects of compute-intensive tree-based methods. The linear scaling with the number of species is a major advantage for large-scale applications and makes Hieranoid well suited to cope with vast amounts of sequenced genomes in the future. %26lt;br%26gt;Hieranoid is an open source and can be downloaded at Hieranoid.sbc.su.se.

• 出版日期2013-6-12