[BioC] marray, weights and normalizations..
Henning Redestig
redestig at mpimp-golm.mpg.de
Thu Apr 21 09:28:33 CEST 2005
> This is correct. Limma will do "loess" normalization for you but not print-tip-loess on such data.
I remedied this by "padding out" the Raw file with NA's which were
systematically lacking spots in the last column of each block, this
allowed me to do PT-loess in Limma which does not show the same strange
behaviour as in marray when weights are used.
Another issue has occured though which I have seen on several datasets
now related to using zero weights. Distributionally I get a whole lot
more outliers leading to M values ranging between e.g. -200, 200 an
effect I cant see when using weights of say, 0.1 instead (for all
negatively GenePix flagged genes). Is this to be expected or am I doing
something wrong?
> As far as I know, maNormMain() only handles spot weights on a
> single-array basis. I assume you are aware of that already.
Yes, I was aware of that since you have pointed that out on this list
previously :)
Thanks for the reply!
/Henning
Gordon Smyth wrote:
>
>> Date: Mon, 18 Apr 2005 12:13:03 +0200
>> From: Henning Redestig <redestig at mpimp-golm.mpg.de>
>> Subject: [BioC] marray, weights and normalizations..
>> To: bioconductor at stat.math.ethz.ch
>>
>> Hi,
>>
>> I am trying to use the Lapointe et al, PNAS 2004 data set from SMD
>> consisting of 112 arrays. These are not as I understand it LIMMA
>> compliant since the spots in the raw files are not directly in the
>> spotting order (some spots have been left out)
>> and therefore I decided
>> to use the marray package which seem to be capable of handling even this
>> kind of formatting.
>> Using read.SMD() to import the data seems to work and image() can plot
>> the spots in spatial order indicating that the spotting order
>> information has been kept.
>>
>> Problem arise when I try to normalize the data using maNormMain() as I
>> wish to weight the spots based on their flags.
>
>
> As far as I know, maNormMain() only handles spot weights on a
> single-array basis. I assume you are aware of that already.
>
> Gordon
>
>> Setting w to the weights
>> vector or NULL I get MA-plots as provided indicating a strong dependence
>> between A and M in the lower intensity range when weights are used
>> (lines are lowess fitted lines per print tip). Could anyone enlighten me
>> as to why this is the case? Isnt the whole point of the normalization to
>> remove any dependence between A and M?
>
>
>> The weights vector was set to 1 for flag=0, 0.1 for flag<=-50 and 0.01
>> for flag<=-75 (GenePix flagging conventions, and weights chosen
>> arbitrarily)
>>
>> Very thankful for help
>
>
>
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