edgeR FDR always 1
1
0
Entering edit mode
2.1 years ago
AngAdd • 0

Hi everyone,

I'm doing the differential expression analysis of miRNAs by using edgeR. I have 3 normal samples and 3 cancer samples. At the end I have this result, where FDR are always 1.

Am I doing something wrong? (I'm new in bioinformatics..)

    mydata <- read.table("provaR.txt",header = TRUE, check.names = FALSE)
    cpm_data <- cpm(data_clean)
    group <- c('normal','normal','normal','cancer','cancer','cancer')
    y <- DGEList(counts = cpm_data, group = group)
    y <- calcNormFactors(y)
    y <- estimateDisp(y)         
    et <- exactTest(y)
    results_edgeR <- topTags(et)
    results_edgeR$table

                  logFC   logCPM     PValue FDR
hsa-miR-10395-3p  2.1245133 2.067156 0.02247458   1
hsa-miR-4479     -2.8776329 1.622607 0.03125763   1
hsa-miR-125a-3p  -0.6333918 4.525262 0.04110584   1
hsa-mir-6858     -1.5911778 2.404987 0.04391790   1
hsa-mir-1272      2.0010084 2.137744 0.04611976   1
hsa-miR-654-3p   -1.7058564 2.246162 0.04907249   1
hsa-miR-497-5p   -0.5813002 4.440483 0.05123472   1
hsa-mir-409       1.1249962 2.713441 0.05229014   1
hsa-mir-935      -0.5925923 4.329391 0.05611091   1
hsa-mir-3187     -0.5953264 4.344462 0.06414303   1
edgeR FDR differentialexpression miRNA • 733 views
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3
Entering edit mode
2.1 years ago

For starters, I'm pretty sure you are not supposed to put cpm into DGEList. It wants raw counts. So fix that first.

If your data says there are no significant differences, then that's what it says. Either there is no real difference, or your samples are so variable that you can't be sure there's a difference with only n=3. (Is there a chance that your samples are not in the order normal, normal, normal, cancer, cancer cancer?)

You can do t-tests in Excel...they are not as good as EdgeR, but they will give you a ballpark idea as to whether or not you should expect some genes to be different between the groups.

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Entering edit mode

Yes, my samples are in this order: normal, normal, normal, cancer, cancer, cancer. Thank you so much!

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