Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2008 Aug 15;24(16):1757-64.
doi: 10.1093/bioinformatics/btn322. Epub 2008 Jun 21.

Database indexing for production MegaBLAST searches

Affiliations

Database indexing for production MegaBLAST searches

Aleksandr Morgulis et al. Bioinformatics. .

Erratum in

  • Bioinformatics. 2008 Dec 15;24(24):2942

Abstract

Motivation: The BLAST software package for sequence comparison speeds up homology search by preprocessing a query sequence into a lookup table. Numerous research studies have suggested that preprocessing the database instead would give better performance. However, production usage of sequence comparison methods that preprocess the database has been limited to programs such as BLAT and SSAHA that are designed to find matches when query and database subsequences are highly similar.

Results: We developed a new version of the MegaBLAST module of BLAST that does the initial phase of finding short seeds for matches by searching a database index. We also developed a program makembindex that preprocesses the database into a data structure for rapid seed searching. We show that the new 'indexed MegaBLAST' is faster than the 'non-indexed' version for most practical uses. We show that indexed MegaBLAST is faster than miBLAST, another implementation of BLAST nucleotide searching with a preprocessed database, for most of the 200 queries we tested. To deploy indexed MegaBLAST as part of NCBI'sWeb BLAST service, the storage of databases and the queueing mechanism were modified, so that some machines are now dedicated to serving queries for a specific database. The response time for such Web queries is now faster than it was when each computer handled queries for multiple databases.

Availability: The code for indexed MegaBLAST is part of the blastn program in the NCBI C++ toolkit. The preprocessor program makembindex is also in the toolkit. Indexed MegaBLAST has been used in production on NCBI's Web BLAST service to search one version of the human and mouse genomes since October 2007. The Linux command-line executables for blastn and makembindex, documentation, and some query sets used to carry out the tests described below are available in the directory: ftp://ftp.ncbi.nlm.nih.gov/pub/agarwala/indexed_megablast [corrected]

Supplementary information: Supplementary data are available at Bioinformatics online.

PubMed Disclaimer

Figures

Fig. 1.
Fig. 1.
Schematic of the data structure used for the database index.
Fig. 2.
Fig. 2.
Wall-clock times for 100 indexed and non-indexed searches in a production setting, as a function of logarithm of query length. Considering times to be tied if they are within 0.01 s, indexed search is faster 75 times, non-indexed search is faster 19 times, and they tie on 6 queries. Indexed search is faster on shorter queries and slower on the longest queries.

Similar articles

Cited by

References

    1. Altschul SF, et al. Gapped BLAST and PSI-BLAST – a new generation of protein database search programs. Nucleic Acids Res. 1997;25:3389–3402. - PMC - PubMed
    1. Cao X, et al. Piers: an efficient model for similarity search in DNA sequence databases. ACM SIGMOD Record (Special Issue on Data Engineering for Life Sciences. 2004;33:39–44.
    1. Gertz EM, et al. Composition-based statistics and translated nucleotide searches: improving the TBLASTN module of BLAST. BMC Biol. 2006;4:41. - PMC - PubMed
    1. Giladi E, et al. SST: an algorithm for finding near-exact sequence matches in time proportional to the logarithm of the database size. Bioinformatics. 2002;18:873–879. - PubMed
    1. Jiang X, et al. Survey on index based homology search algorithms. J. Supercomput. 2007;40:185–212.

Publication types