fdc {arrayMagic} | R Documentation |
Estimate the FDC (false discovery count) through permutations
fdc(x, fac, teststatfun = "rowFtests", nrperm = 100, nrgenesel = c(10, 20, 40, 60, 80, 100, 200), ...)
x |
Matrix. |
fac |
Factor, with length(fac)=ncol(x) . |
teststatfun |
Character. Name of a function that takes arguments
x and fac , and returns a list with component
statistic . See for example rowFtests . |
nrperm |
Numeric. Number of permutations. |
nrgenesel |
Numeric. A vector with the 'number of genes' for which the FDC is to be calculated. |
... |
Further arguments passed to code{teststatfun}. |
A list with elements
stat
: the test statistics;
mpstat
: median permuted test statistics;
fdc
: estimated false discovery counts;
thresh
: the threshholds associated with nrgenesel
;
nrgenesel
Wolfgang Huber <w.huber@dkfz.de>
## data matrix: 2000 genes, 16 samples x <- matrix(runif(2000*16), ncol=16) ## 8 blue and 8 red samples fac <- factor(c(rep("blue", 8), rep("red", 8))) ## implant differential signal into the first 50 genes x[1:50, fac=="blue"] <- x[1:50, fac=="blue"] + 1 res <- fdc(x, fac) plot(res$nrgenesel, res$fdc, pch=16, col="blue", xlab="Number of genes selected", ylab="Expected number of false discoveries") abline(a=0, b=1, col="red", lwd=2) qqplot(res$stat, res$mpstat, pch=".") abline(a=0, b=1, col="red", lwd=2)