[BioC] Discrepancy on results from gcrma function and justGCRMA
James W. MacDonald
jmacdon at med.umich.edu
Wed Feb 3 23:31:26 CET 2010
Hi Jenny,
Jenny Drnevich wrote:
> Hi everyone,
>
> I just spent several hours tracking down this problem, as I noticed this
> same discrepancy between the results of justGCRMA() and gcrma() called
> on the same data. There was also another post about this on Nov 4, 2008,
> but I couldn't find where either of them had ever been answered.
I think I missed that one, but the question was asked again and answered
by me late last year.
> HOWEVER, it appears that the discrepancy has been fixed in R 2.10.1
> (gcrma 2.18.1), but it was in R 2.10.0 (gcrma 2.18.0) (examples and
> sessionInfos below).
>
> While I'm glad it has been "fixed", where would this have been
> documented? I didn't think this type of change would have been included
> in a minor version upgrade. What was the explanation for the original
> discrepancy?
The explanation is that justGCRMA() is a function that I wrote several
years ago. In the intervening period the defaults for gcrma() were
changed without making the corresponding changes to justGCRMA().
I made the (unfounded) assumption that the maintainer of the gcrma
package (Jean Wu) was keeping justGCRMA() consistent with gcrma(), which
as you have seen is not true. Since this was an oversight by both me and
Jean, it wasn't documented anywhere.
I have since made the two functions consistent when running under the
default arguments. However, there are some arguments for gcrma() that
are not available for justGCRMA(), so they are not consistent in all cases.
Best,
Jim
>
> Thanks,
> Jenny
>
> #The examples below are not reproducible because you need .CEL files -
> run them on any that you have.
>
> > library(gcrma)
> Loading required package: affy
> Loading required package: Biobase
>
> Welcome to Bioconductor
>
> Vignettes contain introductory material. To view, type
> 'openVignette()'. To cite Bioconductor, see
> 'citation("Biobase")' and for packages 'citation(pkgname)'.
>
> > setwd("K:/Bulla/CELfiles")
> > raw <- ReadAffy()
> > raw
> AffyBatch object
> size of arrays=834x834 features (10 kb)
> cdf=Rat230_2 (31099 affyids)
> number of samples=6
> number of genes=31099
> annotation=rat2302
> notes=
> >
> > gcrma.1 <- gcrma(raw)
> Adjusting for optical effect......Done.
> Computing affinitiesLoading required package: AnnotationDbi
> .Done.
> Adjusting for non-specific binding......Done.
> Normalizing
> Calculating Expression
> >
> > gcrma.2 <- justGCRMA()
> Computing affinities.Done.
> Adjusting for optical effect.......Done.
> Adjusting for non-specific binding......Done.
> Normalizing
> Calculating Expression
> >
> > all.equal(exprs(gcrma.1),exprs(gcrma.2))
> [1] "Mean relative difference: 0.03514035"
> >
> > sessionInfo()
> R version 2.10.0 (2009-10-26)
> i386-pc-mingw32
>
> locale:
> [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United
> States.1252
> [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
> [5] LC_TIME=English_United States.1252
>
> attached base packages:
> [1] stats graphics grDevices utils datasets methods base
>
> other attached packages:
> [1] rat2302probe_2.5.0 AnnotationDbi_1.8.1 rat2302cdf_2.5.0
> gcrma_2.18.0
> [5] affy_1.24.2 Biobase_2.6.0
>
> loaded via a namespace (and not attached):
> [1] affyio_1.14.0 Biostrings_2.14.3 DBI_0.2-4
> IRanges_1.4.4
> [5] preprocessCore_1.8.0 RSQLite_0.7-3 splines_2.10.0
> tools_2.10.0
> >
>
> #Now switch R versions but run same code....
>
> > library(gcrma)
> Loading required package: affy
> Loading required package: Biobase
>
> Welcome to Bioconductor
>
> Vignettes contain introductory material. To view, type
> 'openVignette()'. To cite Bioconductor, see
> 'citation("Biobase")' and for packages 'citation(pkgname)'.
>
> > setwd("K:/Bulla/CELfiles")
> > raw <- ReadAffy()
> > raw
> AffyBatch object
> size of arrays=834x834 features (10 kb)
> cdf=Rat230_2 (31099 affyids)
> number of samples=6
> number of genes=31099
> annotation=rat2302
> notes=
> >
> > gcrma.1 <- gcrma(raw)
> Adjusting for optical effect......Done.
> Computing affinitiesLoading required package: AnnotationDbi
> .Done.
> Adjusting for non-specific binding......Done.
> Normalizing
> Calculating Expression
> >
> > gcrma.2 <- justGCRMA()
> Computing affinities.Done.
> Adjusting for optical effect.......Done.
> Adjusting for non-specific binding......Done.
> Normalizing
> Calculating Expression
> >
> > all.equal(exprs(gcrma.1),exprs(gcrma.2))
> [1] TRUE
> >
> > sessionInfo()
> R version 2.10.1 (2009-12-14)
> i386-pc-mingw32
>
> locale:
> [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United
> States.1252
> [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
> [5] LC_TIME=English_United States.1252
>
> attached base packages:
> [1] stats graphics grDevices utils datasets methods base
>
> other attached packages:
> [1] rat2302probe_2.5.0 AnnotationDbi_1.8.1 rat2302cdf_2.5.0
> gcrma_2.18.1
> [5] affy_1.24.2 Biobase_2.6.1
>
> loaded via a namespace (and not attached):
> [1] affyio_1.14.0 Biostrings_2.14.10 DBI_0.2-5
> IRanges_1.4.9
> [5] preprocessCore_1.8.0 RSQLite_0.8-0 splines_2.10.1
> tools_2.10.1
> >
>
>
>
>
> At 04:31 PM 10/28/2009, Jin wrote:
>> Jerry <norn2k at ...> writes: > > Hi, > Â > I'm currently using gcrma
>> package in R to summarize probeset intensities from CEL files.
>> Surprisingly, > IÂ found that the results generated from gcrma
>> function and justGCRMA function are quite different. In > general,Â
>> expression values from gcrma function are lower and the boxplots
>> from gcrma are quite > asymmetric (no tails on the bottom). I
>> attached some plots below for your information. This confused > me as
>> I thought that the two functions implemented similar algorithms. >
>> Â > Thank you so much for your help! > Â > Best, > Jianjun > > PS:
>> The package I used is gcrma 2.12.1. I also observed similar results
>> on 2.14 version. > > Hello, I'm running into the same problem
>> with gcrma and justGCRMA. They are not giving the same numeric
>> results. Is this an intended feature? I was under the impression that
>> these two methods were identical with the exception that justGCRMA was
>> more memory efficient because it didn't have to create an AffyBatch
>> object. Can anyone shed some light on this subject? Thanks, Jin
>> _______________________________________________ Bioconductor mailing
>> list Bioconductor at stat.math.ethz.ch
>> https://stat.ethz.ch/mailman/listinfo/bioconductor Search the
>> archives:
>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>
> 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
>
> 330 ERML
> 1201 W. Gregory Dr.
> Urbana, IL 61801
> USA
>
> ph: 217-244-7355
> fax: 217-265-5066
> e-mail: drnevich at illinois.edu
--
James W. MacDonald, M.S.
Biostatistician
Douglas Lab
University of Michigan
Department of Human Genetics
5912 Buhl
1241 E. Catherine St.
Ann Arbor MI 48109-5618
734-615-7826
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