Identifying clinically significant modules

Two approaches were used to identify a correlation between modules and clinical information obtained from patients with GC. Analyses were performed using the WGCNA v1.68 and Cor packages in R 3.5.2 (https://cran.rstudio.com/). The minimum number of genes per module was 30, the correlation threshold of hub genes was 0.90 and the unsigned network edge threshold was 0.05. Firstly, the expression profiles of a gene in all samples and of a vector gene were calculated using Pearson's correlation as module membership (MM). ME was defined as the first principal component of each gene module and the expression of ME was considered representative of all genes in a given module. Clinically significant modules were identified by calculating the correlation between ME and clinical traits, and the degree of the connection was measured. Gene significance (GS) was used to measure this degree; a higher GS indicated increased biological significance of genes. MS were defined as the mean GS of all the genes involved in the module.