[R-pkgs] Introducing Red-R: visual programming for R

[Anup Parikh]

Dear R-Packages Mailing List,

The Red-R development team would like to introduce Red-R: a user
friendly visual programming and data analysis framework for R.

Red-R makes the advanced functionality of R available to the
non-computational users by hiding the computational complexity behind
a visual programming interface. In addition, Red-R improves analysis
readability and data sharing to facilitates better communication in
inter-disciplinary teams.

Analyses are performed by visually linking a series of widgets
together that read, manipulate, and interactively display data. These
pipelines, representing both the data and analysis, can be easily
shared with others. Red-R can also generate reports in odt, html and
latex to help better document and share results.

Red-R is an extension of Orange (http://www.ailab.si/orange), a data
mining framework written in Python and Qt. Red-R accesses all the
functionality and data in R, using the Python interface for R provided
by RPy2 (http://rpy.sourceforge.net). This framework is highly
flexible and can be extended to include virtually all the functionally
R packages currently offer.

If you maintain an R package and are interested in created a GUI
interface please don't hesitate to contact us. We would be happy to
provide any help in creating the Red-R packages.

We would like to thank all those that helped test the software over
the last year and a half and welcome any feedback/suggestions from the
R community.

Please visit the Red-R webpage (www.red-r.org) for more information.

Thank you,
Red-R Development Team
Anup Parikh (anup at red-r.org)
Kyle R. Covington (kyle at red-r.org)