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Bioinformatics. 2008 Feb 1;24(3):319-24. Epub 2007 Nov 26.

Choosing BLAST options for better detection of orthologs as reciprocal best hits.

Author information

  • 1Department of Biology, Wilfrid Laurier University, 75 University Avenue West, Waterloo, ON, Canada, N2L 3C5. gmoreno@wlu.ca

Abstract

MOTIVATION:

The analyses of the increasing number of genome sequences requires shortcuts for the detection of orthologs, such as Reciprocal Best Hits (RBH), where orthologs are assumed if two genes each in a different genome find each other as the best hit in the other genome. Two BLAST options seem to affect alignment scores the most, and thus the choice of a best hit: the filtering of low information sequence segments and the algorithm used to produce the final alignment. Thus, we decided to test whether such options would help better detect orthologs.

RESULTS:

Using Escherichia coli K12 as an example, we compared the number and quality of orthologs detected as RBH. We tested four different conditions derived from two options: filtering of low-information segments, hard (default) versus soft; and alignment algorithm, default (based on matching words) versus Smith-Waterman. All options resulted in significant differences in the number of orthologs detected, with the highest numbers obtained with the combination of soft filtering with Smith-Waterman alignments. We compared these results with those of Reciprocal Shortest Distances (RSD), supposed to be superior to RBH because it uses an evolutionary measure of distance, rather than BLAST statistics, to rank homologs and thus detect orthologs. RSD barely increased the number of orthologs detected over those found with RBH. Error estimates, based on analyses of conservation of gene order, found small differences in the quality of orthologs detected using RBH. However, RSD showed the highest error rates. Thus, RSD have no advantages over RBH.

AVAILABILITY:

Orthologs detected as Reciprocal Best Hits using soft masking and Smith-Waterman alignments can be downloaded from http://popolvuh.wlu.ca/Orthologs.

PMID:
18042555
[PubMed - indexed for MEDLINE]
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