We used the GOSemSim package from CRAN (http://cran.r-project.org) to evaluate intra-module gene function similarity.
To further assess intra-module gene function similarity, the mgeneSim function based on Wang's method in the GOSemSim (R package) was used to estimate semantic similarity of GO terms [45], [46].
These authors introduced prior information on genetic modules from gene function and pathway databases, which could be incorporated in our model in a similar way.
This shows that our module selection method has the ability to identify the optimal number of modules by incorporating gene function category information.
Finally, using microarray data from multiple conditions and species, various comparative studies have been conducted so as to reveal transcriptional regulatory modules, predict gene functions, and uncover evolutionary mechanisms [ 32].
In order to investigate whether a drug has strong effect on the gene function module, we used hyper geometric test on drug sensitivity module with the identified breast cancer prognostic associated gene module.
We evaluated the coherence of each regulatory module from two aspects: 1) Pearson correlation coefficient of expression values of genes in the module; and 2) GO gene function enrichment.
Because distinct modules reveal distinct transcriptional, gene function and genomic signatures, we were interested in investigating module-specific regulatory relationships.
constructed an Arabidopsis gene-expression network and identified many functional modules associated with photosynthesis, protein biosynthesis, cell cycle, defense response and others, and these modules revealed new insights into gene function organization.
We performed a functional enrichment to discover the dominant gene function in different modules.
The modules guided discoveries toward understanding gene function in several areas of study: gene expression throughout the life cycle or in response to different stresses, localization of encoded proteins, in silico analyses of DNA and protein sequences, and analysis of gene knockout phenotypes.
