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The modulePreservation function implements several powerful network based statistics for evaluating module preservation.
The modulePreservation function implements a permutation test involving several powerful network based statistics for evaluating module preservation.
In addition to evaluating module preservation between the two Rhodobacter species, we wanted to assess pairwise conservation of expression between orthologs.
We tried using a novel method for evaluating module preservation [ 34] to check whether modules are preserved in terms of density and connectivity between the species regardless of the parameters used to obtain the modules.
Our study has several strengths including the use of multiple large data sets, carefully validated brain co-expression modules from Oldham et al 2008, and a powerful statistical approach for evaluating module preservation.
The theoretical development approach can be applied to hollow fiber membrane modules for other applications and the theoretical solutions can be utilized for evaluating modules using various eddy promoting designs.
For Greedy and QCUT, we used the relevant software to evaluate modules and estimate the resulting modularity.
To find genes of high connectivity (i.e. 'hubs') in consensus modules, we evaluated the module eigengene-based connectivity (kME) as the correlation between the gene expression and the module eigengene [ 55].
Second, for PrCa-associated modules, we further evaluated the module preservation in the testing dataset.
The evaluation was anonymous and in total 3568 of 4232 (84%% overall response) students evaluated the module.
Functional enrichments of each cluster were then evaluated by module enrichment analysis [ 12] of its gene members, and illustrated using Cytoscape software [ 13] as illustrated in Figure 3.
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