[Bioc-devel] Bioc-devel Digest, Vol 40, Issue 3

[Gordon Smyth]

>Date: Wed, 11 Jul 2007 18:02:04 +0100
>From: Wolfgang Huber <huber at ebi.ac.uk>
>Subject: Re: [Bioc-devel] [BioC] Peculiar behaviour of
>         normalize.quantiles (in affy, preprocessCore) if there are NA data
>To: Seth Falcon <sfalcon at fhcrc.org>
>Cc: bioc-devel <bioc-devel at stat.math.ethz.ch>
>Message-ID: <46950D0C.8050301 at ebi.ac.uk>
>Content-Type: text/plain; charset=ISO-8859-1
>
>Hi Seth & Ben,
>
>thanks for your clarifying comments!
>
> > [moved to bioc-devel, where this should have started I think]
>
>Sorry if I have been stepping on feet... the reason for posting to the
>bioc user list was that more than once I have (sadly) seen people
>looking at histogrammes such as that of qx shown in my previous post,
>and using the suggested "cutoff" e.g. to discriminate between expressed
>and un-expressed genes, and the like. I hope that this does not sound to
>presumptuous, but I think it is a good thing to educate users to
>critically assess such results.
>
>Btw, normalizeQuantiles from the limma package appears to deal with NA
>values more gracefully (but it is written in R, hence slower). I think
>it assumes that the missingness mechanism is random.

Yes it does.

The reason the R version is a bit slower than C is mainly because of 
the need to handle NAs and to treat ties carefully. Without these 
considerations, the R implementation is nearly as fast. Try 
normalizeQuantiles(ties=FALSE) for more speed.

Regards
Gordon