Parallelization of MAFFT for large-scale multiple sequence alignments

Tsukasa Nakamura; Kazunori D. Yamada; Kentaro Tomii; Kazutaka Katoh

doi:10.1093/bioinformatics/bty121

Parallelization of MAFFT for large-scale multiple sequence alignments

Tsukasa Nakamura, Kazunori D. Yamada, Kentaro Tomii, Kazutaka Katoh

Information Sciences

Research output: Contribution to journal › Article › peer-review

416 Citations (Scopus)

Abstract

Summary: We report an update for the MAFFT multiple sequence alignment program to enable parallel calculation of large numbers of sequences. The G-INS-1 option of MAFFT was recently reported to have higher accuracy than other methods for large data, but this method has been impractical for most large-scale analyses, due to the requirement of large computational resources. We introduce a scalable variant, G-large-INS-1, which has equivalent accuracy to G-INS-1 and is applicable to 50 000 or more sequences.

Original language	English
Pages (from-to)	2490-2492
Number of pages	3
Journal	Bioinformatics
Volume	34
Issue number	14
DOIs	https://doi.org/10.1093/bioinformatics/bty121
Publication status	Published - 2018 Jul 15

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/bty121

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title = "Parallelization of MAFFT for large-scale multiple sequence alignments",

abstract = "Summary: We report an update for the MAFFT multiple sequence alignment program to enable parallel calculation of large numbers of sequences. The G-INS-1 option of MAFFT was recently reported to have higher accuracy than other methods for large data, but this method has been impractical for most large-scale analyses, due to the requirement of large computational resources. We introduce a scalable variant, G-large-INS-1, which has equivalent accuracy to G-INS-1 and is applicable to 50 000 or more sequences.",

author = "Tsukasa Nakamura and Yamada, {Kazunori D.} and Kentaro Tomii and Kazutaka Katoh",

note = "Funding Information: This work was supported by JSPS KAKENHI [grant numbers JP16K07464 (to K.D.Y., K.T. and K.K.) and JP17J06457 (to T.N.)] and Platform Project for Supporting Drug Discovery and Life Science Research [grant numbers JP17am0101110 (to T.N., K.D.Y. and K.T.) and JP17am0101108 (to K.K.)] from AMED, Japan. Publisher Copyright: {\textcopyright} The Author(s) 2018. Published by Oxford University Press.",

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T1 - Parallelization of MAFFT for large-scale multiple sequence alignments

AU - Nakamura, Tsukasa

AU - Yamada, Kazunori D.

AU - Tomii, Kentaro

AU - Katoh, Kazutaka

N1 - Funding Information: This work was supported by JSPS KAKENHI [grant numbers JP16K07464 (to K.D.Y., K.T. and K.K.) and JP17J06457 (to T.N.)] and Platform Project for Supporting Drug Discovery and Life Science Research [grant numbers JP17am0101110 (to T.N., K.D.Y. and K.T.) and JP17am0101108 (to K.K.)] from AMED, Japan. Publisher Copyright: © The Author(s) 2018. Published by Oxford University Press.

PY - 2018/7/15

Y1 - 2018/7/15

N2 - Summary: We report an update for the MAFFT multiple sequence alignment program to enable parallel calculation of large numbers of sequences. The G-INS-1 option of MAFFT was recently reported to have higher accuracy than other methods for large data, but this method has been impractical for most large-scale analyses, due to the requirement of large computational resources. We introduce a scalable variant, G-large-INS-1, which has equivalent accuracy to G-INS-1 and is applicable to 50 000 or more sequences.

AB - Summary: We report an update for the MAFFT multiple sequence alignment program to enable parallel calculation of large numbers of sequences. The G-INS-1 option of MAFFT was recently reported to have higher accuracy than other methods for large data, but this method has been impractical for most large-scale analyses, due to the requirement of large computational resources. We introduce a scalable variant, G-large-INS-1, which has equivalent accuracy to G-INS-1 and is applicable to 50 000 or more sequences.

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Parallelization of MAFFT for large-scale multiple sequence alignments

Abstract

ASJC Scopus subject areas

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