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Improved orthology inference with Hieranoid 2
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
Number of Authors: 2
2017 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 33, no 8, p. 1154-1159Article in journal (Refereed) Published
Abstract [en]

Motivation: The initial step in many orthology inference methods is the computationally demanding establishment of all pairwise protein similarities across all analysed proteomes. The quadratic scaling with proteomes has become a major bottleneck. A remedy is offered by the Hieranoid algorithm which reduces the complexity to linear by hierarchically aggregating ortholog groups from InParanoid along a species tree. Results: We have further developed the Hieranoid algorithm in many ways. Major improvements have been made to the construction of multiple sequence alignments and consensus sequences. Hieranoid version 2 was evaluated with standard benchmarks that reveal a dramatic increase in the coverage/accuracy tradeoff over version 1, such that it now compares favourably with the best methods. The new parallelized cluster mode allows Hieranoid to be run on large data sets in a much shorter timespan than InParanoid, yet at similar accuracy.

Place, publisher, year, edition, pages
2017. Vol. 33, no 8, p. 1154-1159
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:su:diva-144722DOI: 10.1093/bioinformatics/btw774ISI: 000400985900007PubMedID: 28096085OAI: oai:DiVA.org:su-144722DiVA, id: diva2:1127955
Available from: 2017-07-20 Created: 2017-07-20 Last updated: 2018-04-24Bibliographically approved
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Kaduk, MateuszSonnhammer, Erik
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