Lab 2 - Analysis of Affymetrix Microarray Data
Contents
1. Multichip Averaging Irizarry et al 7 and PLM Probe level Linear Model fits 3 5 1 RMA Robust Multichip Averaging Normalize the Estrogen data using the rma function which will create an object of class exprSet In order to run rma on the Estrogen data you must either have the CDF Chip Definition File package hgu95av2cd installed or have reposToo1s installed and be connected to the Internet for automatic download of the CDF package by the rma function eset lt rma rawAffyData eset eset is an S4 object of class exprSet By typing the name of the object and pressing enter we are invoking the show method for objects of this class To see the R code for this show method you can type getMethod show exprSet To see R code for the show method when applied to other types of objects you can type getMethods show 3 5 2 Examining the effects of normalization using boxplots Before RMA normalization boxplot rawAffyData col red After RMA normalization boxplot data frame exprs eset col blue Note the considerable effect of normalization on this data set The intensity values in these boxplots have been transformed to a log2 scale To confirm this for yourself see getMethod boxplot AffyBatch and rma 3 5 3 PLM Probe level linear models Probe level Linear Models can be used as a more robust alternative to RMA normalization The provide a matrix of weights for2. each chip which can be used for another type of diagnostic image plot Officially the affyPLM package depends on the affydata package but it should not be required for the simple use of af fyP1m illustrated below Load the affyPL package and create an object of class PLMset using the fitPLM function library affyPLM pimset lt fitPLM rawAffyData plmset There is documentation available in the doc subdirectory of the affyPLM package To find this directory on your computer you can use system file doc package affyPLM from within R Alternatively you can read the latest version of the documentation on the Internet Bolstad 8 Now create image plots used to diagnose spatial artefacts for the first two chips and compare them with the image plots you obtained in section 3 3 1 image plmset 1 image plmset 2 If you are connected to the web you can have a look at Ben Bolstad s affyPLM image gallery browseURL http www stat berkeley edu bolstad PLMImageGallery 3 5 4 GCRMA Using DNA sequence information to improve RMA DNA sequences are made up of four bases nucleotides called A C G and T In double stranded DNA A is always opposite T and C is always opposite G Each G C pair has three hydrogen bonds between the G and the C whereas each A T pair has only two hydrogen bonds between the A and the T It is for this reason that biologists are interested in the GC content of certain ar
3. or microsatellite markers MAS 5 0 The main microarray analysis software from the Affymetrix company MicroArraySuite MAS now version 5 The same as PM but with a single homomericbase change for the middle 13th base transversionpurine lt gt pyrimidine G lt gt C A lt gt T The purpose of the MM probe design is to measure non specific binding and background Perfect A 25 mer complementary to a reference sequence of interest e g part match PM of a gene Mismatch MM The type of RNA in a biological sample as described by physical characteristics of the biological sample e g time or estrogen presence absence or observed susceptibility to disease Probar An i aeeoea 25 base pairs i e a 25 mer Probe pair pair A A PM MM pair MM pair Probe paiese A collection of probe pairs 16 to 20 related to a common gene or a freee of a Robust Matichip Averaging aa IRMA Robust Robust Multichip Averaging Irizarryetal 6 Averaging Irizarry et al 6 Target A type of RNA under a particular condition e g Estrogen present 8 which is hybridized to a microarray chip Phenotype
4. or affy1mcuI which chips are replicates By using the same Target name for the first two rows in the table we are telling limma or affy1mGur that these two CEL files represent replicatechips for the experimental condition Estrogen Absent Time 10 hours Note that we could use a different Targets file for this analysis in which the time effect was ignored if we only wanted to compare Estrogen Absent and Estrogen Present This would simply require removing the 10 s and 48 s from the Target column There is actually a file called phenoData txt supplied within the est rogen package which could be used as a Targets file but in this exercise you should use the format above or download EstrogenTargets txt from http bioinf wehi edu au marray ibc2004 lab2 EstrogenTargets txt This way is simpler because we describe the type of RNA target in just one column Target rather than in two columns estrogen and time h 3 Analyzing the data in R 3 1 Loading the affy package and finding the Estrogen data Firstly load the affy package which automatically loads Biobase and set your working directory to the data subdirectory of the est rogen package library affy setwd system file data package estrogen dir getwd There is documentation available in the doc subdirectory of the affy package To find this directory on your computer you can use system file doc package affy from within R Alternatively you can
5. read the latest version of the documentation on the Internet Gautier et al 3 3 2 Preparing the RNA Targets file If you are connected to the Internet you can download the Estrogen targets file using the download file function below If you are not connected to the Internet and you do not have the file already you can create it in Excel from the table in section 2 and save it as tab delimited text in the directory given by getwd above If you have ignored the advice in Section 2 and installed the est rogen package in a directory where you don t have write permission you will need to store Est rogenTargets txt somewhere else download file http bioinf wehi edu au marray ibc2004 lab2 EstrogenTar gets txt EstrogenTargets txt 3 3 Reading the targets file and the CEL files into R pd lt read phenoData EstrogenTargets txt header TRUE row names 1 as is TRUE rawAffyData lt ReadAffy filenames pData pd FileName phenoData pd rawAffyData lt rawAffyData is an S4 object of class AffyBatch By typing the name of the object and pressing enter we are invoking the show method for objects of this class To see the R code for this show method you can type getMethod show AffyBatch To see R code for the show method when applied to other types of objects you can type getMethods show 3 4 Diagnostic plots 3 4 1 Image plots We can check the quality of the arrays using image p
6. Lab 2 Analysis of Affymetrix Microarray Data James Wettenhall Created June 25 2004 Updated July 2 2004 Contents 1 Software required for this lab 1 Required R packages 2 Recommended R packages 3 Required data files 2 Estrogen data set 3 Analyzing the data in R 1 Loading the affy package and finding the Estrogen data 2 Preparing the RNA Targets file 3 Reading the targets file and the CEL files into R 4 Diagnostic plots 1 Image plots 2 Histograms 3 MA plots using raw unnormalized data 5 Normalization 1 RMA Robust Multichip Averaging 2 Examining the effects of normalization using boxplots 3 PLM Probe level linear models 4 GCRMA Using DNA sequence information to improve RMA 6 More diagnostic plots 1 MA plots using normalized data 7 Saving your R workspace Memory Troubles Acknowledgements References Glossary aoe 1 Software required for this lab You will need R 1 9 0 or later http www R Project org for this lab exercise This section lists all of the R packages you need to have installed and also lists some additional R packages which are recommended Note that most of the R packages can be installed from the Bioconductor site automatically using source http www bioconductor org getBioC R getBioc 1 1 Required R packages It is highly desirable to have these R packages in a directory in which you have write permission esp
7. an 512 Megabytes of RAM you will not be able to do any probe level analysis i e anything which involves rawAffyData on the full set of 8 chips but you can use the function justRMA from the affy package to read in your data from CEL files and then normalize it without creating a rawAffyData object of class AffyBatch Alternatively you can try reading in only a subset of the arrays but you will need to have some replicate arrays for Lab 3 i e for Lab 3 you can t just use arrays 1 3 5 and 7 If you experience memory errors please restart your R session before trying a less memory expensive alternative The following function just RMA should read in all 8 arrays normalize them and create an object of class exprSet with as little as 128 Megabytes of RAM library affy setwd system file data package estrogen pd lt read phenoData EstrogenTargets txt header TRUE row names 1 as is TRUE eset lt justRMA filenames pData pd SFileName phenoData pd eset lt Or to read in only the first four arrays you can use eset lt justRMA filenames pData pd S SFileName 1 4 phenoData pd eset 5 Acknowledgements Thanks to Scholtens et al 1 for providing the Estrogen data on the Bioconductor site http www bioconductor org data experimental html Thanks also to Robert Gentleman and Wolfgang Huber for the vignette in the estrogen package which this lab was based on Thanks also to Sandrin
8. arisons we will ignore the replicate chips 2 4 6 and 8 and just use 1 3 5 and 7 We will use the PM Perfect Match probes to calculate log ratios M and log intensities A The function mva pairs in the affy package can be used for M versus A plots where M is a log ratio in base 2 and A is an average log intensity in base 2 mva pairs pm rawAffyData c 1 3 5 7 It is clear from these plots that there is a significant time effect i e each M A plot comparing time 10 hours with time 48 hours is not centred at M 0 The reader should be aware that the normalization will remove this effect because normalization generally assumes that the majority of genes are not differentially expressed The experimenters felt that there was no possible biological reason why EVERY gene on the chip would be expressed so differently at the later time 48 hours and that it must be an artefact due to the microarray technology Therefore there it seems reasonable to use the traditional normalization methods 3 5 Normalization There are several normalization methods available for Affymetrix data For a detailed comparison see Bolstad et al 4 MAS 5 0 5 is a method distributed in the MicroArray Suite version 5 0 by Affymetrix This method is available in the affy package for R but may give slightly different results from the Affymetrix software Bolstad 6 We will not use MAS 5 0 in this lab exercise Instead we will use RMA Robust
9. e Dudoit Robert Gentleman Rafael Irizarry and Yee Hwa Yang for the DNA Microarray Data and Oligonucleotide Arrays talk slides from the Bioconductor Short Course at DSC 2003 in Vienna http www bioconductor org workshops Vienna03 These talk slides were used to create the glossary below 6 References 1 Scholtens D Miron A Merchant FM Miller A Miron PL Iglehart JD Gentleman R Analyzing Factorial Designed Microarray Experiments Journal of Multivariate Analysis To appear 2 Scholtens D Gentleman R Estrogen 2x2 Factorial Design http www bioconductor org repository devel vignette factDesign pdf 3 Gautier L Irizarry R Cope L and Bolstad B Description of Affy http www bioconductor org repository devel vignette affy pdf 4 Bolstad B M Irizarry R A Astrand M and Speed T P A comparison of normalization methods for high density oligonucleotide array data based on variance and bias Bioinformatics 19 185 2003 5 The MAS 5 0 User Manual http www affymetrix com Auth support downloads manuals mas_manual zip 6 Bolstad B Why do my MAS 5 0 values differ http stat www berkeley edu bolstad MASS5diff MasS5difference html 7 Irizarry R A Hobbs B Collin F Beazer Barclay Y D Antonellis K J Scherf U and Speed T P 2003 Exploration normalization and summaries of high density oligonucleotide array probe level data Biostatistics 4 249 264 4 2003 8 Bolstad B aff
10. eas of the genome RNA is single stranded and is generally created by transcribing copying DNA with the only difference in sequence being that T is replaced by U In microarray hybridizations the probes printed on the chip are single stranded cDNA reverse transcribed from RNA but the target RNA contains the bases A C G and U rather than A C G and T so it is possible to get both A T pairs and A U pairs in the hybridizations The A U pairs have the same properties as the A T pairs in double stranded DNA i e only two hydrogen bonds so the idea of GC content is just as relevant to microarray hybridizations as it is to double stranded DNA molecules The gcrma package takes GC content into account when doing RMA normalization The gcrma package requires the mat chprobes package and a probes package for the Affymetrix chip being used In this case the probes package required is hgu95av2probes Load the gcrma package and normalize the data in the same way as you did with RMA library gcrma esetGCRMA lt gcrma rawAffyData esetGCRMA There is documentation available in the doc subdirectory of the gcrma package To find this directory on your computer you can use system file doc package gcrma from within R Alternatively you can read the latest version of the documentation on the Internet Wu and Irizarry 9 3 6 More diagnostic plots 3 6 1 M A Plots using normalized data After creating an expression set object ese
11. ecially for the est rogen package You can use libPaths C Custom R library directory or LibPaths C Custom R library directory before you run install packages or equivalent to install the package s in a customized directory location Package affy TA sa www bioconductor o 4 package html affy htm www bioconductor org repository release1 4 package html Biobase Biobase ee SE http www bioconductor org data experimental html nttp www bioconductor org data experimentaLhtml s bioconductor org data experimental html Ihgu9Sav2cdf av2cdf http www bioconductor Ihttp www bioconductor org data metaDatahtml is html affyPLM http www bioconductor org repository release1 4 package html affyPL M html http www bioconductor org repository release1 4 package html affydata affydata html gcrma a www bioconductor org repository release1 4 package html gcrma h htt ey bioconductor org repository release1 4 package html matchpr matchprobes obes html oa http www bioconductor org data metaData html 1 2 Recommended R packages Package URL hgu95av2__ http www bioconductor org data metaData html bioconductor org repository release1 4 package html reposTools reposTools i www bioconductor org repository release1 4 package html widgetTool s html DynDoc www bioconductor org repository release1 4 package html DynDoc ht hu Ti bioco
12. lots and histograms of the log intensities Firstly let s look at images of the first two arrays image rawAffyData 1 image rawAffyData 2 No spatial artefacts are apparent in the first two estrogen arrays but we do have an example of a CEL file with a bad spatial artefact badcel lt ReadAffy file bad cel file is short for filenames image badcel To see the R code for the image method for objects of class Af fyBatch use getMethod image AffyBatch 3 4 2 Histograms Another diagnostic plot which may be useful is a histogram of the PM Perfect Match log intensities or the MM MisMatch log intensities The R commands below each plot a histogram of log2 intensities for the first Estrogen microarray chip The first command includes only the PM probes in the histogram whereas the second command includes only the MM probes hist log2 pm rawAffyData 1 breaks 100 col blue hist log2 mm rawAffyData 1 breaks 100 col blue 3 4 3 M A Plots using raw unnormalized data In Lab 1 M A plots were used to compare the two channels on each array red and green whereas for Affymetrix chips there is only one channel on each array so the only meaningful way to define M the log ratio is to compare different chips We have 8 chips so there are C 28 possible comparisons which is quite a lot considering that we are dealing with probe level data Instead of making all possible comp
13. nductor org repository release1 4 package html tkWidgets tkWidgets 1 3 Required data files The Estrogen data set is listed in the Required R packages section There is one additional file which you should obtain Est rogenTargets txt Data URL EstrogenTargets txt http bioinf wehi edu au marray ibc2004 lab2 EstrogenTargets txt 2 Estrogen data set For this lab we will use data from a set of eight Affymetrix chips from a 2x2 factorial design experiment designed to measure changes in gene expression in a breast cancer cell line due to the presence or absence of estrogen and due to a time effect 10 hours or 48 hours The experiment was performed by Scholtens et al 1 who have kindly provided their data for public access on the Bioconductor website http www bioconductor org data experimental html The Estrogen data is stored in the data subdirectory of an R package called estrogen which is listed on this website It can be installed like any other R package then the data can be found from within R in the directory system file data package estrogen This data set is described in detail in the Estrogen 2x2 Factorial Design vignette by Denise Scholtens and Robert Gentleman 2 The following description of the experiment is taken from that vignette Experimental Data The investigators in this experiment were interested in the effect of estrogen on the genes in ER breast cancer cells over time Af
14. t in Section 3 5 1 you can now replot the M A plots from Section 3 4 3 this time using normalized expression values These plots will appear more quickly because they don t require probe level data For the sake of comparison with Section 3 4 3 we will again only use chips 1 3 5 and 7 The function mva pairs in the affy package can be used for M versus A plots where M is a log ratio in base 2 and A is an average log intensity in base 2 mva pairs exprs eset c 1 3 5 7 log it FALSE lt As described in Section 3 4 3 the normalization removes a time effect in this case but the experimenters felt certain that there was no possible biological effect which can change the expression level of EVERY gene so dramatically It is therefore reasonable to assume that this effect is due to different calibrations of the microarray technology and should therefore be removed by normalization The reason that we specify log it FALSE in mva pairs is that the expression measurements in eset have already been log transformed See the help for rma using rma 3 7 Saving your R workspace Please save your R workspace with save image estrogen RData so that you can use the exprset object s you have created in Lab 3 4 Memory Troubles Most of the exercises in this lab can be done with 512 Megabytes of RAM except for affyPIM Section 3 5 3 and gcrma Section 3 5 4 which require 1 Gigabyte of RAM If you have less th
15. ter serum starvation of all eight samples they exposed four samples to estrogen and then measured mRNA transcript abundance after 10 hours for two samples and 48 hours for the other two They left the remaining four samples untreated and measured mRNA transcript abundance at 10 hours for two samples and 48 hours for the other two Since there are two factors in this experiment estrogen and time each at two levels present or absent 10 hours or 48 hours this experiment is said to have a 2x2 factorial design The table below describes the experimental conditions for each of the eight arrays When stored as tab delimited text this is known as the RNA Targets file Name FileName Target Abs10 1 low10 1 cel EstAbsent10 Abs 10 2 low10 2 cel EstAbsent10 Pres10 1 high10 1 cel EstPresent10 Pres10 2 high10 2 cel EstPresent10 Abs48 1 low48 1 cel EstAbsent48 Abs48 2 low48 2 cel EstAbsent48 Pres48 1 high48 1 cel EstPresent48 Pres48 2 high48 2 cel EstPresent48 The file shown as a table above is known as the RNA Targets file in 1imma or in affy1mGut It should be stored in tab delimited text format and it can be created either in a spreadsheet program such as Excel or in a text editor The column headings must appear exactly as above Each chip should be given a unique name or number in the Name column The Affymetrix CEL file name should be listed for each chip in in the FileName column The Target column tells 1imma
16. yPLM Methods for fitting probe level models to Affy data http www bioconductor org repository devel vignette affyPLM pdf 9 Wu A Irizarry R Description of germa http www bioconductor org repository devel vignette gcrma pdf These documents are also available within the doc subdirectory of these R packages which can be found from within R using system file doc package affy system file doc package affyPLM system file doc package gcrma 7 Glossary Term Definition AffyID An identifier for a lAn identifier for a probe pair set sstsi lt sS pair set Affymetrix The largest company which manufactures single channel high density oligonucleotide microarray chips Chip Description File Describes which probes go in which probe sets CDF file and the location of probe pair sets genes gene fragments ESTs See a Call meris Me inchine probe level PMT and MMC valacs www bioconductor org metaData html CEL fie file Cell intensity file Cell intensity file including probe level PM and MM values probe level PM and MM values Cell line Cells grown in tissue culture representing generations of a primary culture DAT DAT file Image file Image file approximately 1047 pixels approximately 50 MB 10 7 pixels approximately 50 MB The type of RNA in a biological sample as described by the DNA Genotype sequence e g using Single Nucleotide Polymorphisms SNPs
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