maImage {marrayPlots} | R Documentation |
The function maImage
creates spatial images of shades of gray or colors that correspond to the values of a statistic for each spot on the array. The statistic can be the intensity log-ratio M, a spot quality measure (e.g. spot size or shape), or a test statistic. This function can be used to explore whether there are any spatial effects in the data, for example, print-tip or cover-slip effects.
maImage(m, x="maM", subset=TRUE, col, contours=FALSE, bar=TRUE, ...)
m |
Microarray object of class "marrayRaw" , "marrayNorm" , or "marrayTwo" . |
x |
Name of accessor function for the spot statistic of interest, typically a slot name for the microarray object m , such as maM . |
subset |
A "logical" or "numeric" vector indicating the subset of spots to display on the image. |
col |
List of colors such as that generated by rainbow , heat.colors , topo.colors , terrain.colors , or similar functions. In addition to these color palette functions, a new function maPalette was defined to generate color palettes from user supplied low, middle, and high color values. |
contours |
If contours=TRUE , contours are plotted, otherwise they are not shown. |
bar |
If bar=TRUE , a calibration color bar is shown to the right of the image. |
... |
Optional graphical parameters, see par . |
This function calls the general function maImage.func
, which is not specific to microarray data. If there are more than one array in the batch, the plot is done for the first array, by default. Default color palettes were set for different types of spot statistics using the maPalette
function. When x=c("maM", "maMloc", "maMscale")
, a green-to-red color palette is used. When x=c("maGb", "maGf", "maLG")
, a white-to-green color palette is used. When x=c("maRb", "maRf", "maLR")
, a white-to-red color palette is used. The user has the option to overwrite these parameters at any point.
A list with elements
x.col |
vector of colors to be used for calibration color bar. |
x.bar |
vector of values to be used for calibration color bar. |
summary |
six number summary of the spot statistics, from the function summary . |
Sandrine Dudoit, http://www.stat.berkeley.edu/~sandrine.
S. Dudoit and Y. H. Yang. (2002). Bioconductor R packages for exploratory analysis and normalization of cDNA microarray data. In G. Parmigiani, E. S. Garrett, R. A. Irizarry and S. L. Zeger, editors, The Analysis of Gene Expression Data: Methods and Software, Springer, New York.
image
, maImage.func
, maColorBar
, maPalette
, summary
.
# To see the demo type demo(marrayPlots) # Examples use swirl dataset, for description type ? swirl data(swirl) # Microarray color palettes Gcol <- maPalette(low = "white", high = "green", k = 50) Rcol <- maPalette(low = "white", high = "red", k = 50) RGcol <- maPalette(low = "green", high = "red", k = 50) # Color images of green and red background and foreground intensities maImage(swirl[, 3], x="maGb") maImage(swirl[, 3], x = "maGf", subset = TRUE, col = Gcol, contours = FALSE, bar = TRUE, main="Swirl array 93") maImage(swirl[, 3], x = "maRb", contour=TRUE) maImage(swirl[, 3], x = "maRf", bar=FALSE) # Color images of pre-normalization intensity log-ratios maImage(swirl[, 1]) maImage(swirl[, 3], x = "maM", subset = maTop(maM(swirl[, 3]), h = 0.1, l = 0.1), col = RGcol, contours = FALSE, bar = TRUE, main = "Swirl array 93: image of pre-normalization M for % 10 tails") # Color image of print-tip-group maImage(swirl[, 1],x="maPrintTip")