DESeq2 design formula with paired samples
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Entering edit mode
17 months ago
helen ▴ 60

I have 6 subjects 1-6, and would like to identify the differentially expressed genes in condition A vs.B and considering the gender effect.

Here is my coldata:

subject gender  condition
1      m          A
1      m          B
2      m          A
2      m          B
3      f          A
3      f          B
4      f          A
4      f          B
5      m          A
5      m          B
6      f          A
6      f          B


I think the condition is nested in the subject, right? But when I tried the following design formula, DESeq2 returned Error in checkFullRank(modelMatrix)

dds <- DESeqDataSetFromMatrix(countData = acts,
colData = coldata,
design = ~ subject + gender + condition + condition:subject)


Although the following combinations can be processed:

design = ~ subject + condition or

design = ~ condition + gender

But how do I modify my design formula to consider paired samples, gender effects, and conditions (or any interaction) at the same time? Thanks!

DESeq2 RNA-Seq • 821 views
0
Entering edit mode
17 months ago
helen ▴ 60

My updated post is here: How to interpret DESeq2 result?