The Bioperl Toolkit: Perl Modules for the Life Sciences

Abstract

The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.[Supplemental material is available online at www.genome.org. Bioperl is available as open-source software free of charge and is licensed under the Perl Artistic License (http://www.perl.com/pub/a/language/misc/Artistic.html). It is available for download at http://www.bioperl.org. Support inquiries should be addressed to bioperl-l@bioperl.org.]

The genome sequence of allopolyploid Brassica juncea and analysis of differential homoeolog gene expression influencing selection

“…Average pairwise diversity (π) and population differentiation statistic (F ST ) were calculated through Bio::PopGen of bioperl package 65 . Selective sweep regions were identified in the 10 vegetableand 7 oil-use B. juncea subvarieties by combining F ST outliers and π ratio outliers (θπ (vegetable-use/oil-use)) with 100 kb sliding windows and 10 kb steps.…”

Evolutionary genomics of the cold-adapted diatom Fragilariopsis cylindrus

“…Putative promoter nucleotide sequences were collected by extracting good quality sequences from different regions relative to the transcription start site (TSS). The collected sequences were divided into promoters (before TSS) and transcripts (after TSS) and ClustalW 64 alignments of both sets were parsed with custom scripts using Bioperl 65 . We calculated the average identity of the alignments and the average percentage identity in 10-bp intervals using a sliding window approach.…”

Single nucleotide polymorphisms as a prerequisite for autoantigens

“…As illustrated in Table 2, human preproinsulin contains seven synonymous and two non-synonymous SNP. Interestingly, the single non-synonymous SNP located in mature insulin (position 38 of preproinsulin) is contained in two of the six known class-II-restricted T cell epitopes (33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50)(51), and directly flanking the only known class-I-restricted epitope (39)(40)(41)(42)(43)(44)(45)(46)(47) in human insulin ( [22] and references therein).…”

“…The database of genetic variations in human genes was dbSNP build 120 [35]. Human gene structure was from Ensembl [36], human release 34c (accessed via Ensembl perl API and Bioperl modules [37]). For gene annotation we used the GO database [38] with human annotation release 18.0 [39].…”