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Question: Different p-value using input files with pairwise and multiple condition design
0
gravatar for Louis Kok
11 days 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.

 

 

 

ADD COMMENTlink modified 11 days ago by Michael Love19k • written 11 days ago by Louis Kok0
0
gravatar for Michael Love
11 days ago by
Michael Love19k
United States
Michael Love19k wrote:

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

ADD COMMENTlink written 11 days ago by Michael Love19k

Thanks Michael. 

ADD REPLYlink written 11 days ago by Louis Kok0
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