gcrma vs. rma
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Stan Smiley ▴ 70
@stan-smiley-567
Last seen 7.3 years ago
Sorry if this should have been sent directly to Zhijin Wu, but here goes... Is there another resource for learning what the gcrma package is all about? Like the theory/rationale behind it and why/how it is better than rma? I must be doing something wrong, but my rma expression levels are the same as what I got from gcrma. Granted I just ran: data <- ReadAffy() eset.rma <- rma(data) eset.gcrma <- gcrma(data) But the expression levels generated were identical. I didn't believe it, so I'm re-running the analysis just to make sure. It's running now, but since gcrma takes so much longer to run, I thought I'd throw this question out now. I've read the "Textual description of gcrma" pdf file, but it's so cursory I'm still left wondering if I just didn't miss the more detailed explanation of the package. Stan Smiley stan.smiley@genetics.utah.edu
gcrma gcrma • 2.1k views
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Ben Bolstad ★ 1.1k
@ben-bolstad-93
Last seen 7.3 years ago
The two routines vary on how the background adjustment is carried out. If you view computing expression values as a three stage process 1. Background Correction 2. Normalization 3. Summarization then in the case of rma() step 1 is a convolution model step 2 is quantile normalization step 3 is a robust multichip model fit using median polish in the case of gcrma() step 1 is a based on a model using GC content step 2 is quantile normalization step 3 is a robust multichip model fit using median polish I would not expect the exact same values from both methods. Thanks, Ben On Fri, 2003-12-12 at 09:22, Stan Smiley wrote: > Sorry if this should have been sent directly to Zhijin Wu, but here goes... > > Is there another resource for learning what the gcrma package is all about? > Like the theory/rationale behind it and why/how it is better than rma? > > I must be doing something wrong, but my rma expression levels are the same > as what I got from gcrma. > > Granted I just ran: > > data <- ReadAffy() > eset.rma <- rma(data) > eset.gcrma <- gcrma(data) > > But the expression levels generated were identical. I didn't believe it, so > I'm re-running the analysis just to make sure. It's running now, but since > gcrma takes so much longer to run, I thought I'd throw this question out > now. > > I've read the "Textual description of gcrma" pdf file, but it's so cursory > I'm still left wondering if I just didn't miss the more detailed explanation > of the package. > > > Stan Smiley > stan.smiley@genetics.utah.edu > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
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Zhijin Wu ▴ 410
@zhijin-wu-438
Last seen 7.3 years ago
Hi, Stan, > > Is there another resource for learning what the gcrma package is all about? > Like the theory/rationale behind it and why/how it is better than rma? here's the paper about the theory behind gcrma http://www.biostat.jhsph.edu/~ririzarr/papers/gcpaper.pdf I am also surprised that you got the same expression values as the rma did. If you send, for example, one array of your data, I may be able to test it. best, Jean
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Well, I'm glad to say the qqplot of the rma vs gcrma is *not* straight after the analysis redo. Thank goodness! Thanks to all who provided me such quick and informative responses! I've got a lot to read up on now... :) Stan Smiley > -----Original Message----- > From: Zhijin Wu [mailto:zwu@jhsph.edu] > Sent: Friday, December 12, 2003 10:35 AM > To: Stan Smiley > Cc: Bioconductor Mailing list > Subject: Re: [BioC] gcrma vs. rma > > > Hi, Stan, > > > > Is there another resource for learning what the gcrma > package is all > > about? Like the theory/rationale behind it and why/how it is better > > than rma? > > here's the paper about the theory behind gcrma http://www.biostat.jhsph.edu/~ririzarr/papers/gcpaper.pdf I am also surprised that you got the same expression values as the rma did. If you send, for example, one array of your data, I may be able to test it. best, Jean
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