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)
andddsTC <- 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