Hello everyone,
I ran a RNASeq pipeline analysis previously with DESeq2 version 1.18; now, with version 1.20, I am getting different p-values that, ultimately influences the number of DE genes (~200 different genes).
I was reading the changes about the changes in versions and the only change I think could be involved is the "minmu" argument of DESeq, which was not present in 1.18. Can this be the answer?
Thanks!
I didn’t change the value of minmu (it was 0.5 before and after), I only elevated it to an argument, rather than an internal parameter. It was exposed for the single cell integration.
So that’s not the cause of any changes in pvalues. I can’t think of any difference between these versions. Can you give summary(abs(res$stat - res2$stat)) ?
I happen to have both versions on my laptop, and I get at most 2 x 10^-5 differences in adjusted p-value. I don't think there was any relevant change in the statistical routine between these versions (there was a bug in the single cell integration that I fixed, but you didn't mention using ZINB-WaVE estimated weights).
Is it possible you were using a version earlier than 1.18?
R 3.4:
> packageVersion("DESeq2")
[1] ‘1.18.1’
> set.seed(1)
> dds <- makeExampleDESeqDataSet()
> dds <- DESeq(dds, quiet=TRUE)
> res <- results(dds)
> save(dds, res, file="deseq2_v1.18.rda")
R 3.5:
> packageVersion("DESeq2")
[1] ‘1.20.0’
> load("deseq2_v1.18.rda")
> dds <- DESeq(dds, quiet=TRUE)
> res2 <- results(dds)
> summary(abs(res$stat - res2$stat))
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.00e+00 6.00e-07 2.00e-06 3.00e-06 4.30e-06 2.23e-05 2
> summary(abs(res$pvalue - res2$pvalue))
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.0e+00 3.0e-07 1.0e-06 1.2e-06 1.8e-06 5.3e-06 3
> summary(abs(res$padj - res2$padj))
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.0e+00 2.0e-07 2.0e-07 5.0e-07 2.0e-07 2.3e-05 3
So, I did what you suggested (with some additions). I had the environment made with v1.18, so I performed the v1.20 analysis and then compared.
First, by comparing the values of the columns:
check1<-vector()
for (i in 1:ncol(res_20)) {
+ check1[i]<-all(res_18[,i]==res_20[,i],na.rm = T)
+ }
check1
[1] TRUE FALSE FALSE FALSE FALSE FALSE
Now, as suggested, I performed the difference between the results
(First of all, check if the rownames are exactly matched)
check2<-all(rownames(res_18) == rownames(res_20)) check2 [1] TRUE
Now, the difference:
for (i in 1:nrow(res_18)) {
+ dif[i,]<-res_20[i,]-res_18[i,]
+ }
dif<-dif[order(dif$padj,decreasing = T),]
head(dif)
baseMean log2FoldChange lfcSE stat pvalue
ENSMUSG00000096992 0 5.169783e-04 1.687938e-03 0.0040201034 2.019885e-03
ENSMUSG00000029190 0 5.193889e-08 2.530548e-05 -0.0001695293 9.630470e-05
ENSMUSG00000112846 0 -5.263351e-06 1.690702e-04 0.0001355298 7.715936e-05
ENSMUSG00000083431 0 5.882076e-05 3.126852e-04 0.0002190303 1.229127e-04
ENSMUSG00000081093 0 -9.029549e-06 1.883606e-04 -0.0001652798 9.436838e-05
ENSMUSG00000093405 0 -1.054840e-05 1.083485e-04 -0.0001479438 8.400461e-05
padj
ENSMUSG00000096992 0.04924934
ENSMUSG00000029190 0.04891005
ENSMUSG00000112846 0.04887932
ENSMUSG00000083431 0.04887640
ENSMUSG00000081093 0.04887206
ENSMUSG00000093405 0.04886462
As you can see, there is big differences in the adjusted p-value, which can have clear differences between the versions.
Next step is to re-do everything as you did (R 3.4; DESeq2 v1.18 - version I used the first time) and then compare to the current version I have (R 3.5; DESeq2 v1.20)
Note the pvalues are only different by at most .002 right? I’m surprised this aggregates to such a big difference in adjusted pvalues, but it’s possible because of the nature of the method.
Moving forward, the results are not supposed to be identical across versions. Unless there was a regression, which I don’t think there was, why don’t you stick with one version for the analysis?
Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
version 2.3.6
Have a look here, there is a reference to that parameter.
https://github.com/mikelove/DESeq2/blob/a24c0bd71fb4a621a7c0772ca00825db5af5c69b/NEWS#L26
Just started doing some experiments and it seems to be "minmu" indeed that is changing this values. Is there any information about the previous value and/or any information concerning the change?