Dear Gordon,
   
  When using a script that I already asked about (below), I noticed the following.
   
  My Data matrix is for 30 samples, the first column represents probe IDs. I use for the unordered dataset (samples are not ordered in the Data file according to the treatments) the following script:
  > design <- model.matrix(~0 +factor(c(3,2,4,5,1,4,3,6,6,1,2,1,3,5,4,2,5,6,3,4,5,6,1,2,3,4,5,6,1,2)))
  > colnames(design) <- c("Untreated","L1","L2","L1A","L2A","A")
  > contrast.matrix <- makeContrasts(L1-Untreated, L2-Untreated, L1A-Untreated, L2A-Untreated, A-Untreated, L1A-A, L2A-A, L1A-L1, L2A-L2, levels=design)
   
  For the ordered data it should produce the same results in the topTable as the script:
  > design <- model.matrix(~0 +factor(c(1,1,1,1,1,2,2,2,2,2,3,3,3,3,4,4,4,4,4,5,5,5,5,5,6,6,6,6,6,6)))
  > colnames(design) <- c("Untreated","L1","L2","L1A","L2A","A")
  > contrast.matrix <- makeContrasts(L1-Untreated, L2-Untreated, L1A-Untreated, L2A-Untreated, A-Untreated, L1A-A, L2A-A, L1A-L1, L2A-L2, levels=design)
   
  However there are some differences, especially in the AveExpr column:
   
  1. unordered:
            ID     logFC  AveExpr         t      P.Value    adj.P.Val        B
168840 -5.302214 12.51356 -27.83821 3.590400e-09 2.717735e-05 11.23314
101140 -5.175045 12.51114 -27.67796 3.756415e-09 2.717735e-05 11.20135
123375 -4.265825 14.04540 -27.65702 3.778740e-09 2.717735e-05 11.19717
194271 -4.237919 16.31592 -27.05930 4.483564e-09 2.717735e-05 11.07557
142723 -5.529549 12.89764 -26.63683 5.071066e-09 2.717735e-05 10.98684

  2. ordered:
            ID     logFC  AveExpr         t      P.Value    adj.P.Val        B
168840 -5.302013 10.23113 -27.83760 3.589533e-09 2.716231e-05 11.23349
101140 -5.174833 10.22872 -27.68107 3.751573e-09 2.716231e-05 11.20243
123375 -4.265788 11.76289 -27.65844 3.775669e-09 2.716231e-05 11.19792
194271 -4.237924 14.03339 -27.06015 4.480631e-09 2.716231e-05 11.07621
142723 -5.529383 10.61520 -26.63693 5.068864e-09 2.716231e-05 10.98732
   
  Could you please comment on this? Is it essential to order samples in the data file according to treatments before running lmFit? I thought that this should not matter as long as one gets the actual order in the design matrix right.
   
  With kind regards,
  Lev.
   
  My script:
  s<-scan("Data.txt",what='character')
  sm<-matrix(s,byrow=TRUE,ncol=31)
  rownames(sm)<-sm[,1]
  sm<-sm[,2:ncol(sm)]
  snn<-apply(sm,2,as.numeric)
  rownames(snn)<-rownames(sm)
  signals<-snn
   
  temp<-vsn(signals)
  exprs(temp)<-log2(exp(exprs(temp)))
   
  design <- model.matrix(~0 +factor(c(3,2,4,5,1,4,3,6,6,1,2,1,3,5,4,2,5,6,3,4,5,6,1,2,3,4,5,6,1,2)))
   
  colnames(design) <- c("Untreated","L1","L2","L1A","L2A","A")
  contrast.matrix <- makeContrasts(L1-Untreated, L2-Untreated, L1A-Untreated, L2A-Untreated, A-Untreated, L1A-A, L2A-A, L1A-L1, L2A-L2, levels=design)
   
  fit <- lmFit(temp, design)
  fit2 <- contrasts.fit(fit, contrast.matrix)
  fit2 <- eBayes(fit2)
  topTable(fit2, adjust="BH")
   
  > design unordered:
   Untreated L1 L2 L1A L2A A
1          0  0  1   0   0 0
2          0  1  0   0   0 0
3          0  0  0   1   0 0
4          0  0  0   0   1 0
5          1  0  0   0   0 0
6          0  0  0   1   0 0
7          0  0  1   0   0 0
8          0  0  0   0   0 1
9          0  0  0   0   0 1
10         1  0  0   0   0 0
11         0  1  0   0   0 0
12         1  0  0   0   0 0
13         0  0  1   0   0 0
14         0  0  0   0   1 0
15         0  0  0   1   0 0
16         0  1  0   0   0 0
17         0  0  0   0   1 0
18         0  0  0   0   0 1
19         0  0  1   0   0 0
20         0  0  0   1   0 0
21         0  0  0   0   1 0
22         0  0  0   0   0 1
23         1  0  0   0   0 0
24         0  1  0   0   0 0
25         0  0  1   0   0 0
26         0  0  0   1   0 0
27         0  0  0   0   1 0
28         0  0  0   0   0 1
29         1  0  0   0   0 0
30         0  1  0   0   0 0
   
  > design ordered:
   Untreated L1 L2 L1A L2A A
1          1  0  0   0   0 0
2          1  0  0   0   0 0
3          1  0  0   0   0 0
4          1  0  0   0   0 0
5          1  0  0   0   0 0
6          0  1  0   0   0 0
7          0  1  0   0   0 0
8          0  1  0   0   0 0
9          0  1  0   0   0 0
10         0  1  0   0   0 0
11         0  0  1   0   0 0
12         0  0  1   0   0 0
13         0  0  1   0   0 0
14         0  0  1   0   0 0
15         0  0  0   1   0 0
16         0  0  0   1   0 0
17         0  0  0   1   0 0
18         0  0  0   1   0 0
19         0  0  0   1   0 0
20         0  0  0   0   1 0
21         0  0  0   0   1 0
22         0  0  0   0   1 0
23         0  0  0   0   1 0
24         0  0  0   0   1 0
25         0  0  0   0   0 1
26         0  0  0   0   0 1
27         0  0  0   0   0 1
28         0  0  0   0   0 1
29         0  0  0   0   0 1
30         0  0  0   0   0 1
   
  >
> > sessionInfo()
>R version 2.4.1 (2006-12-18)
>i386-pc-mingw32
>
>locale:
>LC_COLLATE=English_United 
>Kingdom.1252;LC_CTYPE=English_United 
>Kingdom.1252;LC_MONETARY=English_United 
>Kingdom.1252;LC_NUMERIC=C;LC_TIME=English_United Kingdom.1252
>
>attached base packages:
>[1] 
>"tools" "stats" "graphics" "grDevices" 
>"utils" "datasets" "methods" "base"
>
>other attached packages:
> vsn Biobase limma
>"1.12.0" "1.12.2" "2.9.8"




 		
---------------------------------

	[[alternative HTML version deleted]]

