[BioC] multiple level factors contrast in nbinomLRT, DESeq2.

[sh. chunxuan]

Hi Mike, Simon, 
Thanks very much for the quick answers. 
I moved from DESeq, in which like hood ratio test is used for model comparison, so the the idea just sticked to my mind. 
Later I saw on the other vignette there is a description of the similar situation specifying "which means that we want to test for the effect of treatment (the last factor), controlling for the effect of patients (the first factor)".
Thanks again and best,
Chunxuan


Date: Wed, 20 Aug 2014 14:43:18 +0200
Subject: Re: [BioC] multiple level factors contrast in nbinomLRT, DESeq2.
From: michaelisaiahlove at gmail.com
To: hibergo at outlook.com
CC: bioconductor at r-project.org

Hi Chunxuan,

On Aug 20, 2014 12:38 PM, "sh. chunxuan" <hibergo at outlook.com> wrote:

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> Dear list,

> I am not sure the correct way to interpret the nbinomLRT results in multiple level factors condition.

> Here is a toy example. I would to find DE genes after controlling batch effect in the experiments, in which there are multiple levels.

> ## make data library(DESeq2)dds <- makeExampleDESeqDataSet(m = 18)colData <- data.frame(row.names = rownames(colData(dds)), sample = colData(dds)$sample, condition = rep(LETTERS[1:6], each = 3), batch = factor(rep(c(1, 1, 2), 6)))dds <- DESeqDataSetFromMatrix(counts(dds), colData = colData, design = ~ batch + condition)dds <- estimateSizeFactors(dds)dds <- estimateDispersions(dds)## LRTestdds <- nbinomLRT(dds, reduced = formula(~ batch ))resultsNames(dds)[1] "Intercept"        "batch_2_vs_1"     "condition_B_vs_A" "condition_C_vs_A" "condition_D_vs_A" "condition_E_vs_A" "condition_F_vs_A"res.1 <- results(dds, name = "condition_B_vs_A")res.2 <- results(dds, contrast = list("condition_B_vs_A", "batch_2_vs_1")


> Questions:1.) I would like to get the DE genes between B and A, while controlling for the batch effect.
You should use the default Wald test for such a comparison, not the LRT. See the vignette for an explanation of the difference between the two tests.
So simply use DESeq() and then use:
results(dds, contrast = c("condition", "B", "A"))

> Should I take "res.1" or "res.2", or both are wrong? and what is the correct way to do it?

> 2.) Why "res.3 <- results(dds, contrast = c("condition", "A", "b"))" gave error: "Error in normalizeSingleBracketSubscript(j, x) :   subscript contains invalid names"

This code gives an error because lowercase "b" is not a level. (It should be giving a more understandable error message, not sure why it is not doing so here.)
> 3.) In order to get DE genes between conditions not directly listed in the "resultsNames", is the following codes correct? should "batch_2_vs_1" be included int the contrast?##for example, DE between C and F, controlling for batch effect;res.4 <- results(dds, contrast = list("condition_C_vs_A", "condition_F_vs_A")

Check the help for ?results and the examples there. You should simply use:
contrast = c("condition", "C", "F")

Mike

> Best, Chunxuan

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