[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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>> 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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