[BioC] process one color microarray

[Yong Li]

Hi Paz, hi Jim,

I think there is a problem here. Jim, you have given detailed 
explanation of making design matrix and do various comparisons, but they 
are based on the assumption that the input given to lmFit is log 
expression values from one color array. The problem is that, based on 
Paz's code, in the MAList MA1 the M values are log 2 ratios of mean to 
processed signals of the green channel (of course background corrected 
and quantile normalized). I doubt very much that that piece of codes 
does what Paz wants to do. However, it's also possible that I missed 
something.

Best regards,
Yong

James W. MacDonald wrote:
> Hi Paz,
> 
> On 9/14/2011 5:55 PM, Paz Tapia Ramirez wrote:
>> Hello, I have a question. I'm Working with one-color microarrays . I 
>> worked in 4 conditions different and each condition I have 4 
>> replicates. Now, my question is  when I load the files to 
>> Bioconductor, I load as follows:
>>   my.filenames<- c ("Condic1_repl1.txt",
>>                                   "Condic1_repl2.txt",
>>                                   "Condic1_repl3.txt",
>>                                  "Condic1_repl4.txt",
>>                                   "Condic2_repl1.txt",
>>                                   "Condic2_repl2.txt",
>>                                  "Condic2_repl3.txt",
>>                                   "Condic2_repl4.txt",
>>                                   "Condic3_repl1.txt"
>>                                  "Condic3_repl2.txt",
>>                                   "Condic3_repl3.txt",
>>                                   "Condic3_repl4.txt",
>>                                   "Condic3_repl1.txt",
>>                                  "Condic3_repl2.txt",
>>                                   "Condic3_repl3.txt",
>>                                   "Condic3_repl4.txt")
>>
>> Subsequently, I realize the normalization procedure and some 
>> statistical calculations:
>>   one.col1<-list (R = "gMeanSignal" G = "gProcessedSignal"
>>              Rb = "gBGMedianSignal", Gb = "gProcessedBackground")
>>   RG1<- read.maimages (my.filenames, source = "agilent", columns = 
>> one.col1, dec =".")
>>    RG1<- backgroundCorrect (RG1, method = "half", offset = 50)
>>    MA1<- normalizeBetweenArrays (RG1, method = "quantile")
>>   fit1<- lmFit (MA1, design = NULL)
> 
> The design matrix indicates to lmFit() what is control and what is 
> treatment. When you specify a NULL design matrix, lmFit() will just use 
> a vector of 1s, which would be fine if you had two-color chips and no 
> dye-swaps. Otherwise, you are just testing the hypothesis that the 
> average expression of all samples is not equal to zero (which obviously 
> isn't correct).
> 
> So if you have four conditions with four replicates (and I am assuming 
> here that they are Biological replicates, not just different aliquots of 
> the same sample), you want a design matrix with four columns. The 
> simplest such design matrix (to me, anyway), computes the mean 
> expression for each group, and then you can just make the comparisons 
> you want.
> 
> cond <- factor(rep(1:4, each = 4))
> design <- model.matrix(~ 0 + cond)
> colnames(design) <- c("trt1","trt2","trt3","trt4")
> 
> contrast <- makeContrasts(trt2-trt1, trt3-trt1, trt4-trt1, trt3-trt2, 
> trt4-trt2, trt4-trt3, levels = design)
> fit <- lmFit(Ma1, design)
> fit1 <- contrasts.fit(fit, contrast)
> fit1 <- eBayes(fit1)
> 
> which will make all possible comparisons.
> 
> Alternatively, if you just want to compare all treatments to a control 
> (and assuming your control is trt1).
> 
> design <- model.matrix(~cond)
> fit <- lmFit(Ma1, design)
> fit1 <- eBayes(fit)
> 
> In this case, all coefficients in the model will be e.g., trt2-trt1, 
> trt3-trt1, trt4-trt1, so you don't have to specify contrasts directly.
> 
> Best,
> 
> Jim
> 
> 
> 
>>   fit1<- eBay (fit1)
>>
>> But my question is: how I can specify to bioconductor which files 
>> correspond to Control, or which correspond to microarrays with  
>> treatment?
>>
>> Regards, Paz
>>                          
>>     [[alternative HTML version deleted]]
>>
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