FunNet is an original integrative tool for exploring transcriptional interactions in microarray gene expression datasets. The analytical approach implemented in FunNet relies on knowledge extracted from public annotation databases to improve the biological relevance of the modular interaction patterns identified in co-expression networks. FunNet's algorithmic core is implemented as an R package freely downloadable from one of the CRAN mirrors. This web site provides a user-friendly graphical interface designed to promote FunNet's open use by the community. Details about the format of the data files and various parameters and analytical options are provided in FunNet's tutorial.
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Start by selecting the genome to be considered as a reference for transcriptional interactions analysis. Two main analytical situations are possible:
- the analysis of a single set of transcriptional profiles;
- the simultaneous analysis of two sets of differentially expressed transcripts.
In the latter case, FunNet can optionally perform a discriminant functional analysis of the two sets of genes to identify themes specifically caracterizing each of them.