[BioC] two color time course analysis

[Gordon K Smyth]

Dear Priyanka,

On the quick read through, I don't see any problems with your code.  It 
should work perfectly as far as I can see.  Can you please give us the 
output of

   dim(MA.Aq)

and

   dim(design)

at the time of the error.

Best wishes
Gordon

> Date: Sun, 2 Jan 2011 22:00:06 -0600 (CST)
> From: "Kachroo, Priyanka" <priya_coll at neo.tamu.edu>
> To: bioconductor at r-project.org
> Subject: [BioC] two color time course analysis
> Message-ID: <200725487.382131294027206350.JavaMail.root at neo-mail-3>
> Content-Type: text/plain; charset=utf-8
>
> Hi All,
>
> I would like to ask the forum the best statistical analysis approach for 
> my experimental design in which i have three time points T0, T6 and T12 
> for a treatment group. I need to evaluate the DE genes between T6&T0 and 
> also T12&T0. Since the same set of animals were involved at all three 
> time points, will a paired t-test for T6-T0 and T12-T0 be a better 
> strategy or a time course analysis.
>
> I have dual color arrays hybridized in the following format. I tried to 
> do a time series analysis by first separating the channels and then 
> setting the contrasts as depicted in limma manual for single color 
> arrays (section 8.8 in limma manual). However i get following error: 
> "Error in intraspotCorrelation(MA.Aq, design) : The number of rows of 
> the design matrix should match the number of channel intensities, i.e., 
> twice the number of arrays".
>
> Target file:
> SlideNumber	FileName	Cy3	Cy5	Identity
> 14117071	14117071.gpr	T6	T0	61
> 14117070	14117070.gpr	T6	T0	123
> 14116987	14116987.gpr	T6	T0	308
> 14117067	14117067.gpr	T0	T6	315
> 14117099	14117099.gpr	T0	T6 	319
> 14116988	14116988.gpr 	T0	T12	61
> 14116990	14116990.gpr	T0	T12	123
> 14116964	14116964.gpr	T0	T12	308
> 14116989	14116989.gpr	T12	T0	315
> 14116948	14116948.gpr	T12	T0	319
>
> Here is code used so far:
>> targets<-readTargets("targets.txt")
>> RG<-read.maimages(targets,source="genepix",columns=list(R="F635 Median",G="F532 Median",Rb="B635",Gb="B532"))
> Read 14117071.gpr
> Read 14117070.gpr
> Read 14116987.gpr
> Read 14117067.gpr
> Read 14117099.gpr
> Read 14116988.gpr
> Read 14116990.gpr
> Read 14116964.gpr
> Read 14116989.gpr
> Read 14116948.gpr
>> RG$genes<-readGAL()
>> spottypes<-readSpotTypes("Spottypes.txt")
>> RG <- backgroundCorrect(RG, method="normexp", offset=50)
> Green channel
> Corrected array 1
> Corrected array 2
> Corrected array 3
> Corrected array 4
> Corrected array 5
> Corrected array 6
> Corrected array 7
> Corrected array 8
> Corrected array 9
> Corrected array 10
> Red channel
> Corrected array 1
> Corrected array 2
> Corrected array 3
> Corrected array 4
> Corrected array 5
> Corrected array 6
> Corrected array 7
> Corrected array 8
> Corrected array 9
> Corrected array 10
>> MA.p <- normalizeWithinArrays(RG)
>> MA.Aq<-normalizeBetweenArrays(MA.p,method="Aquantile")
>> targets2<-targetsA2C(targets)
>> targets2
>     channel.col SlideNumber      FileName Identity Target
> 1.1            1    14117071  14117071.gpr       61     T6
> 1.2            2    14117071  14117071.gpr       61     T0
> 2.1            1    14117070  14117070.gpr      123     T6
> 2.2            2    14117070  14117070.gpr      123     T0
> 3.1            1    14116987  14116987.gpr      308     T6
> 3.2            2    14116987  14116987.gpr      308     T0
> 4.1            1    14117067  14117067.gpr      315     T0
> 4.2            2    14117067  14117067.gpr      315     T6
> 5.1            1    14117099  14117099.gpr      319     T0
> 5.2            2    14117099  14117099.gpr      319    T6
> 6.1            1    14116988 14116988.gpr        61     T0
> 6.2            2    14116988 14116988.gpr        61    T12
> 7.1            1    14116990  14116990.gpr      123     T0
> 7.2            2    14116990  14116990.gpr      123    T12
> 8.1            1    14116964  14116964.gpr      308     T0
> 8.2            2    14116964  14116964.gpr      308    T12
> 9.1            1    14116989  14116989.gpr      315    T12
> 9.2            2    14116989  14116989.gpr      315     T0
> 10.1           1    14116948  14116948.gpr      319    T12
> 10.2           2    14116948  14116948.gpr      319     T0
>> lev<-c("T0","T6","T12")
>> u<-unique(targets2$Target)
>> f<-factor(targets2$Target,levels=lev)
>> design<-model.matrix(~0+f)
>> colnames(design)<-lev
>> corfit<-intraspotCorrelation(MA.Aq,design)
> Error in intraspotCorrelation(MA.Aq, design) :
>  The number of rows of the design matrix should match the number of channel intensities, i.e., twice the number of arrays
>>
>
> Can someone please help me with this error and how to obtain 
> differentially expressed genes for contrasts "T6-T0" and "T12-T0".
>
>
> Regards
>
> Priyanka Kachroo

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