Comparative accuracy of methods for protein sequence similarity search

Authors: Agarwal, Pankaj; States, David J

Source: Bioinformatics, Volume 14, Number 1, February 1998 , pp. 40-47(8)

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Abstract:

Motivation: Searching a protein sequence database for homologs is a powerful tool for discovering the structure and function of a sequence. Two new methods for searching sequence databases have recently been described: Probabilistic Smith–Waterman (PSW), which is based on Hidden Markov models for a single sequence using a standard scoring matrix, and a new version of BLAST (WU-BLAST2), which uses Sum statistics for gapped alignments.

Results: This paper compares and contrasts the effectiveness of these methods with three older methods (Smith–Waterman: SSEARCH, FASTA and BLASTP). The analysis indicates that the new methods are useful, and often offer improved accuracy. These tools are compared using a curated (by Bill Pearson) version of the annotated portion of PIR 39. Three different statistical criteria are utilized: equivalence number, minimum errors and the receiver operating characteristic. For complete-length protein query sequences from large families, PSW's accuracy is superior to that of the other methods, but its accuracy is poor when used with partial-length query sequences. False negatives are twice as common as false positives irrespective of the search methods if a family-specific threshold score that minimizes the total number of errors (i.e. the most favorable threshold score possible) is used. Thus, sensitivity, not selectivity, is the major problem. Among the analyzed methods using default parameters, the best accuracy was obtained from SSEARCH and PSW for complete-length proteins, and the two BLAST programs, plus SSEARCH, for partial-length proteins.

Availability: The data and search tools are available from their original authors.

Contact: agarwal@mh.us.sbphrd.com, states@ibc.wustl.edu

Document Type: Research article

Publication date: 1998-02-01

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The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.

Comparative accuracy of methods for protein sequence similarity search

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