The Risa R/Bioconductor package: integrative data analysis from experimental metadata and back again

BMC Bioinformatics

Research

Steffen Neumann¹  Susanna-Assunta Sansone²  Alejandra González-Beltrán²  Philippe Rocca-Serra²  Eamonn Maguire² 

[1] Leibniz Institute of Plant Biochemistry, Department of Stress and Developmental Biology, 06120, Halle, Germany;Oxford e-Research Centre, University of Oxford, OX1 3QG, Oxford, UK;

关键词: Mass Spectrometry Data;    Fatty Acid Amide Hydrolase;    Bioconductor Package;    Public Repository;    Feature Request;   

DOI  :  10.1186/1471-2105-15-S1-S11

来源: Springer

【 摘 要 】

BackgroundThe ISA-Tab format and software suite have been developed to break the silo effect induced by technology-specific formats for a variety of data types and to better support experimental metadata tracking. Experimentalists seldom use a single technique to monitor biological signals. Providing a multi-purpose, pragmatic and accessible format that abstracts away common constructs for describing Investigations, Studies and Assays, ISA is increasingly popular. To attract further interest towards the format and extend support to ensure reproducible research and reusable data, we present the Risa package, which delivers a central component to support the ISA format by enabling effortless integration with R, the popular, open source data crunching environment.ResultsThe Risa package bridges the gap between the metadata collection and curation in an ISA-compliant way and the data analysis using the widely used statistical computing environment R. The package offers functionality for: i) parsing ISA-Tab datasets into R objects, ii) augmenting annotation with extra metadata not explicitly stated in the ISA syntax; iii) interfacing with domain specific R packages iv) suggesting potentially useful R packages available in Bioconductor for subsequent processing of the experimental data described in the ISA format; and finally v) saving back to ISA-Tab files augmented with analysis specific metadata from R. We demonstrate these features by presenting use cases for mass spectrometry data and DNA microarray data.ConclusionsThe Risa package is open source (with LGPL license) and freely available through Bioconductor. By making Risa available, we aim to facilitate the task of processing experimental data, encouraging a uniform representation of experimental information and results while delivering tools for ensuring traceability and provenance tracking.Software availabilityThe Risa package is available since Bioconductor 2.11 (version 1.0.0) and version 1.2.1 appeared in Bioconductor 2.12, both along with documentation and examples. The latest version of the code is at the development branch in Bioconductor and can also be accessed from GitHub https://github.com/ISA-tools/Risa, where the issue tracker allows users to report bugs or feature requests.

【 授权许可】

CC BY   
© González-Beltrán et al.; licensee BioMed Central Ltd. 2014