[BioC] marray, weights and normalizations..
smyth at wehi.edu.au
Thu Apr 21 02:49:54 CEST 2005
>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
>Message-ID: <4263882F.6000807 at mpimp-golm.mpg.de>
>Content-Type: text/plain; charset=us-ascii; format=flowed
>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)
This is correct. Limma will do "loess" normalization for you but not
print-tip-loess on such data.
> 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. 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?
Yes it is, but it won't do so if you tell it to ignore all the low
intensity spots, which is what you're doing when you set the weights to zero.
In my opinion, filtering low intensity spots is against the spirit of loess
normalization. If you want to filter low intensity spots, you should do it
>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
More information about the Bioconductor