plot_pathway_cor {KEGGprofile} | R Documentation |
The function will plot the correlation distributions for each enriched pathway (result from find_enriched_pathway function), and then Wilcoxon tests would be used to estimate the significance of correlations distribution between genes in each pathway and all genes.
plot_pathway_cor(gene_expr, kegg_enriched_pathway, groups = NULL, side = c("both", "pos", "neg"), alternative = NULL)
gene_expr |
the matrix for gene expression, row.names should be NCBI gene ID, such as 67040, 93683 |
kegg_enriched_pathway |
The returned value from find_enriched_pathway function, the enriched pathways. |
groups |
a character used to indicate expression values from different types of samples |
side |
a character string specifying the correlation directions interested, must be one of "both" (default), "pos" or "neg". |
alternative |
a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter. |
p values for Wilcoxon tests in each pathway
data(pro_pho_expr) data(pho_sites_count) genes<-row.names(pho_sites_count)[which(pho_sites_count>=10)] pho_KEGGresult<-find_enriched_pathway(genes,species='hsa') result<-plot_pathway_cor(gene_expr=pro_pho_expr,kegg_enriched_pathway=pho_KEGGresult)