[BioC] limma design matrix missing a Date column

James W. MacDonald jmacdon at uw.edu
Thu Feb 20 18:34:03 CET 2014


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]]
>
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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



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