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Published in:
2009 | OriginalPaper | Chapter
A Screening Method for Z-Value Assessment Based on the Normalized Edit Distance
Authors : Guillermo Peris, Andrés Marzal
Published in: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
Publisher: Springer Berlin Heidelberg
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Pairwise global alignment scores are used to detect related sequences in genome and proteins. These scores are biased by the length and composition of the compared sequences, and the Z-value is used to estimate their statistical significance. The Z-value is computed using a Monte Carlo algorithm that requires a large number of pairwise alignments between random permutations of the sequences compared.
A different alignment score, the
normalized edit distance
, is independent of the sequence lengths, and it usually takes 2 or 3 standard alignment calculations. In this paper we study the relationship between the normalized edit distance and the Z-value, and propose a method to screen pairs of unrelated sequences, so that Z-value needs to be computed for a small percentage of sequence pairs. We apply this method to the comparison of proteins from
Saccharomyces cerevisiae
,
Escherichia coli
,
Methanococcus jannaschii
and
Haemophilus influenzae
, showing that Z-value has to be computed for less than 1% of all protein pairs.