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In this study, we constructed an R. capsulatus gene co-expression network, and took advantage of the module preservation functionality in WGCNA to identify R. capsulatus gene modules preserved in a collection of published R. sphaeroides mRNA expression data, and in a R. capsulatus proteomics dataset.
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The function, module Preservation, in the WGCNA package was used to calculate the Z statistics.
To discriminate changes in modules comparing SZP and CTS, we performed a module Preservation analysis that identified which modules were preserved in both datasets.
We used the modulePreservation function from the WGCNA library to calculate module preservation statistics [ 31].
To assess the preservation of expression and methylation modules in the corresponding complementary data set, we use the network module preservation statistics described in [ 28] and implemented in the function modulePreservation in the WGCNA R package.
The modulePreservation function implements several powerful network based statistics for evaluating module preservation.
Supplementary Figure 4 Module preservation and replication.
(A) Module preservation (z-summary, x axis) as assessed in the 4 test datasets.
The module preservation of 18R modules in the B73 data was calculated, which can also be regarded as a differential network analysis.
First, the significantly changed proteins of B73 were used to calculate the "module preservation" of 18R as illustrated above.
Module preservation during iterative re-clustering of modules.
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