[Bioc-devel] [BioC] Peculiar behaviour of normalize.quantiles in affy, preprocessCore) if there are NA data
bmb at bmbolstad.com
bmb at bmbolstad.com
Fri Jul 13 01:36:00 CEST 2007
Is there any chance that you'd consider having limma depend on a "fixed"
version in preprocessCore rather than having your own separate code?
Note, I am not trying to pick on you specifically since I know there are a
number of other quantile normalization implementations in various
packages. Additionally my personal stance has always been that I am not
going to play policeman on this issue and developers are free to make
there own choices.
In any case, addressing this issue is push to the top of my stack (likely
this upcoming weekend).
>>[moved to bioc-devel, where this should have started I think]
>>Ben Bolstad <bmb at bmbolstad.com> writes:
>> > Wolfgang,
>> > The code in preprocessCore for quantile normalization shows its legacy
>> > being that it was developed around probe-level Affymetrix data
>> > from CEL files where NA values are not to be expected. There may or
>> > not be comments to that effect in the C code documentation (actually
>> > there is further down in the qnorm.c file for a slight variation on
>> > implementation).
>> > If you are willing to make the assumption that the missing data
>> > mechanism is "missing at random" then I think the fix is fairly
>> > just estimate the distribution using the non-missing data. If it is
>> > instead driven by say a truncation mechanism a different fix would be
>> > needed.
>> > In either case I don't think the current situation is desirable and
>> > should be fixed.
>>1. Let's add code to check for and raise an error if any NA's are
>> found. This should be easy and can be done quickly.
>>2. Then we could consider adding an argument that allows NA's and
>> handles things under the missing at random assumption, along with
> As noted later by Wolfgang, the normalizeQuantiles() function in
> limma does exactly this.
> Bioc-devel at stat.math.ethz.ch mailing list
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