MetaR: simple, high-level languages for data analysis with the R ecosystem
- Published
- Accepted
- Subject Areas
- Bioinformatics, Computational Biology
- Keywords
- Data analysis, R language, Bioinformatics, Composable R, Jetbrains MPS, Language Workbench Technology
- Copyright
- © 2015 Campagne et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. MetaR: simple, high-level languages for data analysis with the R ecosystem. PeerJ PrePrints 3:e1465v2 https://doi.org/10.7287/peerj.preprints.1465v2
Abstract
Data analysis tools have become essential to the study of biology. Tools available today were constructed with layers of technology developed over decades. Here, we explain how some of the principles used to develop this technology are sub-optimal for the construction of data analysis tools for biologists. In contrast, we applied language workbench technology (LWT) to create a data analysis language, called MetaR, tailored for biologists with no programming experience, as well as expert bioinformaticians and statisticians. A key novelty of this approach is its ability to blend user interface with scripting in such a way that beginners and experts alike can analyze data productively in the same analysis platform. While presenting MetaR, we explain how a judicious use of LWT eliminates problems that have historically contributed to data analysis bottlenecks. These results show that language design with LWT can be a compelling approach for developing intelligent data analysis tools.
Author Comment
This is a preprint submission to PeerJ Preprints. In this version, we added a new discussion item: Impact on Development of User Proficiency.