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FastBLAST: homology relationships for millions of proteins.

Price MN, Dehal PS, Arkin AP - PLoS ONE (2008)

Bottom Line: 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.FastBLAST enables research groups that do not have supercomputers to analyze large protein sequence data sets.

View Article: PubMed Central - PubMed

Affiliation: Physical Biosciences Divison, Lawrence Berkeley National Laboratory, Berkeley, California, USA. morgannprice@yahoo.com

ABSTRACT

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.

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Overview of FastBLAST.
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pone-0003589-g001: Overview of FastBLAST.

Mentions: FastBLAST runs in two stages (Figure 1). First, it identifies “ad hoc” families that capture homology relationships that are missed by the known families. These ad hoc families are based on “seeds,” or unassigned regions that do not belong to any known family. The members of an ad hoc family are the homologs (from BLAST) of the seed. FastBLAST uses fast sequence clustering to identify these ad hoc families and their members quickly and to reduce the number of seeds. In the first stage, FastBLAST also creates multiple sequence alignments for the ad hoc families.


FastBLAST: homology relationships for millions of proteins.

Price MN, Dehal PS, Arkin AP - PLoS ONE (2008)

Overview of FastBLAST.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2571987&req=5

pone-0003589-g001: Overview of FastBLAST.
Mentions: FastBLAST runs in two stages (Figure 1). First, it identifies “ad hoc” families that capture homology relationships that are missed by the known families. These ad hoc families are based on “seeds,” or unassigned regions that do not belong to any known family. The members of an ad hoc family are the homologs (from BLAST) of the seed. FastBLAST uses fast sequence clustering to identify these ad hoc families and their members quickly and to reduce the number of seeds. In the first stage, FastBLAST also creates multiple sequence alignments for the ad hoc families.

Bottom Line: 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.FastBLAST enables research groups that do not have supercomputers to analyze large protein sequence data sets.

View Article: PubMed Central - PubMed

Affiliation: Physical Biosciences Divison, Lawrence Berkeley National Laboratory, Berkeley, California, USA. morgannprice@yahoo.com

ABSTRACT

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.

Show MeSH