MvsA.cpd {compdiagTools} | R Documentation |
Uses hexbin to draw rank-vs-residuals plots with loess and running median average deviation.
MvsA.cpd(a.x, a.y, call = "", filename = NULL, sample.size = 10000, win.size = 1000, win.step = trunc(length(a.x)/50), ...)
a.x |
values of considered chip. |
a.y |
values of reference chip, e.g. median over all chips. |
call |
whether the data is from normalization of summary. |
filename |
writes a bitmap/pdf if this argument is
specified. The filename is completed with a file extension according
to the type required and a postfix according to call . |
sample.size |
How many points are sampled for running MAD |
win.size |
how large is the average window for running MAD |
win.step |
step size for running MAD |
... |
further argument passed to 'bitmap' |
Uses hexbin to draw a density plot rather than a scatter plot. We expect equally distributed residuals for good quality chips. Therefore, the blue dots representing median average deviation from residuals of a running window should be located on a horizontal line. The read line represents a loess fit and whould be close to zero for the whole x-range.
Use the additional argument type="pdfwrite" to generate PDF.
Stefan Bentink
library(vsn) library(golubEsets) data(golubTest) expr.mat <- exprs(vsn(golubTest, describe.preprocessing=FALSE)) expr.med <- apply(expr.mat, 1, median) MvsA.cpd(expr.mat[,1], expr.med)