sigint.plot: Visualisation of significance of intensity-dependent bias
In OLIN: Optimized local intensity-dependent normalisation of two-color microarrays

Description Usage Arguments Details Author(s) See Also Examples

This function visualises the significance of intensity-dependent bias.

1	sigint.plot(A,M,Sp,Sn,ylim=c(-3,-3),...)

`A`	vector of average logged spot intensity
`M`	vector of logged fold changes
`Sp`	vector of false discovery rate or p-values for positive deviation of median/mean of \code{M} as produced by `fdr.int` or `p.int`
`Sn`	vector of false discovery rate or p-values for negative deviation of median/mean of \code{M} as produced by `fdr.int` or `p.int`
`ylim`	vector of minimal log10(fdr) or log10(p-value) to be visualised corresponding to `Sp` and `Sn`. FDR or p-values smaller than these values will be set equal to these threshold values for visualisation.
`...`	Further optional graphical parameter for the `plot` function generating the MA plot

The function sigint.plot produces a MA-plot of the significance (Sp,Sn) generated by fdr.int or p.int. The abscissa (x-axis) is shows by the average logged spot intensity A=0.5*(log(Cy3)+log(Cy5)); the ordinate axis (y-axis) shows the log10(FDR) or log10(p) given by FDRp or Pn and FDRn or Pn. The significance for positive median/mean of \code{M} of spot intensity neighbourhoods are presented by red colour; the significance for negative median/mean of \code{M} of spot intensity neighbourhoods are presented by green colour. The ordinate axis (y-axis) give the log10-transformed FDR or p-values.

Matthias E. Futschik (http://itb.biologie.hu-berlin.de/~futschik)

sigxy.plot, fdr.int, p.int

# To run these examples, "un-comment" them!
#
# LOADING DATA NOT-NORMALISED
# data(sw)
# CALCULATION OF SIGNIFICANCE OF SPOT NEIGHBOURHOODS
# This can take a while! For testing, you may choose a smaller N.  
# FDR <- fdr.int(maA(sw)[,1],maM(sw)[,1],delta=50,N=100,av="median")
# VISUALISATION OF RESULTS
# sigint.plot(maA(sw)[,1],maM(sw)[,1],FDR$FDRp,FDR$FDRn,c(-5,-5))

# data(sw.olin)
# CALCULATION OF SIGNIFICANCE OF SPOT NEIGHBOURHOODS 
# F <- fdr.int(maA(sw.olin)[,1],maM(sw.olin)[,1],delta=50,N=100,av="median")
# VISUALISATION OF RESULTS
# sigint.plot(maA(sw.olin)[,1],maM(sw.olin)[,1],FDR$FDRp,FDR$FDRn,c(-5,-5))