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Evaluate the following code line-by-line. Some of the code pops up a graphics window, so if you run it all at once you will miss the earlier images. ## Now we want to look at the images of the chips. Basically, we are looking ## for something unusual here; one chip too bright for example. ## Construct image plots for quality control assessment ## Note: that these plots appear dark; they are not log transformed par(oma = c(1,1,3,1)) par(mfrow = c(2,3)) palette.gray <- c(rep(gray(0:10/10), times = seq(1,41, by = 4))) image(soy.ab[,1], transfo = function(x) x, col = palette.gray) image(soy.ab[,2], transfo = function(x) x, col = palette.gray) image(soy.ab[,3], transfo = function(x) x, col = palette.gray) image(soy.ab[,4], transfo = function(x) x, col = palette.gray) image(soy.ab[,5], transfo = function(x) x, col = palette.gray) image(soy.ab[,6], transfo = function(x) x, col = palette.gray) mtext ("> image(soy.ab[,i=1:6], transfo = function(x) x, col = palette.gray)", side = 3, outer = T, cex = .8) ## Construct individual image plots using log intensities ## Note: that these plots appear lighter; they are log transformed ## ## This allows us to see a single microarray chip. par(mfrow = c(1,1)) palette.gray <- c(rep(gray(0:10/10), times = seq(1,41, by = 4))) image(soy.ab[,1], col = palette.gray) title(sub = "> image(soy.ab[,1], col = palette.gray)") ## Repeat above commands with .. soy.ab[,i], i = 2-6 ## Display all six log-transformed image plots in one plot par(oma = c(3,1,3,1)) par(mfrow = c(2,3)) image(soy.ab[,1], col = palette.gray) image(soy.ab[,2], col = palette.gray) image(soy.ab[,3], col = palette.gray) image(soy.ab[,4], col = palette.gray) image(soy.ab[,5], col = palette.gray) image(soy.ab[,6], col = palette.gray) mtext("Image Plots - Hawaii/Resistant vs. Taiwan/Susceptible", side = 3, outer = T) mtext("Top Row: Hawaii/Resistant - Bottom Row: Taiwan/Susceptible", side = 1, outer = T) ## Reset to single screen. par(mfrow = c(1,1))(Complete File)(Rout) You can see the graphics here |
