I have a question with respect to DESeq2.
I have one factor with 4 levels (wild-type, mutant A, mutant B, mutantA&B; the wild-type is set as reference). Based on this, I want to do LRT test to get analysis just like ANOVA and then compare two by two among them Because there are no post-hoc test, so I also did multiple pairwise comparison using Wald test. I learned from the tutorial that the LRT test will give only one of the Log2FC among all others. So to confirm that, I try to match the Log2FC given by LRT test's result table with those other Log2FC given by Wald test. However, I just cannot find any of them fully matched. I found one which is very similar. I guessed it may be that; however, I want to know why will this happen? And I found difficult to understand how the output of coef() translate into LFC? Can anybody help explain to me?
The R code is shown below:
dds <- DESeqDataSetFromMatrix(countData = countData, colData = colData, design = ~class)
dds <- dds[rowSums(counts(dds))>1,]
dds$class <- relevel(dds$class, ref="P.UF1")
### Perform DESeq function to get all MLE & bayes procedure (including MAP)
dds1 <- DESeq(dds,test="LRT",reduced=~1)
dds2 <- DESeq(dds)
### Perform results function to get the statistics and LFC
res_LRT <- results(dds1)
res_DmmcAvsPUF1 <- results(dds2,contrast=c("class","DmmcA","P.UF1"))
res_DpduPvsPUF1 <- results(dds2,contrast=c("class","DpduP","P.UF1"))
res_DmmcA_pduPvsPUF1 <- results(dds2, contrast=c("class","DpduP_mmcA","P.UF1"))
res_DmmcAvsDpduP <- results(dds2, contrast=c("class","DmmcA","DpduP"))
res_DpduP_mmcAvsDmmcA <- results(dds2, contrast=c("class","DpduP_mmcA","DmmcA"))
res_DpduP_mmcAvsDpduP <- results(dds2, contrast=c("class","DpduP_mmcA","DpduP"))
The 2 columns representing similar log2FCs is shown below.