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InParanoid-DIAMOND: faster orthology analysis with the InParanoid algorithm.
Persson, Emma; Sonnhammer, Erik L L.
Affiliation
  • Persson E; Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, 17121 Solna, Sweden.
  • Sonnhammer ELL; Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, 17121 Solna, Sweden.
Bioinformatics ; 38(10): 2918-2919, 2022 05 13.
Article in En | MEDLINE | ID: mdl-35561192
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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Software Type of study: Prognostic_studies Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2022 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Software Type of study: Prognostic_studies Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2022 Document type: Article Affiliation country: