Caching and Visualizing Statistical Analyses

We present the cacher and CodeDepends packages for R, which provide tools for (1) caching and analyzing the code for statistical analyses and (2) distributing these analyses to others in an efficient manner over the web. The cacher package takes objects created by evaluating R expressions and stores them in key-value databases. These databases of cached objects can subsequently be assembled into “cache packages” for distribution over the web. The cacher package also provides tools to help readers examine the data and code in a statistical analysis and reproduce, modify, or improve upon the results. In addition, readers can easily conduct alternate analyses of the data. The CodeDepends package provides complementary tools for analyzing and visualizing the code for a statistical analysis and this functionality has been integrated into the cacher package. In this chapter we describe the cacher and CodeDepends packages and provide examples of how they can be used for reproducible research.

INTERACTING WITH LOCAL AND REMOTE DATA RESPOSITORIES USING THE stashR PACKAGE

The stashR package (a Set of Tools for Administering SHared Repositories) for R implements a simple key-value style database where character string keys are associated with data values. The key-value databases can be either stored locally on the user's computer or accessed remotely via the Internet. Methods specific to the stashR package allow users to share data repositories or access previously created remote data repositories. In particular, methods are available for the S4 classes localDB and remoteDB to insert, retrieve, or delete data from the database as well as to synchronize local copies of the data to the remote version of the database. Users efficiently access information from a remote database by retrieving only the data files indexed by user-specified keys and caching this data in a local copy of the remote database. The local and remote counterparts of the stashR package offer the potential to enhance reproducible research by allowing users of Sweave to cache their R computations for a research paper in a localDB database. This database can then be stored on the Internet as a remoteDB database. When readers of the research paper wish to reproduce the computations involved in creating a specific figure or calculating a specific numeric value, they can access the remoteDB database and obtain the R objects involved in the computation.