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### R code from vignette source 'LPEadj.Rnw'
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### code chunk number 1: LPEadj.Rnw:259-266
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# Loading the library and null dataset (two groups with three
# replicates each).
library(LPEadj)
dat <- matrix(rnorm(6000), ncol=6)
# Applying LPE
lpe.result <- lpeAdj(dat, labels=c(0,0,0,1,1,1), doMax=FALSE, doAdj=TRUE)
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### code chunk number 2: LPEadj.Rnw:275-294
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# Loading the library and null dataset (two groups with three
# replicates each)
library(LPEadj)
dat <- matrix(rnorm(6000), ncol=6)
ADJ.VALUES <- c(1, 1, 1.34585905516761 ,1.19363228146169 ,1.436849413109
,1.289652132873 ,1.47658053092781 ,1.34382984852146
,1.49972130857404, 1.3835405678718)
# calculate base line error distributions
var1 <- adjBaseOlig.error(dat[,1:3], setMax1=FALSE, q=.05)
var2 <- adjBaseOlig.error(dat[,4:6], setMax1=FALSE, q=.05)
# The correct variance adjustments can be fetched using the replicate
# number for each group as in index for the ADJ.VALUES vector.
# eg: ADJ.VALUES[n] if there are n replicates in a group
results <- calculateLpeAdj(dat[,1:3],dat[,4:6],var1,var2,
probe.set.name=c(1:1000), adjust1=ADJ.VALUES[3],
adjust2=ADJ.VALUES[3])
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