Computational Prediction of Intronic microRNA Targets using Host Gene Expression Reveals Novel Regulatory Mechanisms

doi:10.1371/journal.pone.0019312

Computational Prediction of Intronic microRNA Targets using Host Gene Expression Reveals Novel Regulatory Mechanisms

Figure 3

CDF plots for weights.

Plots a–d: the CDFs of the weights (a–b) and (c and d) for seven host genes obtained from ULM (a and b), and CORR (c and d) with the actual (a and c) and permutation setups (b and d). The thick gray line in each plot is the CDF obtained from the pooled permutation data for each method. The Table lists the p-values (Willcoxon ranksum test) showing the probability that the weight or correlation data are drawn from the pooled permutated data (see (4) and (5) for detail). P-values marked in red are predicted to be significant (). It should be noted that the host gene MIRHG1 was excluded for analysis since the expression data related this host gene did not exist in the retrieved dataset.

doi: https://doi.org/10.1371/journal.pone.0019312.g003