[BioC] Missing Values after cyclic loess in limma

[Wolfgang Huber]

Hi Claus

if there is a chance that affine functions might already do a good enough job for you, compared to loess' local polynomials, then "vsn" might be an option for you, which is intended to be more numerically robust.

	Best wishes
	Wolfgang
  
Il giorno Nov 2, 2012, alle ore 6:45 PM, "Claus Mayer [guest]" <guest at bioconductor.org> ha scritto:

> 
> Hello,
> 
> I am just working on my first ever single channel Agilent array data set. Because I do expect large changes in differential expression I wanted to use the cyclic loess normalisation within limma rather than quantile normalisation. I used the default settings i.e. 
> 
> y<-normalizeBetweenArrays(x,method="cyclicloess")
> 
> where x is the ELlistRaw object. As expected this took a while but to my surprise produced hundreds of missing values for each array as indicated by the message
> 
> Warning message:
> In log2(Recall(object$E, method = method, ...)) : NaNs produced
> 
> I checked the raw values which are all well above 0 and include no NAs. I also did not use any background correction, so I don't quite understand why logging should produce any missing values. I had assumed that the method would first log and then apply the cyclic loess algorithm, which in itself shouldn't produce any NAs either. Have I misunderstood something basic here?
> 
> Thanks,
> 
> Claus
> 
> 
> 
> -- output of sessionInfo(): 
> 
> R version 2.13.0 (2011-04-13)
> Platform: i386-pc-mingw32/i386 (32-bit)
> 
> other attached packages:
> [1] limma_3.8.2    
> 
> --
> Sent via the guest posting facility at bioconductor.org.
> 
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at r-project.org
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor