Hello, I am analyzing cDNA microarray data using limma. I generated the GAL file using the program coming with chipwriter, everything looks great. However, when I printed the first batch of chips, after the last dip of pins in the first plate, print, wash, and the pins redipped again in the first plate from the beginning, and print, wash, then stop to change the plate. For the next plate, the pins skipped the first dip, they picked up the material from the second dip, and so on, after printing from the last well of the plate, the pins moved to the first well of the current plate, and print, wash, and remind to change the plate. The company gave us the patch later to solve this problem. So this gal file is a little different than the rest batches of chips, the locations of genes, MSP, and controls are different (5%). After hybridization, I used GenePix Pro 6.1 for spotfinding. After reading the data into limma, I want to use MSP and control spots for print-tip normalization. I don't know how to label different spot types in all arrays using readSpotTypes(). Thanks, Tiandao I am kind of new to R and limma. The following is my setting. > sessionInfo() R version 2.5.1 (2007-06-27) i386-pc-mingw32 locale: LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252 attached base packages: [1] "stats" "graphics" "grDevices" "utils" "datasets" "methods" [7] "base" other attached packages: statmod limma "1.3.0" "2.10.5" Codes for analysis library(limma) A <- list(R="F635 Median",G="F532 Median",Rb="B635",Gb="B532") B <- list("Block", "Column", "Row", "Name", "ID", "X", "Y", "Dia.", "F635 Median", "F635 Mean", "F635 SD", "F635 CV", "B635", "B635 Median", "B635 Mean", "B635 SD", "B635 CV", "% > B635+1SD", "% > B635+2SD", "F635 % Sat.", "F532 Median", "F532 Mean", "F532 SD", "F532 CV", "B532", "B532 Median", "B532 Mean", "B532 SD", "B532 CV", "% > B532+1SD", "% > B532+2SD", "F532 % Sat.", "Ratio of Medians (635/532)", "Ratio of Means (635/532)", "Median of Ratios (635/532)", "Mean of Ratios (635/532)", "Ratios SD (635/532)", "Rgn Ratio (635/532)", "Rgn R2 (635/532)", "F Pixels", "B Pixels", "Circularity", "Sum of Medians (635/532)", "Sum of Means (635/532)", "Log Ratio (635/532)", "F635 Median - B635", "F532 Median - B532", "F635 Mean - B635", "F532 Mean - B532", "F635 Total Intensity", "F532 Total Intensity", "SNR 635", "SNR 532", "Flags", "Normalize", "Autoflag") # read 6 test files targets<-readTargets(file="targets.txt", row.name="Name") # 6 test files RG <- read.maimages(targets$FileName,source="genepix",ext="gpr",columns=A,ot her.columns=B) spottypes <- readSpotTypes("spottypes3.txt") # short spot types RG$genes$Status <- controlStatus(spottypes,RG) targets SlideNumber FileName Cy3 Cy5 Name 1 13582917 N0 N1 N0N121 2 13582918 N0 N1 N0N122 3 13590446 N0 N1 N0N123 4 13590420 N1 H1 N1H121 5 13590521 N1 H1 N1H122 6 13591193 N1 H1 N1H123 spottypes3 SpotType ID Color gene * black Calibration Calib* blue Ratio Ratio* red Negative Neg*|Util* brown MSP MSP orange Alexa Alexa* yellow blank NotDefined green