I have a treatment and control in two time points like this

```
> design
X condition time
1 CTRL_24_hrs_replicate1 control 24
2 CTRL_24_hrs_replicate2 control 24
3 CTRL_24_hrs_replicate3 control 24
4 treatment_24_hrs_replicate1 t 24
5 treatment_24_hrs_replicate2 t 24
6 treatment_24_hrs_replicate3 t 24
7 CTRL_48_hrs_replicate1 control 48
8 CTRL_48_hrs_replicate2 control 48
9 CTRL_48_hrs_replicate3 control 48
10 treatment_48_hrs_replicate1 t 48
11 treatment_48_hrs_replicate2 t 48
12 treatment_48_hrs_replicate3 t 48
>
```

I want to test between **treatment** and **control** considering time point 24 hours to 48 hours

I have done like this

```
dds <- DESeqDataSetFromMatrix(countData=a,colData=design, design=~time + condition + time:condition)
But at this part I get error, although I am trying different things
> ddsTC <- DESeq(dds, test="LRT", reduced = ~ time + time:condition)
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
fitting model and testing
Error in nbinomLRT(object, full = full, reduced = reduced, quiet = quiet, :
less than one degree of freedom, perhaps full and reduced models are not in the correct order
```

or

```
> ddsTC <- DESeq(dds, test="LRT", reduced = ~time:condition)
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
fitting model and testing
Error in nbinomLRT(object, full = full, reduced = reduced, quiet = quiet, :
less than one degree of freedom, perhaps full and reduced models are not in the correct order
>
```

I tried these with no error although I am not certain if this makes sense at all

```
> ddsTC <- DESeq(dds, test="LRT", reduced = ~ time + condition)
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
fitting model and testing
>
> ddsTC <- DESeq(dds, test="LRT", reduced = ~ time)
estimating size factors
estimating dispersions
gene-wise dispersion estimates
mean-dispersion relationship
final dispersion estimates
fitting model and testing
```

Al I want is getting the difference of treatment versus control but ** considering** time goes from 24 hours to 48 hours

Thanks for any help

Thanks a lot

Having

`> ddsTC <- DESeq(dds, test="LRT", reduced = ~ time + condition)`

I will haveI asked somebody and he told me

`condition_IT_vs_control`

contrast will give me, since time is compensated for by fitting all coefficients at the same time

Now my problem is if I could get this by this design or not

`ddsTC <- DESeq(dds, test="LRT", reduced = ~ time + condition)`

Please work with someone familiar with linear models in R to help design your analysis and interpret your results.

Thank you so much

I noticed the results of

`ddsTC <- DESeq(dds, test="LRT", reduced = ~ time + condition)`

and`ddsTC <- DESeq(dds, test="LRT", reduced = ~ time + condition)`

is exactly the sameSorry, how I can get output by

`ddsTC <- DESeq(dds, test="LRT", reduced = ~ time + time:condition)`

. with no errorI guess the right error is this one