A comparison of profile hidden Markov model procedures for remote homology detection - PubMed (original) (raw)

Comparative Study

. 2002 Oct 1;30(19):4321-8.

doi: 10.1093/nar/gkf544.

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Comparative Study

A comparison of profile hidden Markov model procedures for remote homology detection

Martin Madera et al. Nucleic Acids Res. 2002.

Abstract

Profile hidden Markov models (HMMs) are amongst the most successful procedures for detecting remote homology between proteins. There are two popular profile HMM programs, HMMER and SAM. Little is known about their performance relative to each other and to the recently improved version of PSI-BLAST. Here we compare the two programs to each other and to non-HMM methods, to determine their relative performance and the features that are important for their success. The quality of the multiple sequence alignments used to build models was the most important factor affecting the overall performance of profile HMMs. The SAM T99 procedure is needed to produce high quality alignments automatically, and the lack of an equivalent component in HMMER makes it less complete as a package. Using the default options and parameters as would be expected of an inexpert user, it was found that from identical alignments SAM consistently produces better models than HMMER and that the relative performance of the model-scoring components varies. On average, HMMER was found to be between one and three times faster than SAM when searching databases larger than 2000 sequences, SAM being faster on smaller ones. Both methods were shown to have effective low complexity and repeat sequence masking using their null models, and the accuracy of their E-values was comparable. It was found that the SAM T99 iterative database search procedure performs better than the most recent version of PSI-BLAST, but that scoring of PSI-BLAST profiles is more than 30 times faster than scoring of SAM models.

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Figures

Figure 1

Figure 1

Sensitivity plots for the SCOP all-against-all (test 2). The input alignments were: (A) the results of a WU-BLAST search of nrdb90 aligned with ClustalW; (B) T99 alignments realigned with ClustalW. In both figures, HH and SS are the default procedures for HMMER and SAM, respectively, HS indicates a HMMER model converted to the SAM format and scored by SAM, and vice versa for SH.

Figure 1

Figure 1

Sensitivity plots for the SCOP all-against-all (test 2). The input alignments were: (A) the results of a WU-BLAST search of nrdb90 aligned with ClustalW; (B) T99 alignments realigned with ClustalW. In both figures, HH and SS are the default procedures for HMMER and SAM, respectively, HS indicates a HMMER model converted to the SAM format and scored by SAM, and vice versa for SH.

Figure 2

Figure 2

Distribution of E-values E of first false positives in test 2. The probability density is with respect to the log10(E) x_-axis. The experimental curves are smoothed (each model was added as a Gaussian of standard deviation 0.1 and area 2873–1), the theoretical curve is ln(10) E exp(–_E). 1S-BL&CLW is the result of a WU-BLAST search of nrdb90 aligned with ClustalW, 1S-T99 the alignment produced by the T99 procedure; HH and SS are the default procedures for HMMER and SAM, respectively.

Figure 3

Figure 3

Sensitivity plots for the SCOP all-against-all. SCOP version 1.50 was used, filtered down to 2873 sequences of less than 40% sequence identity, with a total of 36 612 possible true pairwise relationships. See the text for further details.

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