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".) 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]]

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]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > 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

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]] > > > > _______________________________________________ > > Bioconductor mailing list > > Bioconductor at stat.math.ethz.ch > > https://stat.ethz.ch/mailman/listinfo/bioconductor > > 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

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]] >> > >> > _______________________________________________ >> > Bioconductor mailing list >> > Bioconductor at stat.math.ethz.ch >> > https://stat.ethz.ch/mailman/listinfo/bioconductor >> > 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 Kol?? Academy of Sciences of the Czech Republic Institute of Molecular Genetics V?de?sk? 1083 CZ-14220 Praha Czech Republic email: kolarmi at img.cas.cz