**0**wrote:

Using DEseq2, the `lfcShrink`

function with the `apeglm`

method requires a single `coef`

value to be specified (i.e. it does not allow a contrast to be specified). Further explanation in the manual.

Therefore, I am having trouble creating a design matrix that represents my comparison of interest. Here is my example code:

```
cells <- c(rep("A", 6), rep("B", 6))
treat <- c(rep("C", 3), rep("T", 3), rep("C", 3), rep("T", 3))
replicate <- c(rep(c(1:3), 4))
group <- rep(c("W", "X", "Y", "Z"), each = 3)
colData <- data.frame(sample_id = paste0(cells, "_", treat, "_", replicate), cells, treat, replicate, group)
colData$cells <- factor(colData$cells, levels = c("A", "B"))
colData$treat <- factor(colData$treat, levels = c("C", "T"))
colData$group <- factor(colData$group, levels = c("W", "X", "Y", "Z"))
design1 <- model.matrix(~ cells + treat + cells:treat, data = colData)
design2 <- model.matrix(~ group, data = colData)
```

And the relevant output:

```
> colData
sample_id cells treat replicate group
1 A_C_1 A C 1 W
2 A_C_2 A C 2 W
3 A_C_3 A C 3 W
4 A_T_1 A T 1 X
5 A_T_2 A T 2 X
6 A_T_3 A T 3 X
7 B_C_1 B C 1 Y
8 B_C_2 B C 2 Y
9 B_C_3 B C 3 Y
10 B_T_1 B T 1 Z
11 B_T_2 B T 2 Z
12 B_T_3 B T 3 Z
> design1
(Intercept) cellsB treatT cellsB:treatT
1 1 0 0 0
2 1 0 0 0
3 1 0 0 0
4 1 0 1 0
5 1 0 1 0
6 1 0 1 0
7 1 1 0 0
8 1 1 0 0
9 1 1 0 0
10 1 1 1 1
11 1 1 1 1
12 1 1 1 1
attr(,"assign")
[1] 0 1 2 3
attr(,"contrasts")
attr(,"contrasts")$cells
[1] "contr.treatment"
attr(,"contrasts")$treat
[1] "contr.treatment"
> design2
(Intercept) groupX groupY groupZ
1 1 0 0 0
2 1 0 0 0
3 1 0 0 0
4 1 1 0 0
5 1 1 0 0
6 1 1 0 0
7 1 0 1 0
8 1 0 1 0
9 1 0 1 0
10 1 0 0 1
11 1 0 0 1
12 1 0 0 1
attr(,"assign")
[1] 0 1 1 1
attr(,"contrasts")
attr(,"contrasts")$group
[1] "contr.treatment"
```

I want to compare T vs C treatments within only the A cells. This seems easy with `design2`

, by specifying `coef = 2`

(i.e. groupX). In that case, the baseline levels are A cells and C treatment. However, I cannot understand how to use an additive (interaction) formula in the model.matrix function (i.e. `design1`

), where explicitly naming multiple factors (e.g. cells, treat) will produce a design matrix to represent this comparison?

Thanks!

**22k**• written 8 days ago by toddknutson •

**0**