repo: an R package for data-centered management of bioinformatic pipelines

BMC Bioinformatics

Software

Francesco Napolitano¹ 

[1] Telethon Institute of Genetics and Medicine (TIGEM), Via Campi Flegrei 34, 80078, Pozzuoli (NA), Italy;

关键词: Reproducible research;    R language;    Data flows;    Data pipelines;   

DOI  :  10.1186/s12859-017-1510-6

 received in 2016-07-18, accepted in 2017-01-31,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundReproducibility in Data Analysis research has long been a significant concern, particularly in the areas of Bioinformatics and Computational Biology. Towards the aim of developing reproducible and reusable processes, Data Analysis management tools can help giving structure and coherence to complex data flows. Nonetheless, improved software quality comes at the cost of additional design and planning effort, which may become impractical in rapidly changing development environments. I propose that an adjustment of focus from processes to data in the management of Bioinformatic pipelines may help improving reproducibility with minimal impact on preexisting development practices.ResultsIn this paper I introduce the repoR package for bioinformatic analysis management. The tool supports a data-centered philosophy that aims at improving analysis reproducibility and reusability with minimal design overhead. The core of repo lies in its support for easy data storage, retrieval, distribution and annotation. In repo the data analysis flow is derived a posteriori from dependency annotations.ConclusionsThe repo package constitutes an unobtrusive data and flow management extension of the R statistical language. Its adoption, together with good development practices, can help improving data analysis management, sharing and reproducibility, especially in the fields of Bioinformatics and Computational Biology.

【 授权许可】

CC BY   
© The Author(s) 2017