Originally posted by dpryan
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The strange is that after I use the count outlier detection by DESeq2 (if I don't filter before DE analysis)
Why outliers have fold change but not outliers have NA fold change and P-value?
and why the first two genes have P-value but not have adjust P-value?
Command in R are bold
W<-res$stat
maxCooks<-apply(assays(dds)[["cooks"]],1,max)
idx<-!is.na(W)
head(res[which(idx=="TRUE"),],100)
DataFrame with 100 rows and 6 columns
baseMean log2FoldChange lfcSE stat pvalue
<numeric> <numeric> <numeric> <numeric> <numeric>
ENSBTAG00000000005 1.0597616 0.6512851 0.4803849 1.3557569 0.1751765
ENSBTAG00000000008 0.8508167 0.2153765 0.4600089 0.4682007 0.6396411
ENSBTAG00000000010 2.9979379 0.2802807 0.5104307 0.5491062 0.5829326
... ... ... ... ... ...
ENSBTAG00000000191 1.4469456 0.03588896 0.4931081 0.07278113 0.9419803
ENSBTAG00000000195 0.4348506 -0.15788350 0.3280363 -0.48129882 0.6303041
ENSBTAG00000000197 3.0236299 -0.08213013 0.5141906 -0.15972703 0.8730961
padj
<numeric>
NA
NA
0.9626562
... ...
NA
NA
0.9892849
head(res[which(idx=="FALSE"),],100)
DataFrame with 100 rows and 6 columns
baseMean log2FoldChange lfcSE stat pvalue
<numeric> <numeric> <numeric> <numeric> <numeric>
ENSBTAG00000000003 0 NA NA NA NA
ENSBTAG00000000011 0 NA NA NA NA
ENSBTAG00000000020 0 NA NA NA NA
... ... ... ... ... ...
ENSBTAG00000000437 0 NA NA NA NA
ENSBTAG00000000438 0 NA NA NA NA
ENSBTAG00000000441 0 NA NA NA NA
padj
<numeric>
NA
NA
NA
... ...
NA
NA
NA
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