Bioinformatics Advance Access originally published online on February 12, 2004
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Bioinformatics 20(8) © Oxford University Press 2004; all rights reserved.
COACH: profile–profile alignment of protein families using hidden Markov models
1 195 Roque Moraes Drive, Mill Valley, CA 94941, USA and 2 Department of Bioengineering, University of California, Berkeley, CA 94720, USA
Received on August 8, 2003; revised on December 23, 2003; accepted on December 24, 2003
Advance Access Publication February 12, 2004
Motivation: Alignments of two multiple-sequence alignments, or statistical models of such alignments (profiles), have important applications in computational biology. The increased amount of information in a profile versus a single sequence can lead to more accurate alignments and more sensitive homolog detection in database searches. Several profile–profile alignment methods have been proposed and have been shown to improve sensitivity and alignment quality compared with sequence–sequence methods (such as BLAST) and profile–sequence methods (e.g. PSI-BLAST). Here we present a new approach to profile–profile alignment we call Comparison of Alignments by Constructing Hidden Markov Models (HMMs) (COACH). COACH aligns two multiple sequence alignments by constructing a profile HMM from one alignment and aligning the other to that HMM.
Results: We compare the alignment accuracy of COACH with two recently published methods: Yona and Levitt's prof_sim and Sadreyev and Grishin's COMPASS. On two sets of reference alignments selected from the FSSP database, we find that COACH is able, on average, to produce alignments giving the best coverage or the fewest errors, depending on the chosen parameter settings.
Availability: COACH is freely available from www.drive5.com/lobster
Contact: bob{at}drive5.com
* To whom correspondence should be addressed.
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