Question: Different p-value using input files with pairwise and multiple condition design
0
gravatar for Louis Kok
10 months ago by
Louis Kok0
Singapore
Louis Kok0 wrote:

Hi,

 

I have run DE analysis using different input files. One is with multiple conditions and another one is just pairwise comparison between treatment and control. I found that the p-value is kind of different. The input files are as below:

For multiple conditions, the input file is as below:

condition       replicate       batch
Ctrl_A  1       1
T1_A    1       1
T2_A    1       1
Ctrl_B  1       1
T1_B    1       1
T2_B    1       1
Ctrl_C  1       1
T1_C    1       1
T2_C    1       1
Ctrl_D  1       1
T1_D    1       1
T2_D    1       1
Ctrl_A  2       2
T1_A    2       2
T2_A    2       2
Ctrl_B  2       2
T1_B    2       2
T2_B    2       2
Ctrl_C  2       2
T1_C    2       2
T2_C    2       2
Ctrl_D  2       2
T1_D    2       2
T2_D    2       2
Ctrl_A  3       3
T1_A    3       3
T2_A    3       3
Ctrl_B  3       3
T1_B    3       3
T2_B    3       3
Ctrl_C  3       3
T1_C    3       3
T2_C    3       3
Ctrl_D  3       3
T1_D    3       3
T2_D    3       3

I would like to compare only T1_D and Ctrl_D. The code is as below:

directory="./"
datList=read.table("multiple.input",header=TRUE)
sampleTable=data.frame(datList)

ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable,
                                       directory = directory,
                                       design= ~ batch + condition)

ddsHTSeq$condition <- factor(ddsHTSeq$condition)
#dds <- estimateSizeFactors(ddsHTSeq)
#nc <- counts(dds, normalized=TRUE)
#filter <- rowSums(nc >= 1) >= 1
#dds <- dds[filter,]
dds <- DESeq(ddsHTSeq)
res <- results(dds, contrast=c("condition", "T1_D","Ctrl_D")
resOrdered <- res[order(res$pvalue),]
resSig <- subset(resOrdered, padj < 0.1)

 

For pairwise conditions (T1_D vs. Ctrl_D), the input file is as below:

condition       replicate       batch
Ctrl_D  1       1
T1_D    1       1
Ctrl_D  2       2
T1_D    2       2
Ctrl_D  3       3
T1_D    3       3

 

The code is as below:

directory="./"
datList=read.table("pairwise.input",header=TRUE)
sampleTable=data.frame(datList)

ddsHTSeq <- DESeqDataSetFromHTSeqCount(sampleTable = sampleTable,
                                       directory = directory,
                                       design= ~ batch + condition)

ddsHTSeq$condition <- relevel(ddsHTSeq$condition, ref = "Ctrl_D")
dds <- DESeq(ddsHTSeq)
res <- results(dds)
resOrdered <- res[order(res$pvalue),]
resSig <- subset(resOrdered, padj < 0.1)

 

 

I found that the number of genes with significant expression is different due to difference in p-value and adjusted p-value when the multiple conditions and pairwise conditions are used separately. Is there some error in the code? Thanks a lot.

 

 

 

deseq2 • 140 views
ADD COMMENTlink modified 10 months ago by Michael Love24k • written 10 months ago by Louis Kok0
Answer: Different p-value using input files with pairwise and multiple condition design
0
gravatar for Michael Love
10 months ago by
Michael Love24k
United States
Michael Love24k wrote:

This is expected and it’s  one of the FAQ in the vignette.

ADD COMMENTlink written 10 months ago by Michael Love24k

Thanks Michael. 

ADD REPLYlink written 10 months ago by Louis Kok0
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