[maNorm] Normalization a complex experiment...
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@marcelo-luiz-de-laia-377
Last seen 8.6 years ago
Hi All, I have a complex experiment (for me) and I do not known how do I do to normalize it. More specifically, I don't know as building the file samples (targets) for marray. The design is: Time 1day 2day 3day Rep1 Rep1 Rep1 Un Treated Rep2 Rep2 Rep2 Rep3 Rep3 Rep3 Rep1 Rep1 Rep1 Un Treated Rep2 Rep2 Rep2 Rep3 Rep3 Rep3 If I have one time, my targets file for marrayinput is like this: # of slide Names experiment Cy3 experiment Cy5 date 1 File1 Un Treated Treated 19/01/2004 It is a temporary series with three different times and three repetitions in each one of the times. Me already analysed some simpler experiments. For example, I know to analyse inside of every time, individually. However, I didn't get to find an example alike to mine in the marray vignettes. After the normalization, I am thinking about using limma. I would like to know which genes were differentialy expressed in every time. Besides, would I like to verify the behavior of these genes along the time (for example, were they increased or done decreased along the time?). I already had looking at the limma user's guide and I saw that there is the function heatdiagram. I will need to analyze it in the marray in a way that is easier of being analyzed in limma. Another doubt that I already have on limma would be the file design. All help will be very welcome. Best wishes. -- Marcelo Luiz de Laia, M.Sc. Dep. de Tecnologia, Lab. Bioqu?mica e de Biologia Molecular Universidade Estadual Paulista - UNESP Via de Acesso Prof. Paulo Donato Castelane, Km 05 14.884-900 - Jaboticabal, SP, Brazil PhoneFax: 16 3209-2675/2676/2677 R. 202/208/203 (trab.) HomePhone: 16 3203 2328 - www.lbm.fcav.unesp.br - mlaia@yahoo.com
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@gordon-smyth
Last seen 9 minutes ago
WEHI, Melbourne, Australia
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In the Tue, 20 Jan 2004 10:42:40 +1100 Gordon Smyth <smyth@wehi.edu.au> write: GS> Heatdiagram may help you visualize your results, but what you really need GS> is the F-statistic computed by the classifyTests() function. This is not GS> yet explained in the User's Guide. Can you consult a local statistician for GS> help who knows a little about linear models and contrasts? GS> GS> Gordon Hi Gordon and All, I find in the html_help and in the user's guide and I accomplished the following test with my data. If is possible, I would like you to verify if it is correct, because I am not sure of that. The experiment design is: Time 1day 2day 3day Rep1 Rep1 Rep1 Un Treated Rep2 Rep2 Rep2 Rep3 Rep3 Rep3 Rep1 Rep1 Rep1 Treated Rep2 Rep2 Rep2 Rep3 Rep3 Rep3 It follows the script: > library(limma) > RG <- read.maimages(files, columns=list(Rf="DataVol",Gf="CtrlVol", + Rb="DataBkgd",Gb="CtrlBkgd")) > show(RG) > summary(RG$R) > genes.names[1:10,] > printer <- list(ngrid.r=4, ngrid.c=5, nspot.r=16, nspot.c=24, ndups=2, + spacing=1, npins=20, start="topleft") > printer > MA <- normalizeWithinArrays(RG, method="none", printer) > boxplot(MA$M~col(MA$M)) > MA <- normalizeWithinArrays(RG, printer) > boxplot(MA$M~col(MA$M)) > MA.fa <- normalizeBetweenArrays(MA,method="scale") > boxplot(MA.fa$M~col(MA.fa\$M)) > design <- model.matrix(~ -1+factor(c(1,1,1,2,2,2,3,3,3))) > colnames(design) <- c("time1","time2","time3") > fit <- lmFit(MA.fa,design) > contrast.matrix <- makeContrasts(time2-time1, time3-time2,time3-time1,levels=design) > fit2 <- contrasts.fit(fit,contrast.matrix) > fit3 <- eBayes(fit2) > time2.time1 <- topTable(fit3, coef=1, adjust="fdr") > time3.time2 <- topTable(fit3, coef=2, adjust="fdr") > time3.time1 <- topTable(fit3, coef=3, adjust="fdr") > clas <- classifyTests(fit3) > vennDiagram(clas) If the script is correct, I obtained genes common to the time 2 and time 1, time 3 and time 2 and time 3 and time 1. However, I didn't obtain any gene common to the three times. Is there as leaving the test a little less rigorous? Maybe I find at least about 5 genes common to the three times! Or it is not a good ideia? Thanks very much Best wishes Marcelo GS>