On best practices in the development of bioinformatics software

Frontiers in Genetics

Volumn 5, Issue JUL, 2014, Pages

  Leprevost, Felipe da Veiga ^a,b   Barbosa, Valmir C ^c   Francisco, Eduardo L ^b   Perez Riverol, Yasset ^d   Carvalho, Paulo C ^a  

^a INSTITUTO OSWALDO CRUZ   (Brazil)

^b Hexabio Bioinformatics   (Brazil)

^c FEDERAL UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^d EUROPEAN BIOINFORMATICS INSTITUTE   (United Kingdom)

Author keywords

Best practices; Bioinformatics; Repository; Source control; Test

Indexed keywords

ACCESS TO INFORMATION; BIOINFORMATICS; CLINICAL DATA REPOSITORY; CODING; COMPUTER PROGRAM; COMPUTER SECURITY; DATA BASE; DATA PROCESSING; DOCUMENTATION; GENETIC CODE; INFORMATION PROCESSING; INFORMATION STORAGE; INFORMATION SYSTEM; NOTE; PROGRAM DEVELOPMENT; READ CODE;

EID: 84906223015     PISSN: None     EISSN: 16648021     Source Type: Journal    
DOI: 10.3389/fgene.2014.00199     Document Type: Note

References (19)

1. Altschul, S., Demchak, B., Durbin, R., Gentleman, R., Krzywinski, M., Li, H., et al. (2013). The anatomy of successful computational biology software. Nat. Biotechnol. 31, 894-897. doi: 10.1038/nbt0614-592b
2. Figshare (2014). Figshare - Credit for All Your Research. Available online at: http://figshare.com/
3. Giardine, B. (2005). Galaxy: a platform for interactive large-scale genome analysis. Genome Res. 15, 1451-1455. doi: 10.1101/gr.4086505
4. GitHub (2014). Github. Available online at: http://github.com/
5. Ince, D. C., Hatton, L., and Graham-Cumming, J. (2012). The case for open computer programs. Nature 482, 485-488. doi: 10.1038/nature10836
6. Langmead, B., Trapnell, C., Pop, M., and Salzberg, S. L. (2009). Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10:R25. doi: 10.1186/gb-2009-10-3-r25
7. Mozilla Foundation. (2014). Mozilla Science Lab. Available online at: http://mozillascience.org/
8. Perez-Riverol, Y., Hermjakob, H., Kohlbacher, O., Martens, L., Creasy, D., Cox, J., et al. (2013). Computational proteomics pitfalls and challenges: havanabioinfo 2012 workshop report. J. Proteomics 87, 134-138. doi: 10.1016/j.jprot.2013.01.019
9. Perez-Riverol, Y., Wang, R., Hermjakob, H., Mller, M., Vesada, V., and Vizcano, J. A. (2014). Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective. Biochim. Biophys. Acta. 1844(1 Pt A), 63-76. doi: 10.1016/j.bbapap.2013.02.032
10. Prli, A., and Procter, J. B. (2012). Ten simple rules for the open development of scientific software. PLoS Comput. Biol. 8:e1002802. doi: 10.1371/journal.pcbi.1002802
11. Sandve, G. K., Nekrutenko, A., Taylor, J., and Hovig, E. (2013). Ten simple rules for reproducible computational research. PLoS Comput. Biol. 9:e1003285. doi: 10.1371/journal.pcbi.1003285
12. Seemann, T. (2013). Ten recommendations for creating usable bioinformatics command line software. Giga Sci. 2:15. doi: 10.1186/2047-217X-2-15
13. Stajich, J. E. (2002). The bioperl toolkit: perl modules for the life sciences. Genome Res. 12, 1611-1618. doi: 10.1101/gr.361602
14. Summers, N. (2014). Mozilla Science Lab, Github and Figshare Team up to Fix the Citation of Code in Academia. Available online at: thenextweb.com/dd/2014/03/17/mozilla-science-lab-github-figshare-team-fix-citation-code-academia/
15. Torvalds, L. (2014a). Git. Available online at: http://git-scm.com
16. Torvalds, L. (2014b). The Linux Kernel Project. Available online at: http://kernel.org
17. Trapnell, C., Pachter, L., and Salzberg, S. L. (2009). Tophat: discovering splice junctions with rna-seq. Bioinformatics 25, 1105-1111. doi: 10.1093/bioinformatics/btp120
18. Via, A., Blicher, T., Bongcam-Rudloff, E., Brazas, M. D., Brooksbank, C., Budd, A., et al. (2013). Best practices in bioinformatics training for life scientists. Brief Bioinform. 14, 528-537. doi: 10.1093/bib/bbt043
19. Wilson, G., Aruliah, D. A., Brown, C. T., Chue Hong, N. P., Davis, M., Guy, R. T., et al. (2014). Best practices for scientific computing. PLoS Biol. 12:e1001745. doi: 10.1371/journal.pbio.1001745