InParanoid-DIAMOND: faster orthology analysis with the InParanoid algorithm
Emma Persson, Erik L. L. Sonnhammer
Abstract
SUMMARY: Predicting orthologs, genes in different species having shared ancestry, is an important task in bioinformatics. Orthology prediction tools are required to make accurate and fast predictions, in order to analyze large amounts of data within a feasible time frame. InParanoid is a well-known algorithm for orthology analysis, shown to perform well in benchmarks, but having the major limitation of long runtimes on large datasets. Here, we present an update to the InParanoid algorithm that can use the faster tool DIAMOND instead of BLAST for the homolog search step. We show that it reduces the runtime by 94%, while still obtaining similar performance in the Quest for Orthologs benchmark. AVAILABILITY AND IMPLEMENTATION: The source code is available at (https://bitbucket.org/sonnhammergroup/inparanoid). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.