FastBLAST: Homology Relationships for Millions of Proteins

Price, Morgan N.; Dehal, Paramvir S.; Arkin, Adam P.

doi:10.1371/journal.pone.0003589

FastBLAST: Homology Relationships for Millions of Proteins

Journal Article · Fri Oct 31 00:00:00 EDT 2008 · PLoS ONE

DOI:https://doi.org/10.1371/journal.pone.0003589· OSTI ID:1627360

Price, Morgan N. ^[1]; Dehal, Paramvir S. ^[2]; Arkin, Adam P. ^[3]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Physical Biosciences Division; Virtual Inst. for Microbial Stress and Survival, Berkeley, CA (United States); DOE/OSTI
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Physical Biosciences Division; Virtual Inst. for Microbial Stress and Survival, Berkeley, CA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Physical Biosciences Division; Virtual Inst. for Microbial Stress and Survival, Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States). Dept. of Bioengineering

Background: All-versus-all BLAST, which searches for homologous pairs of sequences in a database of proteins, is used to identify potential orthologs, to find new protein families, and to provide rapid access to these homology relationships. As DNA sequencing accelerates and data sets grow, all-versus-all BLAST has become computationally demanding. Methodology/Principal Findings: We present FastBLAST, a heuristic replacement for all-versus-all BLAST that relies on alignments of proteins to known families, obtained from tools such as PSI-BLAST and HMMer. FastBLAST avoids most of the work of all-versus-all BLAST by taking advantage of these alignments and by clustering similar sequences. FastBLAST runs in two stages: the first stage identifies additional families and aligns them, and the second stage quickly identifies the homologs of a query sequence, based on the alignments of the families, before generating pairwise alignments. On 6.53 million proteins from the non-redundant Genbank database (‘‘NR’’), FastBLAST identifies new families 25 times faster than all-versus-all BLAST. Once the first stage is completed, FastBLAST identifies homologs for the average query in less than 5 seconds (8.6 times faster than BLAST) and gives nearly identical results. For hits above 70 bits, FastBLAST identifies 98% of the top 3,250 hits per query. Conclusions/Significance: FastBLAST enables research groups that do not have supercomputers to analyze large protein sequence data sets. FastBLAST is open source software and is available at http://microbesonline.org/fastblast.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1627360

Journal Information:: PLoS ONE, Journal Name: PLoS ONE Journal Issue: 10 Vol. 3; ISSN 1932-6203

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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