On the significance of sequence alignments when using multiple scoring matrices | Zendy

Florian Frommlet | Zendy; Andreas Futschik | Zendy; Małgorzata Bogdan | Zendy

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On the significance of sequence alignments when using multiple scoring matrices

Author(s) -

Florian Frommlet,

Andreas Futschik,

Małgorzata Bogdan

Publication year - 2004

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btg498

Subject(s) - pairwise comparison , sequence (biology) , bonferroni correction , set (abstract data type) , multiple sequence alignment , computer science , matrix (chemical analysis) , sequence alignment , algorithm , simple (philosophy) , data mining , mathematics , artificial intelligence , statistics , peptide sequence , genetics , biology , philosophy , materials science , epistemology , gene , composite material , programming language

Pairwise local sequence alignment is commonly used to search data bases for sequences related to some query sequence. Alignments are obtained using a scoring matrix that takes into account the different frequencies of occurrence of the various types of amino acid substitutions. Software like BLAST provides the user with a set of scoring matrices available to choose from, and in the literature it is sometimes recommended to try several scoring matrices on the sequences of interest. The significance of an alignment is usually assessed by looking at E-values and p-values. While sequence lengths and data base sizes enter the standard calculations of significance, it is much less common to take the use of several scoring matrices on the same sequences into account. Altschul proposed corrections of the p-value that account for the simultaneous use of an infinite number of PAM matrices. Here we consider the more realistic situation where the user may choose from a finite set of popular PAM and BLOSUM matrices, in particular the ones available in BLAST. It turns out that the significance of a result can be considerably overestimated, if a set of substitution matrices is used in an alignment problem and the most significant alignment is then quoted.

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