Hello, I have two questions with regard to the AgiMicroRna package and they are FilterMicroRna and SignificantMicroRna functions. I was able to figure most of the package easily except these two functions. If any one can give me some hints or suggestions to get these two functions working, I will really appreciate your help. I think that the alternative way I used to filter control probes is causing trouble with the SignficantMicroRna function. I used this package to analyze Agilent Zebrafish miRNA arrays which were scanned using GenePix 4000B scanner and data extracted using Feature Extraction Software 9.5.3. I have posted the session info below (two functions that need attention are hightlighted). Session Info > library("AgiMicroRna") > targets.micro=readTargets(infile="targets.txt", verbose=TRUE) Target File FileName Treatment GErep Subject 36_DMSO_1 36_DMSO_1.txt 36DMSO 1 1 36_DMSO_2 36_DMSO_2.txt 36DMSO 1 2 36_DMSO_3 36_DMSO_3.txt 36DMSO 1 3 36_TCDD_1 36_TCDD_1.txt 36TCDD 2 1 36_TCDD_2 36_TCDD_2.txt 36TCDD 2 2 36_TCDD_3 36_TCDD_3.txt 36TCDD 2 3 60_DMSO_1 60_DMSO_1.txt 60DMSO 3 1 60_DMSO_2 60_DMSO_2.txt 60DMSO 3 2 60_DMSO_3 60_DMSO_3.txt 60DMSO 3 3 60_TCDD_1 60_TCDD_1.txt 60TCDD 4 1 60_TCDD_2 60_TCDD_2.txt 60TCDD 4 2 60_TCDD_3 60_TCDD_3.txt 60TCDD 4 3 > dd.micro=read.maimages(targets.micro$FileName, columns=list(R="gTotalGeneSignal",G= "gTotalProbeSignal",Rb="gMeanSignal", Gb="gProcessedSignal"), annotation=c("ProbeUID","ControlType","ProbeName","GeneName","Systemat icName", "sequence", "accessions","probe_mappings", "gIsGeneDetected","gIsSaturated","gIsFeatNonUnifOL", "gIsFeatPopnOL","chr_coord","gBGMedianSignal","gBGUsed")) Read 36_DMSO_1.txt Read 36_DMSO_2.txt Read 36_DMSO_3.txt Read 36_TCDD_1.txt Read 36_TCDD_2.txt Read 36_TCDD_3.txt Read 60_DMSO_1.txt Read 60_DMSO_2.txt Read 60_DMSO_3.txt Read 60_TCDD_1.txt Read 60_TCDD_2.txt Read 60_TCDD_3.txt > cvArray(dd.micro, "MeanSignal", targets.micro, verbose=TRUE) Foreground: MeanSignal FILTERING BY ControlType FLAG RAW DATA: 5335 PROBES without CONTROLS: 4620 ---------------------------------- (Non-CTRL) Unique Probe: 490 (Non-CTRL) Unique Genes: 231 ---------------------------------- DISTRIBUTION OF REPLICATED NonControl Probes reps 5 6 7 10 20 18 36 416 ------------------------------------------------------ Replication at Probe level- MEDIAN CV 36_DMSO_1 36_DMSO_2 36_DMSO_3 36_TCDD_1 36_TCDD_2 36_TCDD_3 60_DMSO_1 60_DMSO_2 60_DMSO_3 0.078 0.081 0.091 0.081 0.077 0.067 0.076 0.066 0.103 60_TCDD_1 60_TCDD_2 60_TCDD_3 0.073 0.086 0.069 ------------------------------------------------------ DISTRIBUTION OF REPLICATED Noncontrol Genes reps 20 231 ------------------------------------------------------ > ddTGS.rma = rmaMicroRna(dd.micro, normalize=TRUE, background=FALSE) Calculating Expression > ddPROC = filterMicroRna(ddTGS.rma, dd.micro, control = TRUE, IsGeneDetected = TRUE, wellaboveNEG = FALSE, limIsGeneDetected = 50, limNEG = 25, makePLOT = FALSE, targets.micro, verbose = TRUE) FILTERING PROBES BY FLAGS FILTERING BY ControlType Error in matrix(ddFILT$other$gIsGeneDetected, nrow = dim(ddFILT)[1], ncol = dim(ddFILT)[2]) : attempt to set an attribute on NULL > MMM = ddTGS.rma$Rb > colnames(MMM) = colnames(dd.micro$Rb) > maintitle='TGS.rma' > colorfill='blue' > ddaux=ddTGS.rma > ddaux$G=MMM > mvaMicroRna(ddaux, maintitle, verbose=TRUE) ------------------------------------------------------ mvaMicroRna info: FEATURES : 231 POSITIVE CTRL: 12 NEGATIVE CTRL: 7 STRUCTURAL: 3 > rm(ddaux) > RleMicroRna(MMM,"RLE TGS.rma", colorfill) > boxplotMicroRna(MMM, maintitle, colorfill) > plotDensityMicroRna(MMM, maintitle) > spottypes = readSpotTypes() > ddTGS.rma$genes$Status = controlStatus(spottypes, ddTGS.rma) Matching patterns for: ProbeName GeneName Found 231 gene Found 1 BLANK Found 1 Blank Found 0 blank Found 6 positive Found 0 negative Found 0 flag1 Found 0 flag2 Found 6 flag3 Found 5 flag4 Found 1 flag5 Setting attributes: values > i = ddTGS.rma$genes$Status == "gene" > esetPROC = esetMicroRna(ddTGS.rma[i,], targets.micro, makePLOT=TRUE, verbose = TRUE) outPUT DATA: esetPROC Features Samples 231 12 > design=model.matrix(~-1+treatment) > print(design) treatment36DMSO treatment36TCDD treatment60DMSO treatment60TCDD 1 1 0 0 0 2 1 0 0 0 3 1 0 0 0 4 0 1 0 0 5 0 1 0 0 6 0 1 0 0 7 0 0 1 0 8 0 0 1 0 9 0 0 1 0 10 0 0 0 1 11 0 0 0 1 12 0 0 0 1 attr(,"assign") [1] 1 1 1 1 attr(,"contrasts") attr(,"contrasts")$treatment [1] "contr.treatment" > fit=lmFit(esetPROC, design) > cont.matrix = makeContrasts(treatment36TCDDvstreatment36DMSO = treatment36TCDD-treatment36DMSO, treatment60TCDDvstreatment60DMSO = treatment60TCDD-treatment60DMSO,treatment60TCDDvstreatment36TCDD = treatment60TCDD-treatment36TCDD, treatment60DMSOvstreatment36DMSO = treatment60DMSO-treatment36DMSO, levels=design) > print(cont.matrix) Contrasts Levels treatment36TCDDvstreatment36DMSO treatment60TCDDvstreatment60DMSO treatment36DMSO -1 0 treatment36TCDD 1 0 treatment60DMSO 0 -1 treatment60TCDD 0 1 Contrasts Levels treatment60TCDDvstreatment36TCDD treatment60DMSOvstreatment36DMSO treatment36DMSO 0 -1 treatment36TCDD -1 0 treatment60DMSO 0 1 treatment60TCDD 1 0 > fit2 = contrasts.fit(fit,cont.matrix) > print(head(fit2$coeff)) Contrasts treatment36TCDDvstreatment36DMSO treatment60TCDDvstreatment60DMSO dre-let-7a 0.038640984 0.013333873 dre-let-7b 0.074038749 -0.031608286 dre-let-7c 0.026244357 -0.005682488 dre-let-7d 0.067340768 0.055567054 dre-let-7e 0.004569306 0.136348664 dre-let-7f 0.042880109 0.085568058 Contrasts treatment60TCDDvstreatment36TCDD treatment60DMSOvstreatment36DMSO dre-let-7a 1.7358343 1.76114142 dre-let-7b 0.1366920 0.24233899 dre-let-7c 0.9920976 1.02402449 dre-let-7d 0.8098432 0.82161694 dre-let-7e 0.1186829 -0.01309647 dre-let-7f 1.1245878 1.08189990 > fit2 = eBayes(fit2) > fit2 = basicLimma(esetPROC, design, cont.matrix, verbose = TRUE) DATA Features Samples 231 12 > DE = getDecideTests(fit2, DEmethod = "separate", MTestmethod = "BH", PVcut = 0.1, verbose = TRUE) ------------------------------------------------------ Method for Selecting DEGs: separate Multiple Testing method: BH - pval 0.1 treatment36TCDDvstreatment36DMSO treatment60TCDDvstreatment60DMSO UP 0 5 DOWN 0 1 treatment60TCDDvstreatment36TCDD treatment60DMSOvstreatment36DMSO UP 56 51 DOWN 80 91 ------------------------------------------------------ > pvalHistogram(fit2, DE, PVcut = 0.1, DEmethod ="separate", MTestmethod="BH",cont.matrix, verbose= TRUE) > significantMicroRna(esetPROC, ddTGS.rma, targets.micro, fit2, cont.matrix, DE, DEmethod = "separate", MTestmethod= "BH", PVcut = 0.1, Mcut=0, verbose=TRUE) ------------------------------------------------------ CONTRAST: 1 - treatment36TCDDvstreatment36DMSO Error in data.frame(PROBE_ID, as.character(GENE_ID), as.character(chr_coord), : arguments imply differing number of rows: 231, 0 Thank you very much, Sincerely, Neel Neel Aluru Ph.D. Post doctoral Scholar Biology Department Redfield 304 (MS#32) Woods Hole Oceanographic Institution Woods Hole MA 02543 USA Phone: (508) 289-3607 [Office] 774-392-3727 [Cell] RID: A-7237-2009 [[alternative HTML version deleted]]