Improved orthology inference with Hieranoid 2
| Autor: | Mateusz Kaduk, Erik L. L. Sonnhammer |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Statistics and Probability Computer science Sequence Homology Inference Sequence alignment computer.software_genre Biochemistry Bottleneck 03 medical and health sciences Consensus sequence Code (cryptography) Molecular Biology computer.programming_language Sequence Computational Biology Inparanoid Computer Science Applications Computational Mathematics Tree (data structure) 030104 developmental biology Sequence homology Computational Theory and Mathematics Proteome Data mining Perl Sequence Alignment computer Algorithms Software |
| Zdroj: | Bioinformatics. 33:1154-1159 |
| ISSN: | 1367-4811 1367-4803 |
| DOI: | 10.1093/bioinformatics/btw774 |
| Popis: | 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. Availability and Implementation Perl code freely available at http://hieranoid.sbc.su.se/. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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