Dear list members, I am analysing my microarray data using limma package. Now I encounter several problems. Looking forward to your suggestions! Question 1: During the process of background correction using method="normexp", four warning messages appeared as "NaNs produced in: log(x)" (as you can see in the program posted below). What does that mean? How will it effect the final result? How could it be settled? Question 2: On my microarray, every probe has two replicates.During the process of duplicateCorrelation, two warnings appear as "Too much damping - convergence tolerance not achievable" (as you also can see in the program posted below). What does it mean? Is there anything wrong with my data? Question 3: How to construct the design matrix is a puzzle to me. Here I constructed the design matrix using the function modelMatrix and the object targets. However, I am not sure whether it is constructed appropriately. Looking forward to your suggestions. (Additional info about my experimental design. Uppercase and lowercase words in the R object targets (see below in the posted program) have different meanings. The locusts on the plain [PLAIN] was treated [plain] in a simulated plateau environment while the locusts on the plateau [PLATEAU] was treated [plateau] in a simulated plain environment. They experienced different treatments. I think it is not a complete factorial design. Therefore I did not choose the design matrix for factorial designs. However, I do not know whether what I chose is appropriate.) Question 4: All in all, I wonder whether the differentially expressed genes produced via the posted program are convincing. Will the above-mentioned warnings affect the reliability of the final result? Can I continue to the next step? Thanks! Dejian Zhao ++++++++++++++++++ Program Starts +++++++++++++++++++++ > library(limma) > library(statmod) #duplicateCorrelation requires this package. > targets<-readTargets() > targets Cy3 Cy5 FileName Date 1 PLAIN PLATEAU Locust 186.gpr 2006-5-31 2 PLAIN PLATEAU Locust 187.gpr 2006-5-31 3 PLAIN PLATEAU Locust 188.gpr 2006-5-31 4 PLAIN PLATEAU Locust 189.gpr 2006-5-31 5 PLAIN PLATEAU Locust 190.gpr 2006-5-31 6 PLAIN PLATEAU Locust 191.gpr 2006-5-31 7 plain PLAIN Locust 192.gpr 2006-6-6 8 plain PLAIN Locust 193.gpr 2006-6-6 9 plain PLAIN Locust 194.gpr 2006-6-6 10 plain PLAIN Locust 195.gpr 2006-6-6 11 plain PLAIN Locust 196.gpr 2006-6-6 12 plain PLAIN Locust 197.gpr 2006-6-6 13 plateau PLATEAU Locust 198.gpr 2006-6-8 14 plateau PLATEAU Locust 199.gpr 2006-6-8 15 plateau PLATEAU Locust 200.gpr 2006-6-8 16 plateau PLATEAU Locust 201.gpr 2006-6-8 17 plateau PLATEAU Locust 202.gpr 2006-6-8 18 plateau PLATEAU Locust 203.gpr 2006-6-8 > RG<-read.maimages(targets,source="genepix",wt.fun=wtflags(0.1)) Read Locust 186.gpr Read Locust 187.gpr Read Locust 188.gpr Read Locust 189.gpr Read Locust 190.gpr Read Locust 191.gpr Read Locust 192.gpr Read Locust 193.gpr Read Locust 194.gpr Read Locust 195.gpr Read Locust 196.gpr Read Locust 197.gpr Read Locust 198.gpr Read Locust 199.gpr Read Locust 200.gpr Read Locust 201.gpr Read Locust 202.gpr Read Locust 203.gpr > RG$genes<-readGAL() > spottypes<-readSpotTypes() > spottypes SpotType ID Name Color 1 gene * * black 2 blank Blank * brown 3 buffer *sc * blue 4 rice Os026* * green 5 beta-actin Beta* * red 6 18S 18S* * yellow 7 GAPDH GAPDH* * purple > RG$genes$Status<-controlStatus(spottypes,RG) Matching patterns for: ID Name Found 19200 gene Found 96 blank Found 220 buffer Found 192 rice Found 192 beta-actin Found 96 18S Found 96 GAPDH Setting attributes: values Color > RG.b<-backgroundCorrect(RG,method="normexp",offset=0) Corrected array 1 Corrected array 2 Corrected array 3 Corrected array 4 Corrected array 5 Corrected array 6 Corrected array 7 Corrected array 8 Corrected array 9 Corrected array 10 Corrected array 11 Corrected array 12 Corrected array 13 Corrected array 14 Corrected array 15 Corrected array 16 Corrected array 17 Corrected array 18 Warning messages: 1: NaNs produced in: log(x) 2: NaNs produced in: log(x) 3: NaNs produced in: log(x) 4: NaNs produced in: log(x) > w<-modifyWeights(RG$weights,RG$genes$Status,c("rice","beta- actin","18S","GAPDH"),c(0.1,2,2,2)) MA.p<-normalizeWithinArrays(RG.b,weights=w,iterations=6) > design<-modelMatrix(targets,ref="PLAIN") Found unique target names: plain PLAIN plateau PLATEAU > design plain plateau PLATEAU [1,] 0 0 1 [2,] 0 0 1 [3,] 0 0 1 [4,] 0 0 1 [5,] 0 0 1 [6,] 0 0 1 [7,] -1 0 0 [8,] -1 0 0 [9,] -1 0 0 [10,] -1 0 0 [11,] -1 0 0 [12,] -1 0 0 [13,] 0 -1 1 [14,] 0 -1 1 [15,] 0 -1 1 [16,] 0 -1 1 [17,] 0 -1 1 [18,] 0 -1 1 > i<-MA.p$genes$Status=="gene" > corMA.pi<-duplicateCorrelation(MA.p[i,],design,ndups=2) Warning messages: 1: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace = trace) 2: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace = trace) > fitMA.pi<-lmFit(MA.p[i,],design,ndups=2,correlation=corMA.pi$consens us.correlation) contrast.matrix<-makeContrasts(plain,plateau- PLATEAU,PLATEAU,levels=design) contrast.matrix Contrasts Levels plain plateau - PLATEAU PLATEAU plain 1 0 0 plateau 0 1 0 PLATEAU 0 -1 1 > colnames(contrast.matrix)<-cbind("plain-PLAIN","plateau-PLATEAU ","PLATEAU-PLAIN") contrast.matrix Contrasts Levels plain-PLAIN plateau-PLATEAU PLATEAU-PLAIN plain 1 0 0 plateau 0 1 0 PLATEAU 0 -1 1 > fit2MA.pi<-contrasts.fit(fitMA.pi,contrast.matrix) > fit2MA.pi<-eBayes(fit2MA.pi) > resultsi.001.fc2=decideTests(fit2MA.pi,method="nestedF",adjust.metho d="BH",p.value=0.001,lfc=log2(2)) write.fit(fit2MA.pi, results=decideTests(fit2MA.pi,method="nestedF",adjust.method="BH",p.va lue=0.001,lfc=1), "fit2MA.pi.nestedF.adj_BH.P_001.FC_2.csv", digits=4, adjust="BH", sep=",") > save.image("result.RData") ++++++++++++++++++ Program Ends +++++++++++++++++++++ -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... 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