TargetScore
TargetScore
TargetScore: a probabilistic approach to explore human miRNA targetome by integrating miRNA-overexpression data and sequence information
The R package TargetScore listed below is used to infer the posterior distributions of microRNA (miRNA) targets by probabilistically modeling the likelihood miRNA-overexpression fold-changes and sequence-based scores. Variational 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.
To automate the pipeline of calculating targetScore, we compiled, processed and generated miRNA-overexpression fold-changes from 84 Gene Expression Omnibus (GEO) series corresponding to 6 platforms, 77 human cells or tissues, and 113 distinct miRNAs. The end result is a data package: TargetScoreData. To our knowledge, this is by far the largest miRNA-perturbation data compendium. Accompanied with the data, we also included in this package the sequence feature scores from TargetScanHuman 6.1 including the context+ score and the probabilities of conserved targeting for each miRNA-mRNA interaction (http://www.targetscan.org/cgi-bin/targetscan/data_download.cgi?db=vert_61). Thus, user can use these static sequence-based scores together with user-supplied tissue/cell-specific fold-change due to miRNA overexpression to predict miRNA targets using TargetScore package.
‣ TargetScore software package:
R binary package is also available at Bioconductor:
Recommended Install (in R environment):
source("http://bioconductor.org/biocLite.R")
biocLite("TargetScore")
Install (in Unix Terminal):
R CMD INSTALL TargetScore_0.99.5.tar.gz
Usage (in R environment):
• Load TargetScore:
library(TargetScore)
• Help/Manual:
?TargetScore; vignette(“TargetScore”)
‣ TargetScoreData package:
R binary package is or will be available at Bioconductor:
Install (in terminal):
R CMD INSTALL TargetScoreData_0.99.4.tar.gz
Usage (in R environment):
• Load TargetScore:
library(TargetScoreData)
• Help/Manual:
?TargetScoreData; vignette(“TargetScoreData”)
‣ Citation:
Li, Y., Goldenberg, A., Wong, KC, Zhang Z (2013). A probabilistic approach to explore human miRNA targetome by integrating miRNA-overexpression data and sequence information. Bioinformatics (in press)