Design formula for pairwise comparison of experimental setup with multiple factors
1
0
Entering edit mode
@94673e37
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
2
Entering edit mode
swbarnes2 ▴ 850
@swbarnes2-14086
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)

http://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#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.

0
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(as.data.frame(res1), file="VN1.C.3hVsVN1.C.1h.csv")