In a given experiment I am modeling `~0 + treatment*time + cell_type`

, for which I have `treatment`

(`Control`

and `Treated`

), `time`

(`T1`

, `T2`

, ...) and `cell_type`

(`cell1`

, `cell2`

, ...). Given that I'm looking at the interaction of `treatment`

and `time`

, not all individual factors will be available (e.g. `treated`

and `t1`

) since these are given as linear combinations of the interactions (`treated:t1`

).

When I do:

```
fit <- lmFit(df, design)
```

I can then extract the coefficients with `fit$coefficients`

:

```
treatmentTreated timeT2 timeT3 ... treatmentTreated.timeT2
gene1 -1.34 2.34 1.23 ... 3.45
gene2 -2.44 3.12 0.23 ... 9.12
gene3 -0.37 1.59 0.76 ... 0.43
...
```

Now the issue is that I'd like to extract all coefficients but I do not have those for `treatmentControl`

, or `timeT1`

, as those will be given by a linear combination of the other columns (or rather, the inverse). I'm wondering how I can extract those given that I have no intercept? What am I missing in the interpretation of this? Thanks in advance