Hello,

There is an initiative to make Bioconductor packages runnable on Linux ARM64 - https://stat.ethz.ch/pipermail/bioc-devel/2023-January/019398.html

We face an error while running CMD check for DESeq2:

> ### ** Examples
> 
> 
> # some artificial data
> cts <- matrix(c(80,50,1,100,
+                 1,1,60,100,
+                 0,50,60,100), ncol=4, byrow=TRUE)
> # make a DESeqDataSet
> dds <- DESeqDataSetFromMatrix(cts,
+   data.frame(row.names=seq_len(ncol(cts))), ~1)
converting counts to integer mode
> colnames(dds) <- paste0("sample",1:4)
> 
> # note! here you would instead use
> # estimateSizeFactors() to do actual normalization
> sizeFactors(dds) <- rep(1, ncol(dds))
> 
> norm.cts <- counts(dds, normalized=TRUE)
> 
> # 'pure' should also have normalized counts...
> pure <- matrix(c(10,0,0,
+                  0,0,10,
+                  0,10,0), ncol=3, byrow=TRUE)
> colnames(pure) <- letters[1:3]
> 
> # for real data, you need to find alpha after fitting estimateDispersions()
> mix <- unmix(norm.cts, pure, alpha=0.01)
Warning in sqrt(alpha * q) : NaNs produced
Error in optim(par = rep(1, ncol(pure)), fn = sumLossVST, gr = NULL, i,  : 
  L-BFGS-B needs finite values of 'fn'
Calls: unmix -> lapply -> lapply -> FUN -> optim
Execution halted

Full logs: https://yikun.github.io/bioconductor-0301/report/DESeq2/kunpeng1-checksrc.html

The problem seems to be around here - https://github.com/mikelove/DESeq2/blob/master/R/helper.R#L93-L97 But I don't understand it well enough yet to propose an improvement.

Any ideas ?

Thanks! Martin

My guess is that something negative is sneaking in, but p is supposed to be non-negative by the bounds I set in L-BFGS-B. pure is positive.

I can look into it. But since it doesn't generate an error on my side, do you have recommendations how to test?