M vs A plots of affymetrix data
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@michael-watson-iah-c-378
Last seen 10.3 years ago
Hi I have seen many MvsA plots of affymetrix data (eg http://www.stat.ber keley.edu/users/terry/Classes/s246.2002/Week16/week16.pdf) and I want to recreate them for my own data. I realise that I have to take two arrays pairwise to get my ratio(M) and average(A), but does anyone know if these plots are generally at the probe level or at the gene level? If at the probe level, are they the ratio and average of just the PM intensities? Also, when I read data in using ReadAffy(), are the PM and MM intensities raw or on a logged scale? If I then perform rma() or mas5(), are the gene level intensities on a log scale? This is important, as I need to figure out how to calculate the ratio and average Many thanks Mick
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Ben Bolstad ★ 1.2k
@ben-bolstad-1494
Last seen 7.3 years ago
> I realise that I have to take two arrays pairwise to get my ratio(M) > and average(A), but does anyone know if these plots are generally at > the probe level or at the gene level? You can do them at the probe or probeset level. In the document you referenced some were done at the probe level and some were done at the probeset level. > If at the probe level, are they the ratio and average of just the PM > intensities? Typically just PM intensities. > Also, when I read data in using ReadAffy(), are the PM and MM > intensities raw or on a logged scale? If I then perform rma() or > mas5(), are the gene level intensities on a log scale? This is > important, as I need to figure out how to calculate the ratio and > average ReadAffy() returns intensities on the natural scale. rma() expression values are on the log2 scale. mas5() values are natural scale. You of course are free to construct these yourself, but there are some buit-in functions for doint this also. If you have affyPLM loaded you should be able to use the MAplot() function applied to either AffyBatches or exprSets. eg library(affyPLM) data(Dilution) # Dilution is an AffyBatch. # each array against a median-wise synthetic reference array MAplot(Dilution,ylim=c(-2,2)) # comparing arrays 2:4 with array 1 MAplot(Dilution,ylim=c(-2,2),ref=1,which=2:4) # MA plot comparing 1 to 4 MAplot(Dilution,ylim=c(-2,2),ref=1,which=4) #the infamous pairwise plot MAplot(Dilution,pairs=TRUE) eset.rma <- rma(Dilution) #examine to see that they are on log2 scale exprs(eset.rma)[1:5,] # each array against a median-wise synthetic reference array MAplot(eset.rma) eset.mas5 <- mas5(Dilution) #examine to see on natural scale exprs(eset.mas5)[1:5,] #need to tell it to take the log if supplying natural scale #expression values. MAplot(eset.mas5,log=TRUE) -- Ben Bolstad <bmb at="" bmbolstad.com=""> http://bmbolstad.com
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@james-w-macdonald-5106
Last seen 3 hours ago
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michael watson (IAH-C) wrote: > Hi > > I have seen many MvsA plots of affymetrix data (eg > http://www.stat.berkeley.edu/users/terry/Classes/s246.2002/Week16/we ek16.pdf) > and I want to recreate them for my own data. > > I realise that I have to take two arrays pairwise to get my ratio(M) > and average(A), but does anyone know if these plots are generally at > the probe level or at the gene level? > > If at the probe level, are they the ratio and average of just the PM > intensities? > > Also, when I read data in using ReadAffy(), are the PM and MM > intensities raw or on a logged scale? If I then perform rma() or > mas5(), are the gene level intensities on a log scale? This is > important, as I need to figure out how to calculate the ratio and > average Is there any reason not to use e.g., MAplot() or mva.pairs() in the affy package? These functions will do MA plots using the probe level data. If you want the expression values, there is always plotMA() in limma. help(package = "thepackagename") is your friend. Best, Jim > > Many thanks Mick > > _______________________________________________ Bioconductor mailing > list Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor -- James W. MacDonald, M.S. Biostatistician Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623
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@michael-watson-iah-c-378
Last seen 10.3 years ago
Hi Jim The MAplot() help is a little sparse, so I was trying to figure out how to do it from first principles, however I have subsequently found the http://bioinf.wehi.edu.au/marray/jsm2005/lab3/lab3.html lab which gives details on a few more of the arguments. I've just seen Ben's e-mail too, which answers my next question which was going to be about plotting MvsA plots for the normalised data :) Many thanks Mick ________________________________ From: James W. MacDonald [mailto:jmacdon@med.umich.edu] Sent: Thu 09/03/2006 2:57 PM To: michael watson (IAH-C) Cc: bioconductor at stat.math.ethz.ch Subject: Re: [BioC] M vs A plots of affymetrix data michael watson (IAH-C) wrote: > Hi > > I have seen many MvsA plots of affymetrix data (eg > http://www.stat.berkeley.edu/users/terry/Classes/s246.2002/Week16/we ek16.pdf) > and I want to recreate them for my own data. > > I realise that I have to take two arrays pairwise to get my ratio(M) > and average(A), but does anyone know if these plots are generally at > the probe level or at the gene level? > > If at the probe level, are they the ratio and average of just the PM > intensities? > > Also, when I read data in using ReadAffy(), are the PM and MM > intensities raw or on a logged scale? If I then perform rma() or > mas5(), are the gene level intensities on a log scale? This is > important, as I need to figure out how to calculate the ratio and > average Is there any reason not to use e.g., MAplot() or mva.pairs() in the affy package? These functions will do MA plots using the probe level data. If you want the expression values, there is always plotMA() in limma. help(package = "thepackagename") is your friend. Best, Jim > > Many thanks Mick > > _______________________________________________ Bioconductor mailing > list Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor -- James W. MacDonald, M.S. Biostatistician Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623
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@michael-watson-iah-c-378
Last seen 10.3 years ago
Hi Ben Thanks for the help :) When I tried following your example on the affybatch.example data set: eset.rma <- rma(affybatch.example) MAplot(eset.rma) I get an error about there being no direct or inherited method. Mick ________________________________ From: Ben Bolstad [mailto:bmb@bmbolstad.com] Sent: Thu 09/03/2006 3:15 PM To: michael watson (IAH-C) Cc: bioconductor at stat.math.ethz.ch Subject: Re: [BioC] M vs A plots of affymetrix data > I realise that I have to take two arrays pairwise to get my ratio(M) > and average(A), but does anyone know if these plots are generally at > the probe level or at the gene level? You can do them at the probe or probeset level. In the document you referenced some were done at the probe level and some were done at the probeset level. > If at the probe level, are they the ratio and average of just the PM > intensities? Typically just PM intensities. > Also, when I read data in using ReadAffy(), are the PM and MM > intensities raw or on a logged scale? If I then perform rma() or > mas5(), are the gene level intensities on a log scale? This is > important, as I need to figure out how to calculate the ratio and > average ReadAffy() returns intensities on the natural scale. rma() expression values are on the log2 scale. mas5() values are natural scale. You of course are free to construct these yourself, but there are some buit-in functions for doint this also. If you have affyPLM loaded you should be able to use the MAplot() function applied to either AffyBatches or exprSets. eg library(affyPLM) data(Dilution) # Dilution is an AffyBatch. # each array against a median-wise synthetic reference array MAplot(Dilution,ylim=c(-2,2)) # comparing arrays 2:4 with array 1 MAplot(Dilution,ylim=c(-2,2),ref=1,which=2:4) # MA plot comparing 1 to 4 MAplot(Dilution,ylim=c(-2,2),ref=1,which=4) #the infamous pairwise plot MAplot(Dilution,pairs=TRUE) eset.rma <- rma(Dilution) #examine to see that they are on log2 scale exprs(eset.rma)[1:5,] # each array against a median-wise synthetic reference array MAplot(eset.rma) eset.mas5 <- mas5(Dilution) #examine to see on natural scale exprs(eset.mas5)[1:5,] #need to tell it to take the log if supplying natural scale #expression values. MAplot(eset.mas5,log=TRUE) -- Ben Bolstad <bmb at="" bmbolstad.com=""> http://bmbolstad.com
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as I said. You need affyPLM loaded, not just affy. On Thu, 2006-03-09 at 15:33 +0000, michael watson (IAH-C) wrote: > Hi Ben > > Thanks for the help :) > > When I tried following your example on the affybatch.example data set: > > eset.rma <- rma(affybatch.example) > MAplot(eset.rma) > > I get an error about there being no direct or inherited method. > > Mick > > ________________________________ > > From: Ben Bolstad [mailto:bmb at bmbolstad.com] > Sent: Thu 09/03/2006 3:15 PM > To: michael watson (IAH-C) > Cc: bioconductor at stat.math.ethz.ch > Subject: Re: [BioC] M vs A plots of affymetrix data > > > > > > I realise that I have to take two arrays pairwise to get my ratio(M) > > and average(A), but does anyone know if these plots are generally at > > the probe level or at the gene level? > > You can do them at the probe or probeset level. In the document you > referenced some were done at the probe level and some were done at the > probeset level. > > > > If at the probe level, are they the ratio and average of just the PM > > intensities? > > Typically just PM intensities. > > > > Also, when I read data in using ReadAffy(), are the PM and MM > > intensities raw or on a logged scale? If I then perform rma() or > > mas5(), are the gene level intensities on a log scale? This is > > important, as I need to figure out how to calculate the ratio and > > average > > ReadAffy() returns intensities on the natural scale. rma() expression > values are on the log2 scale. mas5() values are natural scale. > > You of course are free to construct these yourself, but there are some > buit-in functions for doint this also. If you have affyPLM loaded you > should be able to use the MAplot() function applied to either > AffyBatches or exprSets. eg > > > library(affyPLM) > data(Dilution) # Dilution is an AffyBatch. > > # each array against a median-wise synthetic reference array > MAplot(Dilution,ylim=c(-2,2)) > > # comparing arrays 2:4 with array 1 > MAplot(Dilution,ylim=c(-2,2),ref=1,which=2:4) > > > # MA plot comparing 1 to 4 > MAplot(Dilution,ylim=c(-2,2),ref=1,which=4) > > > #the infamous pairwise plot > MAplot(Dilution,pairs=TRUE) > > > eset.rma <- rma(Dilution) > > #examine to see that they are on log2 scale > exprs(eset.rma)[1:5,] > > # each array against a median-wise synthetic reference array > MAplot(eset.rma) > > > eset.mas5 <- mas5(Dilution) > > #examine to see on natural scale > exprs(eset.mas5)[1:5,] > > > #need to tell it to take the log if supplying natural scale > #expression values. > MAplot(eset.mas5,log=TRUE) > > > > > -- > Ben Bolstad <bmb at="" bmbolstad.com=""> > http://bmbolstad.com > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor
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