I would like to use some of the simple annotation aspects of Bioconductor but have had difficulty building a full package (another question for another day). However, I would like to be able to use, for example, alongchromosome from geneplotter without having to explicitly build a data package. I can fairly easily make an environment that contains (for this example) chromosome location (in BP) or chromosome number mapped to my geneIDs (from local data sources). How can I use these simple environment constructs rather than a data package (i.e., perhaps, what are the conceptual and practical differences)? Thanks in advance for any insight. Sean [[alternative HTML version deleted]]

> I would like to use some of the simple annotation aspects of Bioconductor > but have had difficulty building a full package (another question for > another day). However, I would like to be able to use, for example, > alongchromosome from geneplotter without having to explicitly build a data > package. I can fairly easily make an environment that contains (for this > example) chromosome location (in BP) or chromosome number mapped to my > geneIDs (from local data sources). How can I use these simple environment > constructs rather than a data package (i.e., perhaps, what are the > conceptual and practical differences)? an R package is an entity that includes documentation and initialization code that ensures reasonably standard behavior of software across all platforms on which it is installed. when installed in an image of R, all users of that image can make use of the package using the 'library' command, and can get access to documentation using the help facility. the documentation can include validating examples that run with the examples() function. these are strong arguments for using the packaging protocol. if you don't need to share the software (or data object), don't need documentation to remind yourself of what the thing is, and have a fairly simple approach to using R (only a single .RData or .Rprofile that ensures that you can get access to the saved environment of interest) then it is certainly possible that you can just have a globally available function or object that contains the data or functions of interest without too much risk of confusion. and even if you don't have such a simple approach to using R, you can establish your own protocol for getting the unpackaged resources into whatever image of R you happen to be using. the package protocol is a successful approach to managing software. those who ignore it may be condemned to reinvent it.