Literature DB >> 18973434

Significance of gapped sequence alignments.

Lee A Newberg1.   

Abstract

Measurement of the the statistical significance of extreme sequence alignment scores is key to many important applications, but it is difficult. To precisely approximate alignment score significance, we draw random samples directly from a well chosen, importance-sampling probability distribution. We apply our technique to pairwise local sequence alignment of nucleic acid and amino acid sequences of length up to 1000. For instance, using a BLOSUM62 scoring system for local sequence alignment, we compute that the p-value of a score of 6000 for the alignment of two sequences of length 1000 is (3.4 +/- 0.3) x 10(-1314). Further, we show that the extreme value significance statistic for the local alignment model that we examine does not follow a Gumbel distribution. A web server for this application is available at http://bayesweb.wadsworth.org/alignmentSignificanceV1/.

Mesh:

Year:  2008        PMID: 18973434      PMCID: PMC2737730          DOI: 10.1089/cmb.2008.0125

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  9 in total

1.  Sampling rare events: statistics of local sequence alignments.

Authors:  Alexander K Hartmann
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2002-04-15

Review 2.  Statistical significance in biological sequence analysis.

Authors:  Alexander Yu Mitrophanov; Mark Borodovsky
Journal:  Brief Bioinform       Date:  2006-03       Impact factor: 11.622

3.  Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes.

Authors:  S Karlin; S F Altschul
Journal:  Proc Natl Acad Sci U S A       Date:  1990-03       Impact factor: 11.205

4.  A general method applicable to the search for similarities in the amino acid sequence of two proteins.

Authors:  S B Needleman; C D Wunsch
Journal:  J Mol Biol       Date:  1970-03       Impact factor: 5.469

5.  Identification of common molecular subsequences.

Authors:  T F Smith; M S Waterman
Journal:  J Mol Biol       Date:  1981-03-25       Impact factor: 5.469

6.  Searching protein sequence libraries: comparison of the sensitivity and selectivity of the Smith-Waterman and FASTA algorithms.

Authors:  W R Pearson
Journal:  Genomics       Date:  1991-11       Impact factor: 5.736

7.  Memory-efficient dynamic programming backtrace and pairwise local sequence alignment.

Authors:  Lee A Newberg
Journal:  Bioinformatics       Date:  2008-06-16       Impact factor: 6.937

8.  Local sequence alignments statistics: deviations from Gumbel statistics in the rare-event tail.

Authors:  Stefan Wolfsheimer; Bernd Burghardt; Alexander K Hartmann
Journal:  Algorithms Mol Biol       Date:  2007-07-11       Impact factor: 1.405

9.  A probabilistic model of local sequence alignment that simplifies statistical significance estimation.

Authors:  Sean R Eddy
Journal:  PLoS Comput Biol       Date:  2008-05-30       Impact factor: 4.475

  9 in total
  6 in total

1.  Gene expression profile and immunological evaluation of unique hypothetical unknown proteins of Mycobacterium leprae by using quantitative real-time PCR.

Authors:  Hee Jin Kim; Kalyani Prithiviraj; Nathan Groathouse; Patrick J Brennan; John S Spencer
Journal:  Clin Vaccine Immunol       Date:  2012-12-12

2.  Exact calculation of distributions on integers, with application to sequence alignment.

Authors:  Lee A Newberg; Charles E Lawrence
Journal:  J Comput Biol       Date:  2009-01       Impact factor: 1.479

3.  New finite-size correction for local alignment score distributions.

Authors:  Yonil Park; Sergey Sheetlin; Ning Ma; Thomas L Madden; John L Spouge
Journal:  BMC Res Notes       Date:  2012-06-12

4.  Where does the alignment score distribution shape come from?

Authors:  Philippe Ortet; Olivier Bastien
Journal:  Evol Bioinform Online       Date:  2010-12-12       Impact factor: 1.625

5.  Accurate statistics for local sequence alignment with position-dependent scoring by rare-event sampling.

Authors:  Stefan Wolfsheimer; Inke Herms; Sven Rahmann; Alexander K Hartmann
Journal:  BMC Bioinformatics       Date:  2011-02-03       Impact factor: 3.169

6.  Error statistics of hidden Markov model and hidden Boltzmann model results.

Authors:  Lee A Newberg
Journal:  BMC Bioinformatics       Date:  2009-07-09       Impact factor: 3.307

  6 in total

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