R/scaleColorBar.R

In ABarray: Microarray QA and statistical data analysis for Applied Biosystems Genome Survey Microrarray (AB1700) gene expression data.

#- $Id: scaleColorBar.R,v 1.1.1.1 2006/06/06 22:06:37 sunya Exp $

#- Scale bar heatmap for matrixplot.

"scaleColorBar" <-
function (x, horizontal = FALSE, col = rgcolorsfunc(50), scale = 1:length(x), 
          k = 10, cLen = 9, ...) 
{
  x <- unique(sort(as.vector(x)))
  scale <- 1:length(x)	

  if (is.numeric(x)) {
		  #- Let's use just a sequence from min to max, not just real value of x
    x <- seq(min(x), max(x), (max(x) - min(x)) / length(x))
    colmap <- col
  }
  else {
    colmap <- x
    low <- range(scale)[1]
    high <- range(scale)[2]
    x <- seq(low, high, length = length(x))
  }
  
  if (length(x) > k) 
    x.small <- seq(x[1], x[length(x)], length = k)
  else x.small <- x

	 #- Create appropriate margins
  par(mar = c(2, 1, cLen, 5))
  
  if (horizontal) {
    image(x, 1, matrix(x, length(x), 1), axes = FALSE, xlab = "", 
          ylab = "", col = colmap, ...)
    axis(1, at = rev(x.small), labels = signif(rev(x.small), 
                                 2), srt = 270)
  }
  if (!horizontal) {
    image(1, x, matrix(x, 1, length(x)), axes = FALSE, xlab = "", 
          ylab = "", col = colmap, ...)
    par(las = 1)
        #axis(2, at = rev(x.small), labels = signif(rev(x.small), 2))
    axis(4, at = rev(x.small), labels = signif(rev(x.small), 3))
    par(las = 0)
  }
  box()
}

##############################################
#- $Log: scaleColorBar.R,v $
#- Revision 1.1.1.1  2006/06/06 22:06:37  sunya
#- ABarray project converted from ab1700 project
#-
#- Revision 1.2  2006/03/14 19:48:31  sunya
#- Changed icp (internal control probe) QC plots.
#- Added function for icp -> icpPlot
#- ANOVA analysis now performs probe filtering, but no FDR is calculated.
#- hclusterPlot now calculate correlation coefficient for probes, previously
#- it used Euclidian distance. The distance between arrays is still Euclidean.
#-