MetaR takes advantage of Language Workbench Technology to facilitate data analysis with the R language. It can be used by:

biologists with limited computational experience. No programming skills are required to start analyzing data. bioinformaticians who need to perform repetitive analyses and find it beneficial to design and use specialized analyses micro-languages to increase productivity and consistency of data analysis. bioinformaticians who wish to package state of the art analysis methods into user friendly metaR analysis language constructs. MetaR can act as a bridge between analysis experts who develop analysis methods in R and wish to distribute these methods to the broadest audience without investing a lot of effort in developing user interfaces. R programmers who want to experiment with language composition and extension. MetaR offers a composable R language that can be extended with new types of expression and arbitrary new language constructs, including graphical notations. See Chapter 12 of the documentation for details about Composable R.

See these blog posts about MetaR: [Reproducible analyses with docker] [Biomart] [UpSet, Sleuth, MA plots]

MetaR is a component of the NYoSh Data Analysis Workbench. It is designed to work well with other languages of the platform. Importantly, users who learn how to use one component will acquire skills useful with other languages offered on the platform.

The following snapshot illustrates how MetaR simplifies data analysis: we call differentially expressed genes with edgeR, join the resulting table with the table of counts, and produce a heatmap for differentially expressed genes (selected by FDR and fold change):

Here’s another example showing how to look at intersection of gene lists with the integration of UpSetR/MetaR integration:

Supported Platforms

MetaR has been tested on Linux, MacOS X and Windows.

Installation or upgrade

To install MetaR, see installation instructions for each supported platform. To upgrade MetaR, use the MPS Preferences > Plugins dialog. MPS will notify you of available upgrades. Follow instructions to install the new version of the plugin.

If upgrading from a previous version, check out our migration guide to see if you have to perform some extra-steps to upgrade your analyses.

Training Sessions

We offer training sessions periodically. Members of our CTSC institutions get priority, but the sessions are open to all, so feel free to register if you are located in NYC. If you cannot attend one of these sessions, please see the video tutorials.

Source Code

MetaR is open-source (Apache 2.0 license). You can get the code from this GitHub repository:

git clone git@github.com:CampagneLaboratory/MetaR.git

Q&A User forum

You may use the project user forum to ask questions about MetaR and/or share your experience with other users.

Documentation



We maintain a documentation booklet that describes how to use MetaR. You can obtain the documentation for Tablets or in PDF format:

MetaR PDF documentation 2.4.0 17.96 MB Download

Citation

If you use MetaR, please cite:

Fabien Campagne, William ER Digan, Manuele Simi MetaR: simple, high-level languages for data analysis with the R ecosystem bioRxiv 2015 doi: http://dx.doi.org/10.1101/030254