Powerful, flexible and simple gene set analysis.
ErmineJ performs analyses of gene sets in high-throughput genomics data such as gene expression profiling studies. A typical goal is to determine whether particular biological pathways are "doing something interesting" in an experiment that generates long lists of candidates. The software is designed to be used by biologists with little or no informatics background (but if you do, you might be interested in the CLI or the R support).
Major features include:
- A simple-to-use graphical user interface with data visualization; runs on your desktop (not browser-based).
- Multiple methods for gene set analysis including over-representation analysis, a gene score resampling method, rank-based methods that use ROC curves or precision-recall, and a method that uses correlation between data profiles.
- Statistical scoring with multiple test correction and corrections for gene multifunctionality.
- Applicability to any taxon, measurement type, or platform. While it was originally designed for expression profiling, ErmineJ can be use for any genome-wide analysis that yields rankings of genes, provided the genes have some gene sets assigned (such as Gene Ontology annotations).
- The ability to create or modify gene sets, facilitating the use of custom or non-GO gene schemes such as MolSigDB and Phenocarta (gene-disease relations).
- A command line interface as well as an application programming interface.
- New in 2018: R support via ermineR.
For more information see the user manual.
If you like ErmineJ, you should check out GOtrack. Explore Gene Ontology and GO annotation history and how changes over time impacts application and interpretation.