I'm trying to run LPE on my data set (2 replicates each, 2 samples=4 chips, hgu133plus2). Here's what I'm getting: > data[1:3,] ID E.161K.DCM.A.CEL E.161K.DCM.B.CEL ISC.Cntl.A.CEL ISC.Cntl.B.CEL 1 1007_s_at 9.809272 10.158500 9.648349 9.700356 2 1053_at 7.123087 7.335424 6.911521 6.811536 3 117_at 7.951087 7.687096 7.724805 7.792392 > data[,2:4] <- preprocess(data[,2:4], data.type = "MAS5") > data[1:3,] ID E.161K.DCM.A.CEL E.161K.DCM.B.CEL ISC.Cntl.A.CEL ISC.Cntl.B.CEL 1 1007_s_at 3.412529 3.428885 3.402416 9.700356 2 1053_at 2.950885 2.995280 2.896051 6.811536 3 117_at 3.109535 3.049017 3.060164 7.792392 > data <- data[substring(data$ID, 54614:54675) !="AFFX",] > dim(data) [1] 54675 5 > data <- data[substring(data$ID,1,4) !="AFFX",] > dim(data) [1] 54613 5 > data[1:3,] ID E.161K.DCM.A.CEL E.161K.DCM.B.CEL ISC.Cntl.A.CEL ISC.Cntl.B.CEL 1 1007_s_at 3.412529 3.428885 3.402416 9.700356 2 1053_at 2.950885 2.995280 2.896051 6.811536 3 117_at 3.109535 3.049017 3.060164 7.792392 > var.Naive <- baseOlig.error(data[,2:3], q=0.01) > dim(var.Naive) [1] 54613 2 > var.Naive[1:3,] A var.M 1 3.420707 0.0006387559 2 2.973082 0.0037404778 3 3.079276 0.0035043507 > var.wt <- baseOlig.error(data[,4:5], q=0.01) > dim(var.wt) [1] 54613 2 > var.wt[1:3,] A var.M 1 6.551386 58.44331 2 4.853794 58.44331 3 5.426278 58.44331 > lpe.val <-data.frame(lpe(data[,4:5], data[,2:3], var.wt, var.Naive, probe.set.name=data$ID)) > lpe.val <- round(lpe.val, digits=2) Error in Math.data.frame(x, digits) : Non-numeric variable in dataframe: flag.outlier.x > dim (lpe.val) [1] 54613 15 > lpe.val[1:3,] x.ISC.Cntl.A.CEL x.ISC.Cntl.B.CEL median.1 std.dev.1 p.outlier.x flag.outlier.x y.E.161K.DCM.A.CEL 1007_s_at 3.402416 9.700356 6.551386 7.644823 0.5602117 . 3.412529 1053_at 2.896051 6.811536 4.853794 7.644823 0.7172308 . 2.950885 117_at 3.060164 7.792392 5.426278 7.644823 0.6615988 . 3.109535 y.E.161K.DCM.B.CEL median.2 std.dev.2 p.outlier.y flag.outlier.y median.diff pooled.std.dev 1007_s_at 3.428885 3.420707 0.02527362 0.6622332 . 3.130679 5.405736 1053_at 2.995280 2.973082 0.06115945 0.6078503 . 1.880711 5.405879 117_at 3.049017 3.079276 0.05919756 0.4682921 . 2.347002 5.405868 z.stats 1007_s_at 0.5791403 1053_at 0.3479011 117_at 0.4341582 > fdr.BH <- fdr.adjust(lpe.val, adjp="BH") > dimfdr.BH) [1] 54613 2 > roundfdr.BH[1:4, ],2) FDR z.real [1,] 0.85 1.00 [2,] 0.85 1.00 [3,] 0.85 0.99 [4,] 0.85 0.99 > 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 = numeric(0)) : nothing to replace with In addition: Warning messages: 1: NaNs produced in: sqrt(2 * var.x0) 2: NaNs produced in: sqrt(2 * var.y0) 3: NaNs produced in: sqrt(2 * var.x0) 4: NaNs produced in: sqrt(2 * var.y0) > A previous post regarding the NaNs warning had a reply recommending the preprocessing step which I have performed, without receiving an error message. I did have the error for the rounding step though, and my lpe.val results include the p.outlier, and flag.outlier columns that are not shown in the vignette. I am running R 2.0 and Bioconductor 1.5 on a Mac OSX system. Stephanie K. Mewborn, Ph.D. Post-Doctoral Scholar University of Chicago Department of Medicine, Section of Cardiology Phone: 773-702-2684 Fax: 773-702-2681