Hello, I am trying to make a design matrix for limma and include date to account for batch effects, but when I construct the matrix, one of the dates is excluded for some reason (1/7/2014). I am interested in comparing the effects of diet within males and females separately. Any ideas why this date would be excluded? This is the targets frame that I read into R: Name FileName Sex PaternalDiet Date 498 498 Julia_01072014_(MoGene-2_0-st).CEL female c 1/7/2014 594 594 Julia_01082014_(MoGene-2_0-st).CEL female c 1/8/2014 721 721 Julia_01072014_(MoGene-2_0-st).CEL female c 1/7/2014 731 731 Julia_01092014_(MoGene-2_0-st).CEL female c 1/9/2014 766 766 Julia_01092014_(MoGene-2_0-st).CEL female c 1/9/2014 439 439 Julia_01092014_(MoGene-2_0-st).CEL female d 1/9/2014 448 448 julia_01072014_(MoGene-2_0-st).CEL female d 1/7/2014 475 475 Julia_01082014_(MoGene-2_0-st).CEL female d 1/8/2014 575 575 Julia_01072014_(MoGene-2_0-st).CEL female d 1/7/2014 704 704 julia_01072014_(MoGene-2_0-st).CEL female d 1/7/2014 749 749 Julia_01082014_(MoGene-2_0-st).CEL female d 1/8/2014 500 500 Julia_01092014_(MoGene-2_0-st).CEL female s 1/9/2014 524 524 Julia_02042014_(MoGene-2_0-st).CEL female s 2/4/2014 580 580 Julia_01072014_(MoGene-2_0-st).CEL female s 1/7/2014 710 710 Julia_01092014_(MoGene-2_0-st).CEL female s 1/9/2014 778 778 Julia_01082014_(MoGene-2_0-st).CEL female s 1/8/2014 797 797 Julia_01092014_(MoGene-2_0-st).CEL female s 1/9/2014 472 472 Julia_01082014_(MoGene-2_0-st).CEL male c 1/8/2014 570 570 Julia_01082014_(MoGene-2_0-st).CEL male c 1/8/2014 573 573 Julia_01092014_(MoGene-2_0-st).CEL male c 1/9/2014 735 735 Julia_01072014_(MoGene-2_0-st).CEL male c 1/7/2014 737 737 Julia_01092014_(MoGene-2_0-st).CEL male c 1/9/2014 771 771 Julia_01082014_(MoGene-2_0-st).CEL male c 1/8/2014 442 442 Julia_01092014_(MoGene-2_0-st).CEL male d 1/9/2014 452 452 Julia_01082014_(MoGene-2_0-st).CEL male d 1/8/2014 579 579 Julia_01092014_(MoGene-2_0-st).CEL male d 1/9/2014 636 636 Julia_01082014_(MoGene-2_0-st).CEL male d 1/8/2014 751 751Julia_01072014_(MoGene-2_0-st).CEL male d 1/7/2014 754 754 Julia_01092014_(MoGene-2_0-st).CEL male d 1/9/2014 503 503 Julia_01092014_(MoGene-2_0-st).CEL male s 1/9/2014 585 585 Julia_01082014_(MoGene-2_0-st).CEL male s 1/8/2014 660 660 Julia_01072014_(MoGene-2_0-st).CEL male s 1/7/2014 714 714 Julia_01072014_(MoGene-2_0-st).CEL male s 1/7/2014 762 762 Julia_01082014_(MoGene-2_0-st).CEL male s 1/8/2014 779 779 Julia_01082014_(MoGene-2_0-st).CEL male s 1/8/2014 470 470 Julia_02042014_(MoGene-2_0-st).CEL female c 2/4/2014 This is the code that I used, and the resulting design matrix: > targets <- readTargets("targets.txt", row.names="Name") > DS <- paste(targets$PaternalDiet, targets$Sex, sep=".") > DS<-factor(DS, levels=c("c.female","d.female","s.female","c.male","d.male","s.male")) > design <- model.matrix(~0+DS+Date, targets) > design DSc.female DSd.female DSs.female DSc.male DSd.male DSs.male Date1/8/2014 498 1 0 0 0 0 0 0 594 1 0 0 0 0 0 1 721 1 0 0 0 0 0 0 731 1 0 0 0 0 0 0 766 1 0 0 0 0 0 0 439 0 1 0 0 0 0 0 448 0 1 0 0 0 0 0 475 0 1 0 0 0 0 1 575 0 1 0 0 0 0 0 704 0 1 0 0 0 0 0 749 0 1 0 0 0 0 1 500 0 0 1 0 0 0 0 524 0 0 1 0 0 0 0 580 0 0 1 0 0 0 0 710 0 0 1 0 0 0 0 778 0 0 1 0 0 0 1 797 0 0 1 0 0 0 0 472 0 0 0 1 0 0 1 570 0 0 0 1 0 0 1 573 0 0 0 1 0 0 0 735 0 0 0 1 0 0 0 737 0 0 0 1 0 0 0 771 0 0 0 1 0 0 1 442 0 0 0 0 1 0 0 452 0 0 0 0 1 0 1 579 0 0 0 0 1 0 0 636 0 0 0 0 1 0 1 751 0 0 0 0 1 0 0 754 0 0 0 0 1 0 0 503 0 0 0 0 0 1 0 585 0 0 0 0 0 1 1 660 0 0 0 0 0 1 0 714 0 0 0 0 0 1 0 762 0 0 0 0 0 1 1 779 0 0 0 0 0 1 1 470 1 0 0 0 0 0 0 Date1/9/2014 Date2/4/2014 498 0 0 594 0 0 721 0 0 731 1 0 766 1 0 439 1 0 448 0 0 475 0 0 575 0 0 704 0 0 749 0 0 500 1 0 524 0 1 580 0 0 710 1 0 778 0 0 797 1 0 472 0 0 570 0 0 573 1 0 735 0 0 737 1 0 771 0 0 442 1 0 452 0 0 579 1 0 636 0 0 751 0 0 754 1 0 503 1 0 585 0 0 660 0 0 714 0 0 762 0 0 779 0 0 470 0 1 attr(,"assign") [1] 1 1 1 1 1 1 2 2 2 attr(,"contrasts") attr(,"contrasts")$DS [1] "contr.treatment" attr(,"contrasts")$Date [1] "contr.treatment" Thanks for your help! Julia [[alternative HTML version deleted]]

Hi Julia, That date isn't excluded; it's absorbed into the other non-date main effects. In other words, you can interpret DSc.female as being the mean expression for that group, on 1/7/2014. The other date coefficients are thus interpreted as the difference in expression levels between a given date and 1/7/2014 (e.g., the Date1/8/2014 coefficient estimates the mean difference between 1/8/2014 and 1/7/2014). But the upshot is that you have corrected for any date-specific batch effect, and you can make the comparisons you are interested in. You could also look at the F-test for the three date coefficients to see if you even need to adjust for date. Best, Jim On 2/20/2014 12:05 PM, Sabet, Julia A wrote: > Hello, > I am trying to make a design matrix for limma and include date to account for batch effects, but when I construct the matrix, one of the dates is excluded for some reason (1/7/2014). I am interested in comparing the effects of diet within males and females separately. Any ideas why this date would be excluded? This is the targets frame that I read into R: > > Name FileName Sex PaternalDiet Date > 498 498 Julia_01072014_(MoGene-2_0-st).CEL female c 1/7/2014 > 594 594 Julia_01082014_(MoGene-2_0-st).CEL female c 1/8/2014 > 721 721 Julia_01072014_(MoGene-2_0-st).CEL female c 1/7/2014 > 731 731 Julia_01092014_(MoGene-2_0-st).CEL female c 1/9/2014 > 766 766 Julia_01092014_(MoGene-2_0-st).CEL female c 1/9/2014 > 439 439 Julia_01092014_(MoGene-2_0-st).CEL female d 1/9/2014 > 448 448 julia_01072014_(MoGene-2_0-st).CEL female d 1/7/2014 > 475 475 Julia_01082014_(MoGene-2_0-st).CEL female d 1/8/2014 > 575 575 Julia_01072014_(MoGene-2_0-st).CEL female d 1/7/2014 > 704 704 julia_01072014_(MoGene-2_0-st).CEL female d 1/7/2014 > 749 749 Julia_01082014_(MoGene-2_0-st).CEL female d 1/8/2014 > 500 500 Julia_01092014_(MoGene-2_0-st).CEL female s 1/9/2014 > 524 524 Julia_02042014_(MoGene-2_0-st).CEL female s 2/4/2014 > 580 580 Julia_01072014_(MoGene-2_0-st).CEL female s 1/7/2014 > 710 710 Julia_01092014_(MoGene-2_0-st).CEL female s 1/9/2014 > 778 778 Julia_01082014_(MoGene-2_0-st).CEL female s 1/8/2014 > 797 797 Julia_01092014_(MoGene-2_0-st).CEL female s 1/9/2014 > 472 472 Julia_01082014_(MoGene-2_0-st).CEL male c 1/8/2014 > 570 570 Julia_01082014_(MoGene-2_0-st).CEL male c 1/8/2014 > 573 573 Julia_01092014_(MoGene-2_0-st).CEL male c 1/9/2014 > 735 735 Julia_01072014_(MoGene-2_0-st).CEL male c 1/7/2014 > 737 737 Julia_01092014_(MoGene-2_0-st).CEL male c 1/9/2014 > 771 771 Julia_01082014_(MoGene-2_0-st).CEL male c 1/8/2014 > 442 442 Julia_01092014_(MoGene-2_0-st).CEL male d 1/9/2014 > 452 452 Julia_01082014_(MoGene-2_0-st).CEL male d 1/8/2014 > 579 579 Julia_01092014_(MoGene-2_0-st).CEL male d 1/9/2014 > 636 636 Julia_01082014_(MoGene-2_0-st).CEL male d 1/8/2014 > 751 751Julia_01072014_(MoGene-2_0-st).CEL male d 1/7/2014 > 754 754 Julia_01092014_(MoGene-2_0-st).CEL male d 1/9/2014 > 503 503 Julia_01092014_(MoGene-2_0-st).CEL male s 1/9/2014 > 585 585 Julia_01082014_(MoGene-2_0-st).CEL male s 1/8/2014 > 660 660 Julia_01072014_(MoGene-2_0-st).CEL male s 1/7/2014 > 714 714 Julia_01072014_(MoGene-2_0-st).CEL male s 1/7/2014 > 762 762 Julia_01082014_(MoGene-2_0-st).CEL male s 1/8/2014 > 779 779 Julia_01082014_(MoGene-2_0-st).CEL male s 1/8/2014 > 470 470 Julia_02042014_(MoGene-2_0-st).CEL female c 2/4/2014 > > This is the code that I used, and the resulting design matrix: > >> targets <- readTargets("targets.txt", row.names="Name") >> DS <- paste(targets$PaternalDiet, targets$Sex, sep=".") >> DS<-factor(DS, levels=c("c.female","d.female","s.female","c.male","d.male","s.male")) >> design <- model.matrix(~0+DS+Date, targets) >> design > DSc.female DSd.female DSs.female DSc.male DSd.male DSs.male Date1/8/2014 > 498 1 0 0 0 0 0 0 > 594 1 0 0 0 0 0 1 > 721 1 0 0 0 0 0 0 > 731 1 0 0 0 0 0 0 > 766 1 0 0 0 0 0 0 > 439 0 1 0 0 0 0 0 > 448 0 1 0 0 0 0 0 > 475 0 1 0 0 0 0 1 > 575 0 1 0 0 0 0 0 > 704 0 1 0 0 0 0 0 > 749 0 1 0 0 0 0 1 > 500 0 0 1 0 0 0 0 > 524 0 0 1 0 0 0 0 > 580 0 0 1 0 0 0 0 > 710 0 0 1 0 0 0 0 > 778 0 0 1 0 0 0 1 > 797 0 0 1 0 0 0 0 > 472 0 0 0 1 0 0 1 > 570 0 0 0 1 0 0 1 > 573 0 0 0 1 0 0 0 > 735 0 0 0 1 0 0 0 > 737 0 0 0 1 0 0 0 > 771 0 0 0 1 0 0 1 > 442 0 0 0 0 1 0 0 > 452 0 0 0 0 1 0 1 > 579 0 0 0 0 1 0 0 > 636 0 0 0 0 1 0 1 > 751 0 0 0 0 1 0 0 > 754 0 0 0 0 1 0 0 > 503 0 0 0 0 0 1 0 > 585 0 0 0 0 0 1 1 > 660 0 0 0 0 0 1 0 > 714 0 0 0 0 0 1 0 > 762 0 0 0 0 0 1 1 > 779 0 0 0 0 0 1 1 > 470 1 0 0 0 0 0 0 > Date1/9/2014 Date2/4/2014 > 498 0 0 > 594 0 0 > 721 0 0 > 731 1 0 > 766 1 0 > 439 1 0 > 448 0 0 > 475 0 0 > 575 0 0 > 704 0 0 > 749 0 0 > 500 1 0 > 524 0 1 > 580 0 0 > 710 1 0 > 778 0 0 > 797 1 0 > 472 0 0 > 570 0 0 > 573 1 0 > 735 0 0 > 737 1 0 > 771 0 0 > 442 1 0 > 452 0 0 > 579 1 0 > 636 0 0 > 751 0 0 > 754 1 0 > 503 1 0 > 585 0 0 > 660 0 0 > 714 0 0 > 762 0 0 > 779 0 0 > 470 0 1 > attr(,"assign") > [1] 1 1 1 1 1 1 2 2 2 > attr(,"contrasts") > attr(,"contrasts")$DS > [1] "contr.treatment" > > attr(,"contrasts")$Date > [1] "contr.treatment" > > Thanks for your help! > Julia > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- James W. 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