Fast index based algorithms and software for matching position specific scoring matrices

111Citations
Citations of this article
116Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Background: In biological sequence analysis, position specific scoring matrices (PSSMs) are widely used to represent sequence motifs in nucleotide as well as amino acid sequences. Searching with PSSMs in complete genomes or large sequence databases is a common, but computationally expensive task. Results: We present a new non-heuristic algorithm, called ESAsearch, to efficiently find matches of PSSMs in large databases. Our approach preprocesses the search space, e.g., a complete genome or a set of protein sequences, and builds an enhanced suffix array that is stored on file. This allows the searching of a database with a PSSM in sublinear expected time. Since ESAsearch benefits from small alphabets, we present a variant operating on sequences recoded according to a reduced alphabet. We also address the problem of non-comparable PSSM-scores by developing a method which allows the efficient computation of a matrix similarity threshold for a PSSM, given an E-value or a p-value. Our method is based on dynamic programming and, in contrast to other methods, it employs lazy evaluation of the dynamic programming matrix. We evaluated algorithm ESAsearch with nucleotide PSSMs and with amino acid PSSMs. Compared to the best previous methods, ESAsearch shows speedups of a factor between 17 and 275 for nucleotide PSSMs, and speedups up to factor 1.8 for amino acid PSSMs. Comparisons with the most widely used programs even show speedups by a factor of at least 3.8. Alphabet reduction yields an additional speedup factor of 2 on amino acid sequences compared to results achieved with the 20 symbol standard alphabet. The lazy evaluation method is also much faster than previous methods, with speedups of a factor between 3 and 330. Conclusion: Our analysis of ESAsearch reveals sublinear runtime in the expected case, and linear runtime in the worst case for sequences not shorter than A m + m - 1, where m is the length of the PSSM and A a finite alphabet. In practice, ESAsearch shows superior performance over the most widely used programs, especially for DNA sequences. The new algorithm for accurate on-the-fly calculations of thresholds has the potential to replace formerly used approximation approaches. Beyond the algorithmic contributions, we provide a robust, well documented, and easy to use software package, implementing the ideas and algorithms presented in this manuscript. © 2006 Beckstette et al; licensee BioMed Central Ltd.

References Powered by Scopus

Matlnd and matlnspector: New fast and versatile tools for detection of consensus matches in nucleotide sequence data

2439Citations
N/AReaders
Get full text

TRANSFAC®: Transcriptional regulation, from patterns to profiles

1720Citations
N/AReaders
Get full text

Profile analysis: detection of distantly related proteins.

1185Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Genome sequence of the palaeopolyploid soybean

3520Citations
N/AReaders
Get full text

Draft genome sequence of pigeonpea (Cajanus cajan), an orphan legume crop of resource-poor farmers

706Citations
N/AReaders
Get full text

Patric: The comprehensive bacterial bioinformatics resource with a focus on human pathogenic species

245Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Beckstette, M., Homann, R., Giegerich, R., & Kurtz, S. (2006). Fast index based algorithms and software for matching position specific scoring matrices. BMC Bioinformatics, 7. https://doi.org/10.1186/1471-2105-7-389

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 51

57%

Researcher 27

30%

Professor / Associate Prof. 12

13%

Readers' Discipline

Tooltip

Agricultural and Biological Sciences 55

60%

Computer Science 20

22%

Biochemistry, Genetics and Molecular Bi... 14

15%

Engineering 2

2%

Article Metrics

Tooltip
Mentions
News Mentions: 1
References: 2

Save time finding and organizing research with Mendeley

Sign up for free