Question

Deseq2 design for one condition over 8 different time point

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thindmarsmission ▴ 10

@thindmarsmission-17577

Last seen 5.6 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 • 3.5k views

ADD COMMENT • link updated 5.5 years ago by Michael Love 41k • written 5.5 years ago by thindmarsmission ▴ 10

score 2 · Accepted Answer · 2018-10-04

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Michael Love 41k

@mikelove

Last seen 4 hours 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 • link 5.5 years ago Michael Love 41k

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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 • link 5.5 years ago thindmarsmission ▴ 10

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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 • link 5.5 years ago Michael Love 41k

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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 • link 5.5 years ago thindmarsmission ▴ 10

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Take a look at the workflow (linked from the beginning of the vignette). It has a time series example.

ADD REPLY • link 5.5 years ago Michael Love 41k

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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 • link 5.5 years ago Teresa • 0

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This is a FAQ in the DESeq2 vignette.

ADD REPLY • link 5.5 years ago Michael Love 41k