Bioinformatics Advance Access originally published online on March 30, 2006
Bioinformatics 2006 22(12):1437-1439; doi:10.1093/bioinformatics/btl116
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PseudoPipe: an automated pseudogene identification pipeline
1 Banting and Best Department of Medical Research, Donnelly CCBR, University of Toronto 160 College Street, Toronto, ON M5S 3E1, Canada
2 Department of Computer Science, Yale University New Haven, CT 06520, USA
3 Department of Molecular Biophysics and Biochemistry New Haven, CT 06520, USA
4 Department of Biology 506 Wartik Pennsylvania State University, University Park PA 16802, USA
5 Department of Biology, McGill University Stewart Biology Building, 1205 Dr Penfield Avenue, Montreal, QC, H3A 1B1, Canada
*To whom correspondence should be addressed.
Motivation: Mammalian genomes contain many ‘genomic fossils’ i.e. pseudogenes. These are disabled copies of functional genes that have been retained in the genome by gene duplication or retrotransposition events. Pseudogenes are important resources in understanding the evolutionary history of genes and genomes.
Results: We have developed a homology-based computational pipeline (‘PseudoPipe’) that can search a mammalian genome and identify pseudogene sequences in a comprehensive and consistent manner. The key steps in the pipeline involve using BLAST to rapidly cross-reference potential "parent" proteins against the intergenic regions of the genome and then processing the resulting "raw hits" -- i.e. eliminating redundant ones, clustering together neighbors, and associating and aligning clusters with a unique parent. Finally, pseudogenes are classified based on a combination of criteria including homology, intron-exon structure, and existence of stop codons and frameshifts.
Availability: The PseudoPipe program is implemented in Python and can be downloaded at http://pseudogene.org/
Contact: Mark.Gerstein{at}yale.edu or zhaolei.zhang{at}utoronto.ca
Received on December 28, 2005; revised on March 1, 2006; accepted on March 22, 2006
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