Error in designing DESeq2 time pointed experiments
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AZ ▴ 30
@fereshteh-15803
Last seen 4 days ago
United Kingdom

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

LTR DESeq2 • 125 views
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@mikelove
Last seen 3 days ago
United States

The last design is the one we use at the end of the workflow (look up the rnaseqGene workflow)

I strongly recommend working with a statistician who can explain what these designs do rather than just seeing which run without error.

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Thanks a lot

Having > ddsTC <- DESeq(dds, test="LRT", reduced = ~ time + condition) I will have

> resultsNames(ddsTC)
[1] "Intercept"               "time_48_vs_24"           "condition_IT_vs_control"
[4] "time48.conditionIT"
>


I asked somebody and he told me condition_IT_vs_control contrast will give me

the difference of treatment versus control but considering time goes from 24 hours to 48 hours

, 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)

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

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Entering edit mode

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 same

Sorry, how I can get output by ddsTC <- DESeq(dds, test="LRT", reduced = ~ time + time:condition). with no error

I guess the right error is this one