Most packages contributed by users are software packages. However, there are instances where other package types are submitted. The following sections will go into specifics we look for in each of the non-software type packages.
Annotation packages are database-like packages that provide information linking identifies (e.g., Entrez gene names or Affymetrix probe ids) to other information (e.g., chromosomal location, Gene Ontology category).
Experiment data packages provide data sets that are used, often by software packages, to illustrate particular analyses. These packages contain curated data from an experiment, teaching course or publication and in most cases contain a single data set.
We look for similar requirements as software packages, but most importantly is proper documentation for the data included within the package.
These light weight packages are related to resources added to AnnotationHub or ExperimentHub. The package should minimally contain the resource metadata, man pages describing the resources, and a vignette. It may also contain supporting R function the author wants to provide. These packages are similar to the above Annotation or Experiment data packages except the data is stored in AWS S3 buckets or publicly accessibly sites instead of in the package itself.
There is more information about creating a hub packages as well as the contents
of on in the “Creating a Hub Package” vignette within the
Workflow packages contain vignettes that describe a bioinformatics workflow
that involves multiple Bioconductor packages. These vignettes are usually more
extensive than the vignettes that accompany software packages. These packages do
R/ directories nor a
data/ directory as ideally
workflows make use of existing data in a Bioconductor package.