Figure 2

Reproducible power of pathway inference methods. The reproducibility power of a pathway inference method in an inference-validation pair datasets is measured by $C_{score}\left(N\right)=\frac{1}{N}{\sum }_{i=1}^N{t}_{score}\left(P_I^i\right)\cdot t_{score}\left(P_V^i\right)$, where $P_I^i$ is the i^th PA in descending order in the inference dataset, $P_V^i$ is its corresponding PA in the validation dataset, and N is the number of selected inferred pathways. The overall reproducibility is then defined as the average Cscore of selected top inferred pathway activities over all six inference-validation pairs. We compared CMI with five inference methods, including the CORG, mean, median, first component score of PCA, as well as no-inferring gene method. Comparing by different ranges of top inferred activities, the CMI showed significant better overall reproducibility over other methods.