plot_pathway_cor: plot_pathway_cor

In KEGGprofile: An annotation and visualization package for multi-types and multi-groups expression data in KEGG pathway

Description

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.

Usage

plot_pathway_cor(gene_expr, kegg_enriched_pathway, groups = NULL,
  side = c("both", "pos", "neg"), alternative = NULL)

Arguments

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.

Value

p values for Wilcoxon tests in each pathway

Examples

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)

Example output

KEGG.db contains mappings based on older data because the original
  resource was removed from the the public domain before the most
  recent update was produced. This package should now be considered
  deprecated and future versions of Bioconductor may not have it
  available.  Users who want more current data are encouraged to look
  at the KEGGREST or reactome.db packages

KEGGprofile documentation built on Nov. 8, 2020, 6:13 p.m.