Design formula for pairwise comparison of experimental setup with multiple factors
Entering edit mode
Last seen 8 months ago

I have RNAseq with multiple factors such as 4 genotypes, 2 treatment and 4 time points. The top few lines look like,

 Samples    Genotype    Treatment   Time
 S1        VN1            Control   1hr
 S2        VN1            Control   1hr
 S3        VN1            Stress    1hr
 S4        VN1            Stress    1hr
 S5        VN1            Control   3hr
 S6        VN1            Control   3hr
 S7        VN1            Stress    3hr
 S8        VN1            Stress    3hr

Now I am estimating DEGs using DESeq2 package. My intention is to make pairwise comparisons to see time effect and treatment effect using different combinations. For example,

VN1 at 1hr in Control Vs VN1 at 1hr in Stress
VN1 at 1hr in Control Vs VN1 at 3hr in Control  

Since the experimental setup includes multiple factor,I am a bit confused about the correct design for my purpose. Can anyone help?

DEGs DESeq2 • 295 views
Entering edit mode
swbarnes2 ▴ 850
Last seen 7 hours ago
San Diego

To compare small subgroups of your data, do what the vignette says here. (even though the section is on interactions, your questions do not involve using interactions)

You need to make a new column of sample data that combines the others, then make that your design, and contrast one subgroup with another.

Entering edit mode

Thanks. I combined all three factors into one and used contrast function to make comparisons among subgroups. Is the following method correct?

dds <- DESeq(dds)
res1 <-results(dds, contrast=c("condition","VN1.C.3h","VN1.C.1h"), independentFiltering=TRUE, alpha=0.05, pAdjustMethod="BH", parallel=TRUE)
res1 <- lfcShrink(dds, contrast=c("condition","VN1.C.3h","VN1.C.1h"), res=res1)
write.csv(, file="VN1.C.3hVsVN1.C.1h.csv")

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