plot_pathway: plot_pathway

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

Description

A wrapper for function download_KEGGfile, parse_XMLfile and plot_profile

Usage

plot_pathway(gene_expr, line_col, groups, pathway_id = "00010",
  species = "hsa", pathway_min = 5, database_dir = getwd(),
  speciesRefMap = TRUE, ...)

Arguments

gene_expr	the matrix for gene expression, row.names should be NCBI gene ID, such as 67040, 93683
line_col	line color for expression in different samples in the pathway map, valid when type='lines'
groups	a character used to indicate expression values from different types of samples
pathway_id	the KEGG pathway id, such as '00010'
species	the species id in KEGG database, 'hsa' means human, 'mmu' means mouse, 'rno' means rat, etc
pathway_min	The pathways with number of annotated genes less than pathway_min would be ignored
database_dir	the directory where the XML files and png files are located
speciesRefMap	Logical, use the species specific figure as reference map. if set as FALSE, the reference pathway figure without species information will be used
...	any other Arguments for function plot_profile

Details

This wrapper function is developed to make the visualization process more easier. Firstly the existence of XML file and png file would be checked, if not, the download_KEGGfile function would be used to download the files. Then the parse_XMLfile function would be used to parse the XML file. At last the plot_profile function would be used to generate the pathway map.

See Also

download_KEGGfile, parse_XMLfile, plot_profile

Examples

data(pro_pho_expr)
data(pho_sites_count)
#type='lines'
col<-col_by_value(pho_sites_count,col=colorRampPalette(c('white','khaki2'))(4),
breaks=c(0,1,4,10,Inf))
temp<-plot_pathway(pro_pho_expr,bg_col=col,line_col=c("brown1","seagreen3"),
groups=c(rep("Proteome ",6),rep("Phosphoproteome ",6)),magnify=1.2,species='hsa',
database_dir=system.file("extdata",package="KEGGprofile"),pathway_id="04110",max_dist=5)
#type='bg'
pho_expr<-pro_pho_expr[,7:12]
temp<-apply(pho_expr,1,function(x) length(which(is.na(x))))
pho_expr<-pho_expr[which(temp==0),]
col<-col_by_value(pho_expr,col=colorRampPalette(c('green','black','red'))(1024),range=c(-6,6))
temp<-plot_pathway(pho_expr,type="bg",bg_col=col,text_col="white",magnify=1.2,species='hsa',
database_dir=system.file("extdata",package="KEGGprofile"),pathway_id="04110")
#Compound and gene data
set.seed(124)
testData1<-rbind(rnorm(6),rnorm(6),rnorm(6),rnorm(6),rnorm(6),rnorm(6),rnorm(6),rnorm(6))
row.names(testData1)<-c("4967","55753","1743","8802","47","50","cpd:C15972","cpd:C16255")
colnames(testData1)<-c("Control0","Control2","Control5","Sample0","Sample2","Sample5")
temp<-plot_pathway(testData1,type="lines",line_col=c("brown1","seagreen3"),
groups=c(rep("Control",3),rep("Sample",3)),magnify=1.2,species='hsa',
database_dir=system.file("extdata",package="KEGGprofile"),pathway_id="00020",max_dist=2)
testData2<-testData1[,4:6]-testData1[,1:3]
col<-col_by_value(testData2,col=colorRampPalette(c('green','black','red'))(1024),range=c(-2,2))
temp<-plot_pathway(testData2,type="bg",bg_col=col,text_col="white",magnify=1.2,species='hsa',
database_dir=system.file("extdata",package="KEGGprofile"),pathway_id="00020")

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