[BioC] Antw: Re: limma voom: How to create double contrasts?

[James W. MacDonald]

Hi Christian,

On 7/18/2012 9:11 AM, Christian Ametz wrote:
> Hi James,
> thanks for your help. The problem with this interaction is, that I 
> find nearly none DE transcripts in our RNA-Seq experiment (3 
> replicates) while based on our microarray results we expect something 
> in the range of a few hundreds...

I am currently doing some comparisons between RNA-seq and microarray 
results as well (using edgeR rather than voom()), and see surprisingly 
little overlap between the two. I can come up with many reasons why this 
might be so, but without knowing the true underlying status of the 
transcript abundance it is not possible to know which platform does a 
better job of estimating what is really happening. Just knowing that 
they are different isn't particularly enlightening.


> Am I correct that this interaction finds significance if a) the 
> expression of the two groups is sig. different, or b) the fold-change 
> ratio is different (ie. C1 goes from 100 to 1000 when treating with 
> Fusarium compared to mock while C2 goes just from 50 to 100)  or) C1 
> is upregulated while C2 is downregulated when treated with Fusarium 
> and vice versa.

There are two issues here. First, the numerator of the interaction 
contrast is exactly as you have specified, so it is the difference 
between Fusarium vs mock for the two genotypes. This can be significant 
for a variety of reasons (e.g., C1 goes up in F vs M, C2 goes down in 
the same comp, or C1 doesn't change, but C2 either goes up or down, or 
C1 goes up or down and C2 doesn't change).

So you are literally looking for any gene where C1F-C1M-C2F+C2M is 
significantly different from zero, regardless of how that came about. As 
for fold change, you could hypothetically filter on the fold change of 
one or the other 'subcontrasts', but in general I think people just 
filter on the sum of the contrast. In which case you cannot say anything 
about the underlying contrasts (e.g., C1F-C1M might have a 0.5 log FC, 
and C2F-C2M might have a -0.5 log FC, which sums to 1 in the 
interaction, but neither contrast is significant at a two-fold FC).


> My problem is to interpret the contrasts correctly, besides the basic 
> contrasts. So basically whats the difference between this two contrasts:
> Diff_C1C2=(C1F-C1M)-(C2F-C2M) and
> Diff_C1C2_new = (C1F+C2F)/2-(C1M+C2M)/2 ?

This is simple algebra, so don't over think things. We have gone over 
the interaction term, so let's think about the second contrast you are 
looking at. The first term is the average expression for the C1F and C2F 
samples, and the second term is the average of the C1M and C2M samples. 
And you are computing the difference between the two, so it is simply 
the difference between F and M, averaged over the C1 and C2 genotypes.

This might be something of interest, if you either think the C1 and C2 
genotypes aren't really that different, or if you are looking for genes 
that react similarly in the two genotypes.

Best,

Jim


> Will the second contrast just find significance if both groups are 
> either up or downregulated?
> Thanks once more for your help!
> All the best
> Christian
>
> >>> "James W. MacDonald" <jmacdon at uw.edu> 7/18/2012 2:55 >>>
> Hi Christian,
>
> On 7/17/2012 4:32 AM, Christian Ametz wrote:
> > Dear members,
> >
> > I'm struggling to create the contrast matrix for our experiment 
> comprising of 4 genotypes in treated and untreated conditions:
> >
> > The genotypes are labelled C1 to C4
> > The conditions are treated (F) and untreated (M)
> > I set up the contrast matrix like this:
> >
> > cont.matrix.30<- makeContrasts(
> > C1_FvsM=C1F-C1M,
> > C2_FvsM=C2F-C2M,
> > C3_FvsM=C3F-C3M,
> > C4_FvsM=C4F-C4M,
> > Diff_C1C2=(C1F-C1M)-(C2F-C2M),
> > levels=design)
> >
> >
> > The first four "normal" contrasts estimating the response of 
> treated/untreated genotypes are working great. My problem is the 
> "double contrast" Diff_C1C2 where I want to find those genes that show 
> a difference in response (treated vs untreated)  between the two 
> genotypes C1 and C2.
>
> The technical term for that contrast is an interaction, and you have set
> it up correctly. So what is the problem?
>
> Best,
>
> Jim
>
>
> >
> >
> > I would gladly accept any help!
> >
> > Thanks
> > Christian
> >
> >
> >
> >
> >
> >
> > [[alternative HTML version deleted]]
> >
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>
> -- 
> James W. MacDonald, M.S.
> Biostatistician
> University of Washington
> Environmental and Occupational Health Sciences
> 4225 Roosevelt Way NE, # 100
> Seattle WA 98105-6099
>

-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099