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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 between treatment and control considering time point 2 hours to 4 hours

I have done like this

dds <- DESeqDataSetFromMatrix(countData=a,colData=design, design=~time + condition + time:condition)

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

> resultsNames(ddsTC)
[1] "Intercept"                "condition_t_vs_control"  
[3] "time"                     "conditiont.time"

What is the difference of the results of these codes

results(ddsTC, name="condition_t_vs_control", test="Wald")

versus

results(ddsTC, name="conditiont.time", test="Wald")

Actually I want to know what condition_t_vs_control gives and what conditiont.time gives

Thank you so much for any intuition

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1 Answer 1

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condition_t_vs_control gives the effect of condition, conditiont.time is the interaction of condition and time. If you wanted to test the effect of time, use name="time".

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  • $\begingroup$ Thank you, using which contrast I can get the difference of IT versus control but considering time goes from 24 hours to 48 hours? $\endgroup$
    – Zizogolu
    Commented Oct 19, 2021 at 16:35
  • $\begingroup$ Just condition_IT_vs_control, since time is compensated for by fitting all coefficients at the same time (let me know if that phrasing is confusing). $\endgroup$
    – Devon Ryan
    Commented Oct 19, 2021 at 19:22
  • $\begingroup$ Sorry @Devon Ryan I get error for ddsTC <- DESeq(dds, test="LRT", reduced = ~ time + time:condition) 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 what should I do please ? $\endgroup$
    – Zizogolu
    Commented Oct 26, 2021 at 16:06
  • $\begingroup$ Make sure to specify the full model, I don't know what that defaults to. $\endgroup$
    – Devon Ryan
    Commented Oct 26, 2021 at 16:24
  • $\begingroup$ Thank you so much for your answer, I think this is my full model dds <- DESeqDataSetFromMatrix(countData=a,colData=design, design=~time + condition + time:condition) am I right? design=~time + condition + time:condition When I try to reduce that by removing reduced = ~ time + time:condition I get error $\endgroup$
    – Zizogolu
    Commented Oct 26, 2021 at 17:25

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