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The prediction of microRNA targets is a challenging task that has given rise to several prediction algorithms. Databases of predicted targets can be used in a microRNA target enrichment analysis, enhancing our capacity to extract functional information from gene lists. However, the available tools in this field analyze gene sets one by one limiting their use in a meta-analysis. Here, we present an R system for miRNA enrichment analysis that is suitable for systems biology. These collection of R scripts and embedded data allow using predicted targets of public databases or a custom integration of them. As a proof-of-principle, we have successfully performed the challenging analysis of 2158 tumoral samples at a time. The obtained results have been summarized in a network where each cancer disease is linked to enriched miRNAs and overrepresented functions. These network connections have proven to be an invaluable resource for the study of biological and pathological causes and effects of the expression of miRNAs.[1]
