inst/testScripts/system/chipTypes/Hs_PromPR_v02/21.MatSmoothing.R

In HenrikBengtsson/aroma.affymetrix: Analysis of Large Affymetrix Microarray Data Sets

###########################################################################
# Replication test
#
# Description:
# This test verifies that aroma.affymetrix can reproduce the estimates
# of the MAT (Model-based Analysis of Tiling arrays) algorithm.
#
# Author: Mark Robinson and Henrik Bengtsson
# Created: 2008-12-09
# Last modified: 2012-09-02
###########################################################################
library("aroma.affymetrix")
library("limma");  # makeContrast()
verbose <- Arguments$getVerbose(-20, timestamp=TRUE)


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Data set
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
dataSet <- "GSE24546"
tags <- "testset"
chipType <- "Hs_PromPR_v02"
sampleNamesMap <- c(
  GSM605951="Prec1_MeDNA_Input1",
  GSM605952="Prec1_MeDNA_IP2",
  GSM605953="Prec1_MeDNA_IP1"
)

cdf <- AffymetrixCdfFile$byChipType(chipType)
print(cdf)

csR <- AffymetrixCelSet$byName(dataSet, tags=tags, cdf=cdf)
print(csR)


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Normalize the data using the MAT model
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
mn <- MatNormalization(csR)
csM <- process(mn, verbose=more(verbose, 3))
print(csM)


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Convert data set such that it maps to the "unique" CDF
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
csU <- convertToUnique(csM, verbose=verbose)
print(csU)

# Rename
setFullNamesTranslator(csU, function(names, ...) { sampleNamesMap[names] })


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# MatSmoothing: Design #1
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
sampleNames <- getNames(csU)

design1 <- makeContrasts(Prec1_MeDNA_IP1-Prec1_MeDNA_Input1, levels=sampleNames)
colnames(design1) <- "Prec1_IP1_minus_Input"
print(design1)

ms1 <- MatSmoothing(csU, design=design1, probeWindow=600, tag="singleIP")
csMS1 <- process(ms1, units=NULL, verbose=verbose)
print(csMS1)


# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# MatSmoothing: Design #2
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
sampleNames <- getNames(csU)

design2 <- makeContrasts(Prec1_MeDNA_IP1 + Prec1_MeDNA_IP2-Prec1_MeDNA_Input1, levels=sampleNames)
colnames(design2) <- "Prec1_IPs_minus_Input"

ms2 <- MatSmoothing(csU, design=design2, probeWindow=800, tag="multipleIP")
csMS2 <- process(ms2, units=NULL,verbose=verbose)
print(csMS2)