COMER2: GPU-accelerated sensitive and specific homology searches

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 l...

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Detalles Bibliográficos
Autor principal: Margelevičius, Mindaugas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267824/
https://www.ncbi.nlm.nih.gov/pubmed/32167522
http://dx.doi.org/10.1093/bioinformatics/btaa185
Descripción
Sumario: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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