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.
conda install -c bioconda bioconductor-targetscore
conda install -c bioconda/label/gcc7 bioconductor-targetscore
conda install -c bioconda/label/cf201901 bioconductor-targetscore