[BioC] One channel microarray antibody analysis

[Jordi Altirriba Gutiérrez]

Dear BioC users,
I am trying to analyze 4 antibody arrays (hypromatrix) with 400 spots, which 
are stained with the HRP system (images in black and white with an important 
background in my case) [for more information about the arrays 
http://www.hypromatrix.com/Technology/phosphorylation.html ]. The images 
were obtained with an standard scanner with high resolution.
I have analyzed the TIFF images with GenePix, as it was a Cy3 image, to 
obtain the signal and the background which corresponds to each spot.
All the 4 arrays are four different conditions, 1 control and 3 conditions 
(neither technical nor biological replicates) and there aren’t control 
spots. Nevertheless, it’s expected that many of the spots don’t change its 
expression (I am very conscious that the design is very weak).
I have considered the 4 different arrays as 3 arrays of 2 colors:

Array---Cy3---------Cy5
1--------Reference---Condition1
2--------Reference---Condition2
3--------Reference---Condition3

I have normalized within and between the arrays and I have calculated the 
fold change.
Is my analysis correct or should I proceed in a different way?
Many thanks in advance for your advices.
Yours faithfully,

Jordi Altirriba
PhD student
Hospital Clinic, Barcelona, Spain

This is the code that I have used:

>library(limma)
>targets <- readTargets()

>targets
                            SlideNumber  FileName                  Cy3    
Cy5      Date
standard_cond1   1                    standard_cond1.txt   Ref     cond1   
7/6/2006
standard_cond2   2                    standard_cond2.txt   Ref     cond2   
7/6/2006
standard_cond3   3                    standard_cond3.txt   Ref     cond3   
7/6/2006

>RG <- read.maimages(targets$FileName, columns=list(R="F635 Mean",G="F532 
>Mean",Rb="B635 Median",Gb="B532 
>Median"),annotation=c("Block","Row","Column","ID","Name"))
>RGb <- backgroundCorrect(RG, method="subtract")
>MA <- normalizeWithinArrays(RGb, method="loess")
>MA.q <- normalizeBetweenArrays(MA, method="quantile")
>sink(“results.txt”)
>MA.q$M
>sink()


>MA.q
An object of class "MAList"
$targets
                                   FileName
standard_ cond1          standard_ cond1.txt
standard_ cond2          standard_ cond2.txt
standard_ cond3          standard_ cond3.txt

$genes
      Block Row  Column         ID                  Name
1     1       1        1                   14,3,3             14,3,3
2     1       2        1                   c-Abl              c-Abl
398 more rows ...

$source
[1] "generic"

$M
     standard_cond1 standard_cond2    standard_cond3
[1,]   -0.5339283    -0.31473618          -0.8712970
[2,]    0.5333891     0.17447885           0.1897565
398 more rows ...

$A
     standard_cond1 standard_cond2   standard_cond3
[1,]     12.92027       12.79477            13.06500
[2,]     12.82701       13.04232            13.04360
398 more rows ...

This is my R session:
>sessionInfo()
Version 2.3.0 (2006-04-24)
i386-pc-mingw32

attached base packages:
[1] "methods"   "stats"     "graphics"  "grDevices" "utils"     "datasets"  
"base"

other attached packages:
  limma
"2.7.2"