Detecting microRNA binding and siRNA off-target effects from expression data

The algorithm Sylamer finds over- or underrepresented nucleotide motifs, such as microRNA seeds, in a gene list ranked according to expression levels and thus establishes whether a microRNA is directly affecting gene expression. Sylamer is a method for detecting microRNA target and small interfering RNA off-target signals in 3′ untranslated regions from a ranked gene list, sorted from upregulated to downregulated, after a microRNA perturbation or RNA interference experiment. The output is a landscape plot that tracks occurrence biases using hypergeometric P-values for all words across the gene ranking. We demonstrated the utility, speed and accuracy of this approach on several datasets.