plot_profile: plot_profile

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

Description

The function plot gene expression profiles on KEGG pathway maps

Usage

plot_profile(gene_expr, pathway_name, result_name = paste(pathway_name,
  "_profile_", type, ".png", sep = ""), KEGG_database, groups,
  bg_col = "white", text_col = "black", line_col,
  border_col = "grey", text_cex = 0.25, magnify = 1,
  type = c("lines", "bg"), pathway_min = 5,
  genes_kept = c("foldchange", "first", "random", "var", "abs"),
  species = "hsa", database_dir = getwd(), max_dist, lwd = 1.2,
  speciesRefMap = TRUE)

Arguments

gene_expr	the matrix for gene expression, row.names should be NCBI gene ID, such as 67040, 93683
pathway_name	the species id and KEGG pathway id, such as 'hsa00010'
result_name	the name of figure file generated by KEGGprofile. The default name is pathway_name+'_profile_'+type+'.png', such as 'hsa04110_profile_lines.png'
KEGG_database	the matrix returned by function parse_XMLfile, which contains genes in this pathway, and their names, locations etc
groups	a character used to indicate expression values from different types of samples
bg_col	background color for gene rectangles in the pathway map
text_col	the colors for text in the pathway map. A color matrix generated by function col_by_value can be used here
line_col	line color for expression in different samples in the pathway map, valid when type='lines'
border_col	border color for gene rectangles in the pathway map. A color matrix generated by function col_by_value can be used here
text_cex	cex for text in the pathway map. A color matrix generated by function col_by_value can be used here
magnify	the coefficient used to magnify the gene rectangles
type	the type of pathway map visulization, could be 'bg' or 'lines'. Default is 'bg'. See also 'Details'
pathway_min	The pathways with number of annotated genes less than pathway_min would be ignored
genes_kept	methods used for choosing genes when several genes corresponding to one location in pathway map. Default is 'foldchange', which kept the gene with largest fold changes. 'first' kept the first gene. 'random' chosed gene random. 'var' kept the gene with largest variation. 'abs' kept the gene with largest absolute value
species	the species id in KEGG database, 'hsa' means human, 'mmu' means mouse, 'rno' means rat, etc
database_dir	the directory where the XML files and png files are located
max_dist	The expression changes that represented by the distance from the bottom to the top of gene rectangle, valid when type='lines'. This param is used to ensure the dynamic changes of lines in different gene polygon represent equal variation. It would be calculated from the maximum changes of genes in this pathway by default. If max_dist=NA, then the lines would be plotted from top to bottom in each gene rectangle
lwd	The line width when type='lines'
speciesRefMap	Logical, use the species specific figure as reference map. if set as FALSE, the reference pathway figure without species information will be used

Details

There are two visualization methods to represent gene expression profiles: 'background' and 'lines'. The first one is applicable for analysis with only one sample or one type of data, which divides the gene polygon into several sub-polygons to represent different time points. And each sub-polygon has a specific background color to represent expression changes in that time point. The second method plots lines with different colors in the gene polygon to represent different samples or different types of data. The dynamic changes of lines mean the profiles of genes in different time points.

Value

a matrix containing genes maped in this pathway, and their names, expressions

Examples

XML2database<-parse_XMLfile(pathway_id="04110",species="hsa",
database_dir=system.file("extdata",package="KEGGprofile"))
data(pro_pho_expr)
temp<-plot_profile(pro_pho_expr,pathway_name="hsa04110",KEGG_database=XML2database,
line_col=c("brown1","seagreen3"),groups=c(rep("Proteome ",6),rep("Phosphoproteome ",6)),
magnify=1.2,database_dir=system.file("extdata",package="KEGGprofile"),max_dist=5)

slzhao/KEGGprofile documentation built on Oct. 27, 2020, 4:29 a.m.