plot_pathway

Share:

Description

A wrapper for function download_KEGGfile, parse_XMLfile and plot_profile

Usage

1
2
3
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

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
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")