Same p-adjusted value for all samples
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bjen731 • 0
@2586ad17
Last seen 6 days ago
United Kingdom

Hi.

I've performed my DEseq2 analysis on my samples. However, when I take a look at the resulting output, all of my p-adjusted values are the same for all genes and are equal to 0.9999068. Does this mean I have created an error upstream of analysis?

Also when I take a look at the summary of the results the LFC up and down as 0 for both. Does this indicate no significant log fold changes?

I'd really appreciate any advice on this please.

Thank you!


# deseq2 analysis design

dds1 <- DESeqDataSetFromMatrix(countData = countdata,
                               colData = colData,
                               design = ~ Treatment)

# subset Athero samples

dds1c <- dds1b[,dds1b$Sample == "Athero"]

# set untreated as reference for differential gene expression

dds1c$Treatment <- relevel(dds1c$Treatment, ref = "untreated")

# Run Deseq2

FCdds <- DESeq(dds1c) 

# View results of deseq2 data output 

resFC <- results(FCdds)

# View summary of deseq2 data output

summary(resFC)

out of 17755 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up)       : 0, 0%
LFC < 0 (down)     : 0, 0%
outliers [1]       : 24, 0.14%
low counts [2]     : 0, 0%
(mean count < 0)
[1] see 'cooksCutoff' argument of ?results
[2] see 'independentFiltering' argument of ?results
DESeq2 p-adjusted-value Logfoldchange • 127 views
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@mikelove
Last seen 22 hours ago
United States

This has been asked and answered before on the support site. Here are some tips for searching the support site:

You can use the search bar above but I've found Google is more useful:

site:support.bioconductor.org same padj

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Hi,

Thank you so much! I've had a look at a previous response you made to the same issue someone else had where you mentioned the paper in the link below:

http://www.jstor.org/stable/2346101

Unfortunately, I don't seem to have access to this via my institution.

I was wondering if the reason for the exact same P-adj values for all genes is to do with an error on my part?

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The fact that some adjusted pvalues are identical is a direct consequence of the algorithm and not a problem.

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