HI! I have a question, about design matrix in Deseq2, when I don't have any control or conditions. But same sample at different time points for differential expression analysis . I want to do differential expression between different time points. How I should define my Design ?
design(dds) <- ~Time dds <- DESeq(dds, test="LRT") res <- results(dds)
Also, in another case if I have 3 biological replicates for each time point [no treatment/condition] and want to analyse across time points . It should be like:
design(dds) <- ~replicates + time dds <- DESeq(dds, reduced=~replicates, test="LRT") res <- results(dds)
Is it correct way?
I was trying to take a look o another question, but in that case they have conditions.
DESeq2 likelihood ratio test (LRT) design - 2 genotypes, 4 time points
Thanks for your reply Michael,
yes, in one case i have replicates across all time points, I used ~rep+time for full design and ~rep for reduced. I got following results
> resultsNames(dds)
[1] "Intercept" "rep" "time"
Should not I get, like "t1_vs_t2" "t2_vs_t3" etc.. actually, I wanna understand how to interpret it? any suggestions for articles and links. thanks again.
There is a message that DESeq2 prints out, that you may have missed, that tells you about options for modeling numeric covariates.
If you want to treat time as a categorical you need to run factor() on the variable first.
thanks, i got following combinations:(and sorry to bother you again)
> resultsNames(dds)
[1] "Intercept" "rep_a2_vs_a1" "rep_a3_vs_a1" "time_t2_vs_t1" "time_t3_vs_t1" "time_t4_vs_t1" "time_t5_vs_t1" "time_t6_vs_t1" "time_t7_vs_t1" "time_t8_vs_t1"
What is the meaning of "reduced=~rep" and if I want combination of all the time points, what design should i use,(here I can find combinations only with t1 and rest of time points).
Thanks a lot.
Dear Love,
I would like to put you a question related to the design of an RNA-seq experiment. If I have 65 samples and of them, 7 samples are from one condition and the rest from the other condition, could I perform a DE analysis with the total amount of samples in Deseq2 or should I select a subset of 7 samples from those 58 samples from one of the two conditions?
Thank you in advanced.
This is a FAQ in the DESeq2 vignette.