Hello,
I apologize if this question was answered many times before. I'm a little bit confused by DEseq2 coefficient. I have two factors, genotype (WT, KO) and batch (B1, B2, B3) variables and would like to see gene expression between WO and KO while accounting for batch effect. I came across a similar post and I'm just not sure if pulling coefficient by results(dds, contrast=c("genotype","KO","WT"))
would be genotype effect within Batch B1 (reference level) or overall difference between genotype. i.e. sample 1~6 (WT) vs sample 7 ~ 12 (KO).
library(DESeq2)
library(tidyverse)
dds <- makeExampleDESeqDataSet(n = 1000, m = 12, betaSD = 2)
dds$genotype <- factor(rep(c("WT", "KO"), each = 6))
dds$genotype <- relevel(dds$genotype, "WT")
dds$batch <- factor(rep(c("B1", "B2", "B3"), 4))
dds$batch <- relevel(dds$batch, "B1")
colnames(dds) <- paste0("sample", 1:ncol(dds))
design(dds) <- ~1 + batch + genotype
dds <- DESeq(dds)
resultsNames(dds)
mod_mat <- model.matrix(design(dds), colData(dds))
results(dds, contrast=c("genotype","KO","WT"))
> mod_mat
(Intercept) batchB2 batchB3 genotypeKO
sample1 1 0 0 0
sample2 1 1 0 0
sample3 1 0 1 0
sample4 1 0 0 0
sample5 1 1 0 0
sample6 1 0 1 0
sample7 1 0 0 1
sample8 1 1 0 1
sample9 1 0 1 1
sample10 1 0 0 1
sample11 1 1 0 1
sample12 1 0 1 1
Thanks a lot, Dr. Love.
I'm sorry. I should've paid more attention to the vignettes.