plotCorrelations: Radarchart visualization of correlations between samples and...

In cit-bioinfo/consensusMIBC: Transcriptomic predictor of muscle-invasive bladder cancer consensus subtypes

Description

Plot function using radarcharts to visualize global correlation profiles between samples and consensus classes

Usage

plotCorrelations(xres, col.samp = "#1414BE", col.med = "red",
  axistype = 2, seg = 4, pty = 32, plty = 1, plwd = 2,
  cglty = 1, cglwd = 0.5, cglcol = "grey80", centerzero = T, ...)

Arguments

xres	The results returned by getConsensusClass, either the full dataset or a subset of rows.
col.samp	Color used to plot sample correlation profiles
col.med	Color used to plot the median correlation profile by consensus class
axistype	see radarchart documentation
seg	see radarchart documentation
pty	see radarchart documentation
plty	see radarchart documentation
plwd	see radarchart documentation
cglty	see radarchart documentation
cglwd	see radarchart documentation
cglcol	see radarchart documentation
centerzero	see radarchart documentation
...	further arguments passed to radarchart

Value

Plot a single radar chart for a single sample result. If multiple sample results are used, sample profiles are grouped by consensus class prediction on 6 radar charts, also showing the median profile by consensus class.

Author(s)

Gordon Robertson and Aurelie Kamoun

See Also

radarchart

Examples

  data(tcgadat)
  xres <- getConsensusClass(tcga.dat)
  
  #-- Example for a single sample plot, return a single radarchart
  plotCorrelations(xres[1, ]) 
  
  #-- Example for multiple samples, returns one radarchart per consensus class
  plotCorrelations(xres) 

cit-bioinfo/consensusMIBC documentation built on Aug. 10, 2019, 1:22 p.m.