Jump to ContentJump to Main Navigation
Show Summary Details
More options …

Statistical Applications in Genetics and Molecular Biology

Editor-in-Chief: Sanguinetti, Guido


IMPACT FACTOR 2018: 0.536
5-year IMPACT FACTOR: 0.764

CiteScore 2018: 0.49

SCImago Journal Rank (SJR) 2018: 0.316
Source Normalized Impact per Paper (SNIP) 2018: 0.342

Mathematical Citation Quotient (MCQ) 2018: 0.02

Online
ISSN
1544-6115
See all formats and pricing
More options …
Volume 3, Issue 1

Issues

Volume 10 (2011)

Volume 9 (2010)

Volume 6 (2007)

Volume 5 (2006)

Volume 4 (2005)

Volume 2 (2003)

Volume 1 (2002)

On the Dependence Structure of Sequence Alignment Scores Calculated with Multiple Scoring Matrices

Florian Frommlet / Andreas Futschik
Published Online: 2004-10-05 | DOI: https://doi.org/10.2202/1544-6115.1073

A common practice in protein sequence alignment is to try several scoring matrices until “something interesting" is found. This leads to a multiple testing problem making p- and E-values hard to interpret. We focus on local alignment and propose to use logistic copula functions to model explicitly the dependence structure of scores obtained using different scoring matrices. By doing this, we obtain p-value correction factors when using more than one scoring matrix on the same sequences. Furthermore the parameter of the logistic copula can be interpreted as measure of dependence, providing insight concerning the relatedness of the scores from different matrices.

Keywords: sequence alignment; copula functions; multivariate dependence

About the article

Published Online: 2004-10-05


Citation Information: Statistical Applications in Genetics and Molecular Biology, Volume 3, Issue 1, Pages 1–12, ISSN (Online) 1544-6115, DOI: https://doi.org/10.2202/1544-6115.1073.

Export Citation

©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston.Get Permission

Comments (0)

Please log in or register to comment.
Log in