[BioC] limma - Identifying interactions

Michal Kolář kolarmi at img.cas.cz
Mon May 11 09:43:59 CEST 2009


Dear Suzanne,

I completely agree with Jim. You may also be interested in the  
following article, where the authors used a similar design: McMurray  
et al. (2008) Nature 453 p. 1112 doi:10.1038/nature06973

Best regards,
Michal

On 8 May 2009, at 12:00, bioconductor-request at stat.math.ethz.ch wrote:

> From: "James W. MacDonald" <jmacdon at med.umich.edu>
> Date: 7 May 2009 22:01:34 GMT+02:00
> To: Suzanne Szak <suzanne.szak at biogenidec.com>
> Cc: "bioconductor at stat.math.ethz.ch" <bioconductor at stat.math.ethz.ch>
> Subject: Re: [BioC] limma - Identifying interactions
>
>
> Hi Suzanne,
>
> Please don't take things off list - the archives are intended to be  
> a resource for people to search.
>
> Suzanne Szak wrote:
>> Dear Jim,
>> Thank you  very much for your response.   I've been spinning my  
>> wheels on this ... and by no means am I a statistician, which  
>> makes it all the more daunting.
>> Actually, I currently only have 3 contrasts represented in my  
>> contrast.matrix:
>> 1)  "Combo   vs.   Control"  designated as    combo-control  .   
>> Note that in this column, I don't have a contribution from x or   y.
>> 2)  "Drug X   vs.    Control"  designated as    x-control
>> 2)  "Drug Y    vs.   Control"  designated as    y-control
>>  >contrast.matrix
>>         combo-control        x-control        y-control         
>> x                        0                1                0
>> y                        0                0                1
>> combo                        1                0                0
>> control                -1                -1                -1
>
> You are right - my mistake. Which brings me to another point. Your  
> design matrix is what I would call a 'factor effects'  
> parameterization, in which everything is compared to an intercept,  
> in this case the controls. So the coefficient for e.g., the x  
> treatment is actually x - control. So the contrast matrix above is  
> wrong, as you are subtracting the control twice from every sample,  
> which as you have noticed is bad. You need to substitute a zero in  
> the control row for every contrast.
>
>>  From here, I would typically just run:
>>  > fit <- lmFit(chips.norm, design)
>>  > fit2 <- contrasts.fit(fit, contrast.matrix)
>>  > fit2 <- eBayes(fit2)
>> Then I would impose filters on the lods score, fold change, etc.  
>> to identify my genes of interest.  Using these matrices, I get  
>> ~80% of all genes on the Affymetrix chip as being significant in  
>> my "Combo vs Control" scenario .... no way!  That's why I used the  
>> phrase  "without luck."
>> Anyway, from your response, it sounds like my contrast.matrix  
>> should have a column like this:
>>  > contrast.matrix.try
>>         combo-control
>> x                        -1
>> y                     -1
>> combo               1
>> control             1
>
> Close, but not quite. This will give you (combo-control)-(x- 
> control)-(y-control)+control = combo-x-y+2control
>
> I think you want a zero in the control row, so you end up with
>
> (combo-control)-(x-control)-(y-control) = combo-x-y+control
>
> I would do it this way, as this will account for the possibility  
> that there is a baseline expression of the gene (captured by the  
> control), and the x, y, combo treatments just cause the expression  
> to go up or down from this point. So combo is really combo 
> +baseline, x is x+baseline, etc, so the above translates to
>
> (combo+baseline)-(x+baseline)-(y+baseline)+baseline = combo-x-y
>
> Or you could argue for
>
> x        -.5
> y        -.5
> combo    1
> control   0
>
> which would be about the same, but you are averaging the x, y  
> contribution.
>
> Best,
>
> Jim
>
>
>
>
>> But when I try this, again, about ~60% of the genes on the chip  
>> are significant  (e.g. lods>0,  abs(fold change) > 2).
>> I know you must be very busy, and I'd really appreciate any time  
>> that you might dedicate to helping me.  Thanks,
>> Suzanne
>> *"James W. MacDonald" <jmacdon at med.umich.edu>*
>> 07-May-2009 10:22 AM
>> Message Size: *5.0 KB*
>> 	
>> To
>> 	Suzanne Szak <suzanne.szak at biogenidec.com>
>> cc
>> 	bioconductor at stat.math.ethz.ch
>> Subject
>> 	Re: [BioC] limma - Identifying interactions
>> 	
>> Hi Suzanne,
>> Suzanne Szak wrote:
>>  > Hi all,
>>  >
>>  > I'd like to use limma to identify a possible interaction  
>> between two drugs
>>  > (called "x" and "y") which would be reflected in gene  
>> expression.  That
>>  > is, each drug has its own effect, but I think there might be  
>> synergy
>>  > between the two drugs if cells are treated with both of them  
>> ("combo").
>>  >
>>  > What should the design matrix and contrast matrix look like?  I  
>> tried the
>>  > matrices below (as well as other variations) without any luck.   
>> And, given
>>  > the correct design and contrast matrices, how do I interpret  
>> the results
>>  > to get the answer I want?  (e.g. I want to find genes in which  
>> "combo" >
>>  > "x" + "y".)
>> What do you mean by 'without any luck'? The fourth contrast below  
>> should
>> give you what you want (Combo - x - y + control).
>> Best,
>> Jim
>>  >
>>  > Thanks much,
>>  > Suzanne
>>  >
>>  >> design
>>  >                         x       y       Combo           Control
>>  > x.cel                   1       0       0               1
>>  > x.cel                   1       0       0               1
>>  > y.cel                   0       1       0               1
>>  > y.cel                   0       1       0               1
>>  > control.cel             0       0       0               1
>>  > control.cel             0       0       0               1
>>  > combo.cel               1       1       1               1
>>  > combo.cel               1       1       1               1
>>  >
>>  >
>>  >> contrast.matrix
>>  >
>>  >         combo-control   x-control       y-control
>>  > x                       0               1               0
>>  > y                       0               0               1
>>  > combo                   1               0               0
>>  > control         -1              -1              -1
>>  >
>>  >
>>  >                  [[alternative HTML version deleted]]
>>  >
>>  > _______________________________________________
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>>  > Search the archives: http://news.gmane.org/ 
>> gmane.science.biology.informatics.conductor
>> -- 
>> James W. MacDonald, M.S.
>> Biostatistician
>> Douglas Lab
>> University of Michigan
>> Department of Human Genetics
>> 5912 Buhl
>> 1241 E. Catherine St.
>> Ann Arbor MI 48109-5618
>> 734-615-7826
>
> -- 
> James W. MacDonald, M.S.
> Biostatistician
> Douglas Lab
> University of Michigan
> Department of Human Genetics
> 5912 Buhl
> 1241 E. Catherine St.
> Ann Arbor MI 48109-5618
> 734-615-7826

--
-----------------------------------------------------
Michal Kolář

Academy of Sciences of the Czech Republic
Institute of Molecular Genetics
Vídeňská 1083
CZ-14220 Praha
Czech Republic

email:	kolarmi at img.cas.cz



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