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The module size determines how many entries will be tested for co-occurrence, the support sets a lower boundary on the required number of co-occurrences, and the Z-score/P-value cutoff sets the significance threshold.
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To identify all modules with a score associated with an FDR of 5% or less, we determined a critical value c for each module size class that gave FDR c,k) = 0.05.
Edge-swapping (1000 simulations, see above) was used to determine occurrence probabilities and gene co-occurrence was analyzed using module size 3 (co-occurrence of three genes), bi-binomial Z-score cutoff 6, bi-binomial P-value cutoff 1.0E-5, and support 5. Supplementary material Simulation S1 provides details on why module size 3 is chosen.
Then, module clustering was process based on dissimilarity matrix with minimum module size setting at 100.
Basic Statistics (# genes, # modules, average module size (AMS), Density (DY)).
At this step size, the maximum module size was 54 (module size (3 > size ≤ 54).
The module fitness score measures both module size and homogeneity.
The maximum module size at this step was 160 (module size (3 > size ≤ 160).
We also summarize the module size of significant and non-significant modules across platforms.
Modules were identified with dynamic tree cut with minimum module size = 20, using the hybrid method.
Modules were detected using a dynamic tree-cutting algorithm (hybrid mode, minimal module size of 100).
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