Integrative Differential Network Analysis in Genomics.

iDINGO: Integrative Differential Network Analysis in Genomics

iDINGO is a pathway-based method for estimating group-specific conditional dependencies and inferring differential networks between groups, based on genomic data. This can be done in a single-platform framework (for example, RNA-Seq data) or an integrative multi-platform framework (microRNA -> RNA -> Proteomics, where data from all three platforms are available for every sample).

Using iDINGO

We recommend filtering genomic data to fewer than 300 genes, generally filtered using a pathway/pathways of interest. Single-platform analyses are run using dingo with an nxp matrix, where n is the number of samples. Multi-platform analyses are run using idingo, with up to 3 separate data matrices containing the same n samples. For both dingo and idingo, the number of bootstraps is specified by B (we recommend at least 100). Parallel computing can speed this step up significantly, by setting the number of cores. Finally, the plotNetwork function plots the differential network identified by dingo or idingo, based on a user-specified p-value or differential score threshold.