DESeq2 lfcShrink with interactions
1
0
Entering edit mode
@hannepainter-19708
Last seen 5.5 years ago

Dear Bioconductor Community,

I am using DESeq2 to analyse a mouse RNAseq dataset and have an identical study design to one described in in example section of ?results.I have pasted below:

## Example 3: two conditions, three genotypes

# Using interaction terms

dds <- makeExampleDESeqDataSet(n=100,m=18)
dds$genotype <- factor(rep(rep(c("I","II","III"),each=3),2))
design(dds) <- ~ genotype + condition + genotype:condition
dds <- DESeq(dds)
resultsNames(dds)

# the condition effect for genotype I (the main effect)
results(dds, contrast=c("condition","B","A"))

# the condition effect for genotype III.
# this is the main effect *plus* the interaction term
# (the extra condition effect in genotype III compared to genotype I).
results(dds, contrast=list( c("condition_B_vs_A","genotypeIII.conditionB") ))

I am specifically interested in looking at the condition effect for genotypes I-III and have adapted the contrasts listed above for my own dataset. However, I am struggling to perform lfcShrink() using types "apeglm" and "ashr".

Does any one have any suggestions on how to perform log fold change shrinkage on this design?

I look forward to your replies.

deseq2 lfcShrink interactions • 2.2k views
ADD COMMENT
0
Entering edit mode
@mikelove
Last seen 16 hours ago
United States

There is a section in the vignette where we show how to arrange various contrasts so they are a single coefficient in the design and therefore can be used with apeglm.

Note that ashr can work with a results table alone, so it works already without rearrangement.

ADD COMMENT
0
Entering edit mode

Hello Michael, I think I'm having a similar issue, and although I went to look in the vignette to solve the problem, I'm still confused. Basically I have RNA-seq data for two tissues (A and C) exposed to 3 different conditions (M, C, D). I'm using design = ~ tissue + treatment + tissue:treatment and my reference level was set to condition M

resultsNames(dds)
[1] "Intercept"             "tissue_C_vs_A"       "treatment_D_vs_M"     
[4] "treatment_HD_vs_M"     "tissueC.treatmentD"  "tissueC.treatmentHD"

To test for the effect of D vs M in tissue C, and the effect of HD vs M in tissue C, I use:

res.C.DvsM <- results(dds, contrast=list( c("treatment_D_vs_M","tissueC.treatmentD") ), lfcThreshold=0.5)

res.C.HDvsM <- results(dds, contrast=list( c("treatment_HD_vs_M","tissueC.treatmentD") ), lfcThreshold=0.5)

How can I arrange the contrasts in order to set a single coefficient and use lfcshrink() with type="apeglm" in this case ? It was not very clear to me in the tutorial.

Thank's in advance, Pedro

ADD REPLY
0
Entering edit mode

You can use a design of ~tissue + tissue:treatment such that each tissue will have its own treatment coefficient, which can be used with lfcShrink and type="apeglm". This design is equivalent to what you have above, it just rearranges the terms so you don't have to add the coefficients together.

ADD REPLY
0
Entering edit mode

Yes, it's also a bit more simple. Thank you for the quick reply!

ADD REPLY

Login before adding your answer.

Traffic: 663 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