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OLIN (version 1.50.0)

sigint.plot: Visualisation of significance of intensity-dependent bias

Description

This function visualises the significance of intensity-dependent bias.

Usage

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

Arguments

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

Details

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.

See Also

sigxy.plot, fdr.int, p.int

Examples

Run this code

# 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))


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