Deseq2 design for one condition over 8 different time point
1
0
Entering edit mode
@thindmarsmission-17577
Last seen 6.2 years ago

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

deseq2 rna-seq design matrix deseq • 4.0k views
ADD COMMENT
2
Entering edit mode
@mikelove
Last seen 1 day ago
United States

If you have replicates that track across time you would use ~rep + time for the full model and ~rep for the reduced model. If you don't have replicates that track across time, you would use ~time for the full model and ~1 for the reduced model.

ADD COMMENT
1
Entering edit mode

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.

ADD REPLY
1
Entering edit mode

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.

ADD REPLY
0
Entering edit mode

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.

ADD REPLY
1
Entering edit mode
Take a look at the workflow (linked from the beginning of the vignette). It has a time series example.
ADD REPLY
0
Entering edit mode

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.

ADD REPLY
0
Entering edit mode

This is a FAQ in the DESeq2 vignette.

ADD REPLY

Login before adding your answer.

Traffic: 853 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6