Margelevičius M. COMER2: GPU-accelerated sensitive and specific homology searches.
Bioinformatics 2020;
36:3570-3572. [PMID:
32167522 PMCID:
PMC7267824 DOI:
10.1093/bioinformatics/btaa185]
[Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Revised: 03/02/2020] [Accepted: 03/10/2020] [Indexed: 11/30/2022] Open
Abstract
Summary
Searching for homology in the vast amount of sequence data has a particular emphasis on its speed. We present a completely rewritten version of the sensitive homology search method COMER based on alignment of protein sequence profiles, which is capable of searching big databases even on a lightweight laptop. By harnessing the power of CUDA-enabled graphics processing units, it is up to 20 times faster than HHsearch, a state-of-the-art method using vectorized instructions on modern CPUs.
Availability and implementation
COMER2 is cross-platform open-source software available at https://sourceforge.net/projects/comer2 and https://github.com/minmarg/comer2. It can be easily installed from source code or using stand-alone installers.
Contact
mindaugas.margelevicius@bti.vu.lt
Supplementary information
Supplementary data are available at Bioinformatics online.
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