[BioC] Filtering before differential analysis

Jenny Drnevich drnevich at illinois.edu
Fri Jan 16 16:55:35 CET 2009

Hi Sally,

Your script is transferring the flags to weights, and in your script, 
only ESTs with a flag of 0 get a weight of 1, and all other spots get 
a weight of 0, which means they are not used at all in the analysis. 
So yes, you are in effect "filtering" out these individual spots by 
setting the weights to 0, which is exactly what Gordon said you 
should not do. I second this opinion for the following reason: a 
"bad" spot is a spot where you had no information whatsoever on what 
the expression level might have been, so the number that you get 
(because you always get a number) has no relationship at all to what 
the real value was and so you should throw it out by giving it a 
weight of 0. However, if you don't measure anything above background 
for a particular spot (which GenePix will flag -50), it's not a "bad" 
spot, because you do have useful information that the expression 
level is below detection, and the number that you get will be 
relatively valid compared to other spots that had detectable 
expression. Would you throw out values of 0 if you got them in any 
other scientific measurement? Likely not, so why throw them out here?


At 11:30 AM 1/15/2009, Sally wrote:
>Is flagging the same as filtering?  In my Limma script it takes only 
>those ESTs with a flag of 0 (which are good spots).
>myfun <- function(x) as.numeric ( x$Flag >0)
>  Is this not the same as filtering?  If I actually remove the 
> absent spots from my Imagene files, then the files each have 
> different lengths and the order of genes is not the same in each file.
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Jenny Drnevich, Ph.D.

Functional Genomics Bioinformatics Specialist
W.M. Keck Center for Comparative and Functional Genomics
Roy J. Carver Biotechnology Center
University of Illinois, Urbana-Champaign

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1201 W. Gregory Dr.
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e-mail: drnevich at illinois.edu

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