CoMSA: compression of protein multiple sequence alignment files.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
15 01 2019
Historique:
received: 28 12 2017
accepted: 10 07 2018
pubmed: 17 7 2018
medline: 24 10 2019
entrez: 17 7 2018
Statut: ppublish

Résumé

Bioinformatics databases grow rapidly and achieve values hardly to imagine a decade ago. Among numerous bioinformatics processes generating hundreds of GB is multiple sequence alignments of protein families. Its largest database, i.e. Pfam, consumes 40-230 GB, depending of the variant. Storage and transfer of such massive data has become a challenge. We propose a novel compression algorithm, CoMSA, designed especially for aligned data. It is based on a generalization of the positional Burrows-Wheeler transform for non-binary alphabets. CoMSA handles FASTA, as well as Stockholm files. It offers up to six times better compression ratio than other commonly used compressors, i.e. gzip. Performed experiments resulted in an analysis of the influence of a protein family size on the compression ratio. CoMSA is available for free at https://github.com/refresh-bio/comsa and http://sun.aei.polsl.pl/REFRESH/comsa. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 30010777
pii: 5053318
doi: 10.1093/bioinformatics/bty619
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

227-234

Auteurs

Sebastian Deorowicz (S)

Institute of Informatics, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwice, Poland.

Joanna Walczyszyn (J)

Institute of Informatics, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwice, Poland.

Agnieszka Debudaj-Grabysz (A)

Institute of Informatics, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwice, Poland.

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Classifications MeSH