[BioC] limma help - choosing an approach

[john seers (IFR)]

Hello Naomi (and anyone else)

Thanks again for your help. It has  been extremely helpful. Almost there
I think, though I am still just doing it on autopilot and not quite sure
how meaningful this is. I am slightly worried by the limma documentation
which describes the single channel analysis as "experimental" so
combined with my lack of understanding makes me feel quite uncertain.
Anyway I can run it now and pull out lists of genes - though what they
mean I am not sure yet.

So, a bit of sanity checking if that is OK. 

> a) I needed to build my targets from a list of treatments for red and
gree.

I guess these are equivalent to Cy5 and Cy3 with Genepix. The function
"targetsC<-targetsA2C(targets)" converts it to single channel format.
(See targets files below, showing before and after). 


>b) The design matrix will have more than 4 columns, as you have 3 
>levels of concentration.  So there are 2 columns for concentration 
>and 2 for time:concentration.

I have altered the targets file to reflect this better.

So now my code looks like:

Time<-targetsC$Time
Conc<-targetsC$Target
Time<-factor(Time, levels=c("t1", "t4"))
Conc<-factor(Conc, levels=c("c0", "c20", "c100"))


Giving:

> Time
 [1] t1 t1 t4 t4 t4 t4 t1 t1 t1 t1 t4 t4 t1 t1 t1 t1 t4 t4 t4 t4 t4 t4
t1 t1 t4 t4 t1 t1 t1 t1
Levels: t1 t4
> Conc
 [1] c100 c0   c20  c0   c100 c0   c20  c0   c20  c0   c20  c0   c20  c0
c100 c0   c20  c0   c20  c0   c100 c0   c100 c0   c100 c0  
[27] c100 c0   c20  c0  
Levels: c0 c20 c100
> 

Set up the design file:

design<-model.matrix(~Time + Conc + Time:Conc)

Giving (first three lines):

   (Intercept) Timet4 Concc20 Concc100 Timet4:Concc20 Timet4:Concc100
1            1      0       0        1              0               0
2            1      0       0        0              0               0


colnames(design)<-c("Intercept", "t4", "c20", "c100", "t4c20", "t4c100")


corfit<-intraspotCorrelation(MA.nba, design)
fit<-lmscFit(MA.nba, design, correlation=corfit$consensus)


# contrast matrix
contrast.matrix<-makeContrasts(t4, c20, c100, t4c20, t4c100,
levels=design)

(What is possible here? What sort of contrasts are valid/meaningful?
Presumably I could do c20 + c100 to compare against c0?).



# contrast timepoints and controls
fit2<- contrasts.fit(fit, contrast.matrix)


# eBayes 
eb<- eBayes(fit2)


ngenes<-20
topa1<-topTable(eb, coef=1, number=ngenes, adjust="none", sort.by="M")

.....




Regards


John Seers



Targets data before transforming using targetsA2C


SlideNumber	FileName	Cy3	Cy5	Time
598	598new.gpr	c100	c0	t1
599	599new.gpr	c20	c0	t4
600	600new.gpr	c100	c0	t4
617	617new.gpr	c20	c0	t1
621	621new.gpr	c20	c0	t1
637	637new.gpr	c20	c0	t4
638	638new.gpr	c20	c0	t1
639	639new.gpr	c100	c0	t1
748	748new.gpr	c20	c0	t4
751	751new.gpr	c20	c0	t4
833	833new.gpr	c100	c0	t4
835	835new.gpr	c100	c0	t1
836	836new.gpr	c100	c0	t4
957	957new.gpr	c100	c0	t1
958	958new.gpr	c20	c0	t1

Targets data after transforming using targetsA2C


> targetsC
         channel.col SlideNumber   FileName Time Target
598new.1           1         598 598new.gpr   t1   c100
598new.2           2         598 598new.gpr   t1     c0
599new.1           1         599 599new.gpr   t4    c20
599new.2           2         599 599new.gpr   t4     c0
600new.1           1         600 600new.gpr   t4   c100
600new.2           2         600 600new.gpr   t4     c0
617new.1           1         617 617new.gpr   t1    c20
617new.2           2         617 617new.gpr   t1     c0
621new.1           1         621 621new.gpr   t1    c20
621new.2           2         621 621new.gpr   t1     c0
637new.1           1         637 637new.gpr   t4    c20
637new.2           2         637 637new.gpr   t4     c0
638new.1           1         638 638new.gpr   t1    c20
638new.2           2         638 638new.gpr   t1     c0
639new.1           1         639 639new.gpr   t1   c100
639new.2           2         639 639new.gpr   t1     c0
748new.1           1         748 748new.gpr   t4    c20
748new.2           2         748 748new.gpr   t4     c0
751new.1           1         751 751new.gpr   t4    c20
751new.2           2         751 751new.gpr   t4     c0
833new.1           1         833 833new.gpr   t4   c100
833new.2           2         833 833new.gpr   t4     c0
835new.1           1         835 835new.gpr   t1   c100
835new.2           2         835 835new.gpr   t1     c0
836new.1           1         836 836new.gpr   t4   c100
836new.2           2         836 836new.gpr   t4     c0
957new.1           1         957 957new.gpr   t1   c100
957new.2           2         957 957new.gpr   t1     c0
958new.1           1         958 958new.gpr   t1    c20
958new.2           2         958 958new.gpr   t1     c0
> 



 
---

John Seers
Institute of Food Research
Norwich Research Park
Colney
Norwich
NR4 7UA
 

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e-mail john.seers at bbsrc.ac.uk                         
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