Estimates of statistical significance for comparison of individual positions in multiple sequence alignments

<p>Abstract</p> <p>Background</p> <p>Profile-based analysis of multiple sequence alignments (MSA) allows for accurate comparison of protein families. Here, we address the problems of detecting statistically confident dissimilarities between (1) MSA position and a set of...

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Main Authors: Sadreyev Ruslan I, Grishin Nick V
Format: Article
Language:English
Published: BMC 2004-08-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/5/106
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spelling doaj-3cfa9672d1f44889afd73271524f5efe2020-11-25T02:28:21ZengBMCBMC Bioinformatics1471-21052004-08-015110610.1186/1471-2105-5-106Estimates of statistical significance for comparison of individual positions in multiple sequence alignmentsSadreyev Ruslan IGrishin Nick V<p>Abstract</p> <p>Background</p> <p>Profile-based analysis of multiple sequence alignments (MSA) allows for accurate comparison of protein families. Here, we address the problems of detecting statistically confident dissimilarities between (1) MSA position and a set of predicted residue frequencies, and (2) between two MSA positions. These problems are important for (i) evaluation and optimization of methods predicting residue occurrence at protein positions; (ii) detection of potentially misaligned regions in automatically produced alignments and their further refinement; and (iii) detection of sites that determine functional or structural specificity in two related families.</p> <p>Results</p> <p>For problems (1) and (2), we propose analytical estimates of P-value and apply them to the detection of significant positional dissimilarities in various experimental situations. (a) We compare structure-based predictions of residue propensities at a protein position to the actual residue frequencies in the MSA of homologs. (b) We evaluate our method by the ability to detect erroneous position matches produced by an automatic sequence aligner. (c) We compare MSA positions that correspond to residues aligned by automatic structure aligners. (d) We compare MSA positions that are aligned by high-quality manual superposition of structures. Detected dissimilarities reveal shortcomings of the automatic methods for residue frequency prediction and alignment construction. For the high-quality structural alignments, the dissimilarities suggest sites of potential functional or structural importance.</p> <p>Conclusion</p> <p>The proposed computational method is of significant potential value for the analysis of protein families.</p> http://www.biomedcentral.com/1471-2105/5/106
collection DOAJ
language English
format Article
sources DOAJ
author Sadreyev Ruslan I
Grishin Nick V
spellingShingle Sadreyev Ruslan I
Grishin Nick V
Estimates of statistical significance for comparison of individual positions in multiple sequence alignments
BMC Bioinformatics
author_facet Sadreyev Ruslan I
Grishin Nick V
author_sort Sadreyev Ruslan I
title Estimates of statistical significance for comparison of individual positions in multiple sequence alignments
title_short Estimates of statistical significance for comparison of individual positions in multiple sequence alignments
title_full Estimates of statistical significance for comparison of individual positions in multiple sequence alignments
title_fullStr Estimates of statistical significance for comparison of individual positions in multiple sequence alignments
title_full_unstemmed Estimates of statistical significance for comparison of individual positions in multiple sequence alignments
title_sort estimates of statistical significance for comparison of individual positions in multiple sequence alignments
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2004-08-01
description <p>Abstract</p> <p>Background</p> <p>Profile-based analysis of multiple sequence alignments (MSA) allows for accurate comparison of protein families. Here, we address the problems of detecting statistically confident dissimilarities between (1) MSA position and a set of predicted residue frequencies, and (2) between two MSA positions. These problems are important for (i) evaluation and optimization of methods predicting residue occurrence at protein positions; (ii) detection of potentially misaligned regions in automatically produced alignments and their further refinement; and (iii) detection of sites that determine functional or structural specificity in two related families.</p> <p>Results</p> <p>For problems (1) and (2), we propose analytical estimates of P-value and apply them to the detection of significant positional dissimilarities in various experimental situations. (a) We compare structure-based predictions of residue propensities at a protein position to the actual residue frequencies in the MSA of homologs. (b) We evaluate our method by the ability to detect erroneous position matches produced by an automatic sequence aligner. (c) We compare MSA positions that correspond to residues aligned by automatic structure aligners. (d) We compare MSA positions that are aligned by high-quality manual superposition of structures. Detected dissimilarities reveal shortcomings of the automatic methods for residue frequency prediction and alignment construction. For the high-quality structural alignments, the dissimilarities suggest sites of potential functional or structural importance.</p> <p>Conclusion</p> <p>The proposed computational method is of significant potential value for the analysis of protein families.</p>
url http://www.biomedcentral.com/1471-2105/5/106
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