Package anRichmentMethods includes genral functions for working with collections and for enrichment calculations while anRichment contains mostly data together with functions to access the stored collections and to build specific collections dynamically from external data.
Click here to access the tutorial page.
Download and installation
Prerequisites
Although the packages can be installed under older R versions (down to R-3.0.0), we strongly recommend using the newest R version because the external annotation packages (GO, organism-specific genome annotation) are continuously updated.
Simple installation
We provide an installation script
that automatically installs all necesary dependencies as well as both
packages anRichmentMethods and anRichment. The simplest installation procedure consist of these two steps:
sessionInfo()
.
Manual installation
If the above automatic script fails, one can install the dependencies and the anRichment/anRichmentMethods
packages separately. Download the packages anRichment and anRichmentMethods from the links below, then follow
these installation instructions.
R package download
Packages anRichment and anRichmentMethods are available here in the source form.
Should you discover bugs (of which there are most likely plenty), please report them to Peter Langfelder
(peter.langfelder at gmail.com).
Extensions: packages containing additional collections
Some users may be interested in additional collections beyond the stanadard internal collection and the
dynamically
generated GO collection. We aim to provide further collections in separate "mostly-data" packages that
contain an
additional collection (or collections) and simple accessor functions. Currently, there are 2 such packages
available:
Huntington's Disease WGCNA Collection
This collection contains, as gene sets, the modules determined by Weighted Gene Co-expression Network Analysis (WGCNA) applied to various Huntington's disease (HD)-related data sets. Some analyses are plain WGCNA, some are consensus WGCNA across multiple data sets. Some of the data sets survey expression in human, and some in mouse data, so the collection contains gene sets corresponding to both organisms.
Brain Type Cell Type Marker Collection
This collection contains sets of genes over-expressed in broad cell types defined from single cell RNA-seq on mouse brain cells.
Brain Disease Collection
This collection contains sets of genes implicated in brain diseases in public data.
The package is currently maintained by Peter Langfelder and contains gene sets compiled by multiple contributors. At the risk of putting out an incomplete list, these include Jeremy A. Miller, Michael Palazzolo, Jim Wang, X. William Yang and his group (in particular, Jeff Cantle and Nan Wang), Dan Salomon and his group, Jeff Aaronson and the team at Rancho Biosciences. PL gratefully ackowledges the support of CHDI, Inc.