Question

Filtering genes based on Agilent flags

0

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Mcmahon, Wyatt ▴ 50

@mcmahon-wyatt-2201

Last seen 10.2 years ago

Hello list,

I was wondering if anyone knows of a wt.fun function which will filter genes based on their flags in an Agilent FE file. Using the help, I have found functions for Spot and GenePix files, but nothing for Agilent. Has anyone had this problem?

Thanks in advance,
Wyatt

K. Wyatt McMahon, Ph.D.
Postdoctoral Research Associate - Functional Genomics Center and Services Facility
Texas Tech University
Department of Plant and Soil Sciences
Campus Box 42122
79409

limma agilent microarrays • 1.4k views

ADD COMMENT • link updated 6.7 years ago by Gordon Smyth 51k • written 17.4 years ago by Mcmahon, Wyatt ▴ 50

Gordon Smyth · Answer 1 · 2007-06-20

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John Fernandes ▴ 100

@john-fernandes-1557

Last seen 10.2 years ago

I've written one to find spots noted as "well above background":

wtfun <- function(x) {
         okAboveBG <- x[,"rIsWellAboveBG"]==1 &
x[,"gIsWellAboveBG"]==1
         okSaturated <- x[,"rIsSaturated"]==0 & x[,"gIsSaturated"]==0
         okPopnOutlier <- x[,"rIsFeatPopnOL"]==0 &
x[,"gIsFeatPopnOL"]==0
         okNonUnifOutlier <- x[,"rIsFeatNonUnifOL"]==0 &
x[,"gIsFeatNonUnifOL"==0
         as.numeric(okAboveBG & okSaturated & okPopnOutlier &
okNonUnifOutlier)
}

John

ADD COMMENT • link updated 6.7 years ago by Gordon Smyth 51k • written 17.4 years ago by John Fernandes ▴ 100

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I don't agree with using the "well above background" variables as quality flags. A spot that is near background might simply represent a gene that isn't expressed. The probe might be working correctly and this information should not be lost.

A probe that is never (on any array) well above background should probably be filtered out of downstream analyses, but that is best done by subsetting the EList object rather than by setting quality weights with wt.fun. The weights are designed to selectively down-weight individual spots rather than to act on a whole probe.

ADD REPLY • link 6.7 years ago Gordon Smyth 51k

score 0 · Answer 2 · 2018-03-17

The wt.fun argument for read.maimages() in limma is designed to flag poor quality spots. It is not intended for gene filtering.

Flagging poor quality spots is seldom needed with Agilent microarrays. limma is very robust to a range of spot qualities anyway.

Gene filtering should instead be done after the read step. Don't use wt.fun but instead use the other.columns argument of read.maimages() to read in any Agilent variables you want to use during the filtering step.