Hi Nitin and all, I m trying to use LPE to compare 2 groups. In first group I have 4 chips and in the second one 8 chips (same kind of CEL files, ie, HU133A from Affymetrix). here is what I doing: library(affy) library(LPE) library(gcrma) data1<-ReadAffy() data2 <-gcrma(data1) data3<-exprs(data2) data4<-data.frame(Name=geneNames(data2), data3) var.g1 <- baseOlig.error(data4[,2:5],q=0.01) # group1 colum 2 a 5 var.g2 <- baseOlig.error(data4[,6:13],q=0.01) # group2 colum 6 a 13 lpe.val1<-data.frame(lpe(data4[,6:13], data4[,2:5], var.g2, var.g1, probe.set.name=data4$Name)) And here is what I obtain first: Warning messages: 1: NaNs produced in: sqrt(1.57 * ((var.x/n1) + (var.y/n2))) 2: NaNs produced in: sqrt(var.x) 3: NaNs produced in: sqrt(var.y) then the following: > lpe.val <- round(lpe.val1, digits=2) > fdr.BH <- fdr.adjust(lpe.val, adjp="BH") > fdr.2 <- fdr.adjust(lpe.val, adjp="resamp", iterations=2) iteration number 1 is in progress iteration number 1 finished iteration number 2 is in progress iteration number 2 finished Computing FDR... Error in "[<-"(`*tmp*`, j, value = z.real[num.genes.signif]) : nothing to replace with In addition: Warning messages: 1: NaNs produced in: sqrt(1.57 * ((var.x/n1) + (var.y/n2))) 2: NaNs produced in: sqrt(var.x) 3: NaNs produced in: sqrt(var.y) When I look at the file I dont get any adjusted p values any suggestion ? thanks Philippe ps I ve been also trying the old version of LPE without permutation lpe.val1<-data.frame(lpe(data4[,6:13], data4[,2:5], var.g2, var.g1, probe.set.name=data4$Name, adjp=c("BH","BY"))) and obtained the same warning meesages: 1: NaNs produced in: sqrt(1.57 * ((var.x/n1) + (var.y/n2))) 2: NaNs produced in: sqrt(var.x) 3: NaNs produced in: sqrt(var.y) and no adjusp P values

Dear Philippe, As the warning messages indicate, NANs are being produced in taking square root, which means some values in var.x are being calculated as negative from baseOlig.error function. I apply preprocess function to the data set, before giving it as input for baseOlig.error function, which takes care of missing values, thresholds the data at 1, and does log2 transformation. Could you please send me the data4, so that I can check what part is going wrong? Thanks. Nitin PhD candidate, University of Virginia ------------------------------------ > Hi Nitin and all, > I m trying to use LPE to compare 2 groups. In first group I have 4 chips and in the second one 8 chips (same kind of CEL files, ie, HU133A from Affymetrix). > here is what I doing: > > library(affy) > library(LPE) > library(gcrma) > > data1<-ReadAffy() > data2 <-gcrma(data1) > data3<-exprs(data2) > data4<-data.frame(Name=geneNames(data2), data3) > var.g1 <- baseOlig.error(data4[,2:5],q=0.01) # group1 colum 2 a 5 > var.g2 <- baseOlig.error(data4[,6:13],q=0.01) # group2 colum 6 a 13 > > lpe.val1<-data.frame(lpe(data4[,6:13], data4[,2:5], var.g2, var.g1, probe.set.name=data4$Name)) > > And here is what I obtain first: > Warning messages: > 1: NaNs produced in: sqrt(1.57 * ((var.x/n1) + (var.y/n2))) > 2: NaNs produced in: sqrt(var.x) > 3: NaNs produced in: sqrt(var.y) > > then the following: > > > lpe.val <- round(lpe.val1, digits=2) > > fdr.BH <- fdr.adjust(lpe.val, adjp="BH") > > fdr.2 <- fdr.adjust(lpe.val, adjp="resamp", iterations=2) > iteration number 1 is in progress > iteration number 1 finished > iteration number 2 is in progress > iteration number 2 finished > Computing FDR... > Error in "[<-"(`*tmp*`, j, value = z.real[num.genes.signif]) : > nothing to replace with > In addition: Warning messages: > 1: NaNs produced in: sqrt(1.57 * ((var.x/n1) + (var.y/n2))) > 2: NaNs produced in: sqrt(var.x) > 3: NaNs produced in: sqrt(var.y) > > When I look at the file I dont get any adjusted p values > any suggestion ? > thanks > Philippe > > ps I ve been also trying the old version of LPE without permutation > lpe.val1<-data.frame(lpe(data4[,6:13], data4[,2:5], var.g2, var.g1, probe.set.name=data4$Name, adjp=c("BH","BY"))) > > and obtained the same warning meesages: > 1: NaNs produced in: sqrt(1.57 * ((var.x/n1) + (var.y/n2))) > 2: NaNs produced in: sqrt(var.x) > 3: NaNs produced in: sqrt(var.y) > and no adjusp P values > >