[BioC] arrays with different gal files

[Tiandao Li]

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$FileName,source="genepix",ext="gpr",columns=A,other.columns=B)
spottypes <- readSpotTypes("spottypes3.txt") # short spot types
RG$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