Sharing Programming Resources Between Bio* Projects Through Remote Procedure Call and Native Call Stack Strategies

J.C.P. Prins, N. Goto, A. Yates, L. Gautier, S. Willis, C. Fields, T. Katayama

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

Open-source software (OSS) encourages computer programmers to reuse software components written by others. In evolutionary bioinformatics, OSS comes in a broad range of programming languages, including C/C++, Perl, Python, Ruby, Java, and R. To avoid writing the same functionality multiple times for different languages, it is possible to share components by bridging computer languages and Bio* projects, such as BioPerl, Biopython, BioRuby, BioJava, and R/Bioconductor. In this chapter, we compare the two principal approaches for sharing software between different programming languages: either by remote procedure call (RPC) or by sharing a local call stack. RPC provides a language-independent protocol over a network interface; examples are RSOAP and Rserve. The local call stack provides a between-language mapping not over the network interface, but directly in computer memory; examples are R bindings, RPy, and languages sharing the Java Virtual Machine stack. This functionality provides strategies for sharing of software between Bio* projects, which can be exploited more often. Here, we present cross-language examples for sequence translation, and measure throughput of the different options. We compare calling into R through native R, RSOAP, Rserve, and RPy interfaces, with the performance of native BioPerl, Biopython, BioJava, and BioRuby implementations, and with call stack bindings to BioJava and the European Molecular Biology Open Software Suite. In general, call stack approaches outperform native Bio* implementations and these, in turn, outperform RPC-based approaches. To test and compare strategies, we provide a downloadable BioNode image with all examples, tools, and libraries included. The BioNode image can be run on VirtualBox-supported operating systems, including Windows, OSX, and Linux.
Original languageEnglish
Title of host publicationEvolutionary Genomics. Statistical and Computational Methods, Volume 2
EditorsM. Anisimova
Pages513-527
Number of pages556
DOIs
Publication statusPublished - 2012

Publication series

NameMethods in Molecular Biology
PublisherHumana Press
Number856

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    Prins, J. C. P., Goto, N., Yates, A., Gautier, L., Willis, S., Fields, C., & Katayama, T. (2012). Sharing Programming Resources Between Bio* Projects Through Remote Procedure Call and Native Call Stack Strategies. In M. Anisimova (Ed.), Evolutionary Genomics. Statistical and Computational Methods, Volume 2 (pp. 513-527). (Methods in Molecular Biology; No. 856). https://doi.org/10.1007/978-1-61779-585-5_21