DREAM3: Network Inference Using Dynamic Context Likelihood of Relatedness and the Inferelator

doi:10.1371/journal.pone.0009803

DREAM3: Network Inference Using Dynamic Context Likelihood of Relatedness and the Inferelator

Figure 6

Distributions of static vs. dynamic mutual information values.

We computed static and dynamic Mutual Information (MI) values for every possible regulatory interaction. Vertical lines represent distribution means. We present the combined probability densities for the five -gene networks. We show that: 1) both dynamic and static MI densities are right skewed, consistent with the assumption that MI values of true positives would be higher than MI values of true negatives; 2) the standard deviations for static MI z-scores, , is larger than for dynamic MI z-scores, , possibly making it easier to recover TPs from the dynamic MI z-scores; and 3) most dynamic MI values are smaller than the mean of the static MI values; this shift confounds mixed-CLR. Note that both static- and dynamic-MI values were estimated from the same number of observations, using the same number of bins. Thus, dataset size or bin number differences do not explain the shift in distributions.

doi: https://doi.org/10.1371/journal.pone.0009803.g006