OLIN (version 1.50.0)

p.int2: Calculates significance of intensity-dependent bias

Description

This function assesses the significance of intensity-dependent bias. This is achieved by comparing the observed average values of logged fold-changes within an intensity neighbourhood with an empirical distribution generated by permutation tests. The significance is given by (adjusted) p-values.

Usage

p.int2(object,delta=50,N=-1,av="median",p.adjust.method="none")

Arguments

object

object of class marrayRaw or marrayNorm

delta

integer determining the size of the neighbourhood (2 * delta+1).

N

number of random samples (of size 2 * delta+1) used for the generation of empirical distribution. If N is negative, the number of samples 100 times the length of A.

av

averaging of M within neighbourhood by mean or median (default)

p.adjust.method

method for adjusting p-values due to multiple testing regime. The available methods are “none”, “bonferroni”, “holm”, “hochberg”, “hommel” and “fdr”. See also p.adjust

Details

This function p.int2 is basically the same as p.int except for differences in their in- and output format. For the details about the functionality, see p.int.

See Also

p.int,fdr.int2, sigint.plot2, p.adjust

Examples

# To run these examples, "un-comment" them!
#
# LOADING DATA NOT-NORMALISED
# data(sw)
# CALCULATION OF SIGNIFICANCE OF SPOT NEIGHBOURHOODS
#  For this illustration, N was chosen rather small. For "real" analysis, it should be larger.
# P <- p.int2(sw,delta=50,N=10000,av="median",p.adjust.method="none")
# VISUALISATION OF RESULTS
# sigint.plot2(sw[,1],Sp=P$Pp[[1]],Sn=P$Pn[[1]],c(-5,-5)) # array 1
# sigint.plot2(sw[,3],Sp=P$Pp[[3]],Sn=P$Pn[[3]],c(-5,-5)) # array 3