I have a fairly complex microarray design (at least for me) involving a cross-over design with repeated measurements. The main effect of interest is the type of exercise (Load and Volume), with muscle biopsy performed pre and post. Each subject was subjected to one of the exercise types for 1 month, measured pre-and post-challenge then allowed a wash-out period before being subjected to the other exercise type for a month, and measured pre-and post-challenge. It will look like this:

df <- data.frame(Time = factor(rep(c("Pre","Post"), each=1, 4)), 
                              Type = factor(rep(c("Volume", "Load"), each=2)), 
                              Subject = factor(rep(1:12, each = 4))[1:48])
df

   Time   Type Subject
1   Pre Volume       1
2  Post Volume       1
3   Pre   Load       1
4  Post   Load       1
5   Pre Volume       2
6  Post Volume       2
7   Pre   Load       2
8  Post   Load       2
9   Pre Volume       3
10 Post Volume       3
11  Pre   Load       3
12 Post   Load       3
13  Pre Volume       4
14 Post Volume       4
15  Pre   Load       4
16 Post   Load       4
17  Pre Volume       5
18 Post Volume       5
19  Pre   Load       5
20 Post   Load       5
21  Pre Volume       6
22 Post Volume       6
23  Pre   Load       6
24 Post   Load       6
25  Pre Volume       7
26 Post Volume       7
27  Pre   Load       7
28 Post   Load       7
29  Pre Volume       8
30 Post Volume       8
31  Pre   Load       8
32 Post   Load       8
33  Pre Volume       9
34 Post Volume       9
35  Pre   Load       9
36 Post   Load       9
37  Pre Volume      10
38 Post Volume      10
39  Pre   Load      10
40 Post   Load      10
41  Pre Volume      11
42 Post Volume      11
43  Pre   Load      11
44 Post   Load      11
45  Pre Volume      12
46 Post Volume      12
47  Pre   Load      12
48 Post   Load      12

I’m not quite sure how to make the design to investigate the difference within the type of exercise (Pre vs Post) but also between (Load vs Volume). Any suggestion would be appreciated.

sessionInfo( )

R version 4.0.4 (2021-02-15)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] limma_3.46.0        affy_1.68.0         Biobase_2.50.0      BiocGenerics_0.36.0

loaded via a namespace (and not attached):
[1] BiocManager_1.30.13   zlibbioc_1.36.0       compiler_4.0.4        tools_4.0.4           affyio_1.60.0        
[6] tinytex_0.31          preprocessCore_1.52.1 xfun_0.21