TargetScore: Infer microRNA targets using
microRNA-overexpression data and sequence information
Description
Infer the posterior distributions of microRNA targets by
probabilistically modelling the likelihood
microRNA-overexpression fold-changes and sequence-based scores.
Variaitonal Bayesian Gaussian mixture model (VB-GMM) is applied
to log fold-changes and sequence scores to obtain the
posteriors of latent variable being the miRNA targets. The
final targetScore is computed as the sigmoid-transformed
fold-change weighted by the averaged posteriors of target
components over all of the features.