Normalize background on marray Agilent object
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@guillermo-marco-puche-5959
Last seen 8.4 years ago
Hello, To read.maimages with Limma do you need to parse Agilent headers from txt files ? I had some troubles with marray pacakge using read.Agilent function. Best, Guillermo. On 06/21/2013 04:18 PM, James W. MacDonald wrote: > Hi Guillermo, > > On 6/21/2013 3:06 AM, Guillermo Marco Puche wrote: >> Dear Gordon, >> >> Thank you for your answer. I'll look further into Agilent array image >> files with limma. >> >> As I said the problem is that i'm not currently reading image from >> Agilent array, but the text data file with marray library and loading it >> into a maData object like this: > > Please note that the read.maimages function doesn't read image files - > it reads in the same text files you are reading with read.Agilent. > > Your original question had to do with the 'correct' background > correction to use for your Agilent array data. Gordon has therefore > suggested that you use the 'normexp' method in limma. This does of > course require you to switch to a different package, but limma tends > to get better support than marray, so you might be wise to make the > switch. > > But to your original point, you are asking a question that might not > have a definitive answer. There is no 'best' way to do a background > correction. There are methods that seem to do a reasonable job over a > range of experiments, and if I understand correctly, this is why > Gordon is suggesting you use normexp. But which method might be best > for your particular situation will be difficult for anybody to predict. > > Best, > > Jim > > >> >> maData = read.Agilent(fnames=input , path=NULL, name.Gf = >> "gMedianSignal", name.Gb = "gBGMedianSignal", name.Rf = >> "rMedianSignal", name.Rb = "rBGMedianSignal", name.W= NULL, layout = >> NULL, gnames = NULL, targets = NULL, notes=NULL, skip=NULL, sep="\t", >> quote="\"", DEBUG=FALSE, info.id=NULL) >> >> >> >> >>> On 06/20/2013 01:11 PM, Gordon K Smyth wrote: >>>> Dera Guillermo, >>>> >>>> The usual process is to (1) background correct the foreground >>>> intensities with respect to the background, then (2) normalize the >>>> M-values (log-ratios). >>>> >>>> For an Agilent two colour array, I do this by: >>>> >>>> library(limma) >>>> RG<- read.maimages(files, source="agilent") >>>> RGb<- backgroundCorrect(RG, method="normexp") >>>> MA<- normalizeWithinArrays(RGb, method="loess") >>>> >>>> although it is sometimes a good idea to remove positive control >>>> probes before the normalization step. >>>> >>>> A recent example using this pipeline is: >>>> >>>> http://www.biomedcentral.com/1471-2105/14/165 >>>> >>>> Best wishes >>>> Gordon >>>> >>>>> Date: Wed, 19 Jun 2013 22:38:34 +0200 >>>>> From: Guillermo Marco Puche<guillermo.marco@sistemasgenomicos.com> >>>>> To: "bioconductor@r-project.org"<bioconductor@r-project.org> >>>>> Subject: [BioC] Normalize background on marray Agilent object >>>>> >>>>> Hello, >>>>> >>>>> I'm currently trying to normalize rBG values for a marray object. >>>>> Data origin is Agilent dual channel array. I've loaded information >>>>> with >>>>> readAgilent() function. >>>>> >>>>> What's the correct way to normalize the data? I would like to >>>>> normalize >>>>> background information first maNorm function manual isn't very >>>>> clarifying for me. >>>>> >>>>> Thanks ! >>>>> >>>>> Best regards, >>>>> Guillermo. >>>> >>>> ______________________________________________________________________ >>>> The information in this email is confidential and intended solely for >>>> the addressee. >>>> You must not disclose, forward, print or use it without the >>>> permission of the sender. >>>> ______________________________________________________________________ >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor@r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor [[alternative HTML version deleted]]
Normalization limma PROcess marray Normalization limma PROcess marray • 996 views
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@gordon-smyth
Last seen 37 minutes ago
WEHI, Melbourne, Australia
Dear Guillermo, I already gave you all the code you need to use. The code already parses the header for you. Could you not posssibly try it before asking more questions? Thanks Gordon > Date: Wed, 03 Jul 2013 09:59:42 +0200 > From: Guillermo Marco Puche <guillermo.marco at="" sistemasgenomicos.com=""> > To: bioconductor at r-project.org > Cc: "James W. MacDonald" <jmacdon at="" uw.edu=""> > Subject: Re: [BioC] Normalize background on marray Agilent object > > Hello, > > To read.maimages with Limma do you need to parse Agilent headers from > txt files ? I had some troubles with marray pacakge using read.Agilent > function. > > Best, > > Guillermo. > > On 06/21/2013 04:18 PM, James W. MacDonald wrote: >> Hi Guillermo, >> >> On 6/21/2013 3:06 AM, Guillermo Marco Puche wrote: >>> Dear Gordon, >>> >>> Thank you for your answer. I'll look further into Agilent array image >>> files with limma. >>> >>> As I said the problem is that i'm not currently reading image from >>> Agilent array, but the text data file with marray library and loading >>> it into a maData object like this: >> >> Please note that the read.maimages function doesn't read image files - >> it reads in the same text files you are reading with read.Agilent. >> >> Your original question had to do with the 'correct' background >> correction to use for your Agilent array data. Gordon has therefore >> suggested that you use the 'normexp' method in limma. This does of >> course require you to switch to a different package, but limma tends to >> get better support than marray, so you might be wise to make the >> switch. >> >> But to your original point, you are asking a question that might not >> have a definitive answer. There is no 'best' way to do a background >> correction. There are methods that seem to do a reasonable job over a >> range of experiments, and if I understand correctly, this is why Gordon >> is suggesting you use normexp. But which method might be best for your >> particular situation will be difficult for anybody to predict. >> >> Best, >> >> Jim >> >> >>> >>> maData = read.Agilent(fnames=input , path=NULL, name.Gf = >>> "gMedianSignal", name.Gb = "gBGMedianSignal", name.Rf = >>> "rMedianSignal", name.Rb = "rBGMedianSignal", name.W= NULL, layout = >>> NULL, gnames = NULL, targets = NULL, notes=NULL, skip=NULL, sep="\t", >>> quote="\"", DEBUG=FALSE, info.id=NULL) >>> >>> >>> >>> >>>> On 06/20/2013 01:11 PM, Gordon K Smyth wrote: >>>>> Dera Guillermo, >>>>> >>>>> The usual process is to (1) background correct the foreground >>>>> intensities with respect to the background, then (2) normalize the >>>>> M-values (log-ratios). >>>>> >>>>> For an Agilent two colour array, I do this by: >>>>> >>>>> library(limma) >>>>> RG<- read.maimages(files, source="agilent") >>>>> RGb<- backgroundCorrect(RG, method="normexp") >>>>> MA<- normalizeWithinArrays(RGb, method="loess") >>>>> >>>>> although it is sometimes a good idea to remove positive control >>>>> probes before the normalization step. >>>>> >>>>> A recent example using this pipeline is: >>>>> >>>>> http://www.biomedcentral.com/1471-2105/14/165 >>>>> >>>>> Best wishes >>>>> Gordon >>>>> >>>>>> Date: Wed, 19 Jun 2013 22:38:34 +0200 >>>>>> From: Guillermo Marco Puche<guillermo.marco at="" sistemasgenomicos.com=""> >>>>>> To: "bioconductor at r-project.org"<bioconductor at="" r-project.org=""> >>>>>> Subject: [BioC] Normalize background on marray Agilent object >>>>>> >>>>>> Hello, >>>>>> >>>>>> I'm currently trying to normalize rBG values for a marray object. >>>>>> Data origin is Agilent dual channel array. I've loaded information >>>>>> with readAgilent() function. >>>>>> >>>>>> What's the correct way to normalize the data? I would like to >>>>>> normalize background information first maNorm function manual isn't >>>>>> very clarifying for me. >>>>>> >>>>>> Thanks ! >>>>>> >>>>>> Best regards, >>>>>> Guillermo. ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
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Dear Gordon, That's the error message I'm getting while using your code: Error in 1:n : NA/NaN argument I detail all the commands I'm previously using to try to find the problem. library(marray) input <- c("Arrays/UR0267/FE File/252206034056_SLOT01_S01_CytoCGH_0105_May11_1_1.txt") Sys.setlocale('LC_ALL','C') maData = read.Agilent(fnames=input , path=NULL, name.Gf ="gMedianSignal", name.Gb = "gBGMedianSignal", name.Rf ="rMedianSignal", name.Rb = "rBGMedianSignal", name.W= NULL, layout =NULL, gnames = NULL, targets = NULL, notes=NULL, skip=NULL, sep="\t", quote="\"", DEBUG=FALSE, info.id=NULL) Best regards, Guillermo. On 07/04/2013 01:39 AM, Gordon K Smyth wrote: > Dear Guillermo, > > I already gave you all the code you need to use. The code already > parses the header for you. Could you not posssibly try it before > asking more questions? > > Thanks > Gordon > >> Date: Wed, 03 Jul 2013 09:59:42 +0200 >> From: Guillermo Marco Puche <guillermo.marco@sistemasgenomicos.com> >> To: bioconductor@r-project.org >> Cc: "James W. MacDonald" <jmacdon@uw.edu> >> Subject: Re: [BioC] Normalize background on marray Agilent object >> >> Hello, >> >> To read.maimages with Limma do you need to parse Agilent headers from >> txt files ? I had some troubles with marray pacakge using >> read.Agilent function. >> >> Best, >> >> Guillermo. >> >> On 06/21/2013 04:18 PM, James W. MacDonald wrote: >>> Hi Guillermo, >>> >>> On 6/21/2013 3:06 AM, Guillermo Marco Puche wrote: >>>> Dear Gordon, >>>> >>>> Thank you for your answer. I'll look further into Agilent array >>>> image files with limma. >>>> >>>> As I said the problem is that i'm not currently reading image from >>>> Agilent array, but the text data file with marray library and >>>> loading it into a maData object like this: >>> >>> Please note that the read.maimages function doesn't read image files >>> - it reads in the same text files you are reading with read.Agilent. >>> >>> Your original question had to do with the 'correct' background >>> correction to use for your Agilent array data. Gordon has therefore >>> suggested that you use the 'normexp' method in limma. This does of >>> course require you to switch to a different package, but limma tends >>> to get better support than marray, so you might be wise to make the >>> switch. >>> >>> But to your original point, you are asking a question that might not >>> have a definitive answer. There is no 'best' way to do a background >>> correction. There are methods that seem to do a reasonable job over >>> a range of experiments, and if I understand correctly, this is why >>> Gordon is suggesting you use normexp. But which method might be best >>> for your particular situation will be difficult for anybody to predict. >>> >>> Best, >>> >>> Jim >>> >>> >>>> >>>> maData = read.Agilent(fnames=input , path=NULL, name.Gf = >>>> "gMedianSignal", name.Gb = "gBGMedianSignal", name.Rf = >>>> "rMedianSignal", name.Rb = "rBGMedianSignal", name.W= NULL, layout = >>>> NULL, gnames = NULL, targets = NULL, notes=NULL, skip=NULL, sep="\t", >>>> quote="\"", DEBUG=FALSE, info.id=NULL) >>>> >>>> >>>> >>>> >>>>> On 06/20/2013 01:11 PM, Gordon K Smyth wrote: >>>>>> Dera Guillermo, >>>>>> >>>>>> The usual process is to (1) background correct the foreground >>>>>> intensities with respect to the background, then (2) normalize the >>>>>> M-values (log-ratios). >>>>>> >>>>>> For an Agilent two colour array, I do this by: >>>>>> >>>>>> library(limma) >>>>>> RG<- read.maimages(files, source="agilent") >>>>>> RGb<- backgroundCorrect(RG, method="normexp") >>>>>> MA<- normalizeWithinArrays(RGb, method="loess") >>>>>> >>>>>> although it is sometimes a good idea to remove positive control >>>>>> probes before the normalization step. >>>>>> >>>>>> A recent example using this pipeline is: >>>>>> >>>>>> http://www.biomedcentral.com/1471-2105/14/165 >>>>>> >>>>>> Best wishes >>>>>> Gordon >>>>>> >>>>>>> Date: Wed, 19 Jun 2013 22:38:34 +0200 >>>>>>> From: Guillermo Marco Puche<guillermo.marco@sistemasgenomicos.com> >>>>>>> To: "bioconductor@r-project.org"<bioconductor@r-project.org> >>>>>>> Subject: [BioC] Normalize background on marray Agilent object >>>>>>> >>>>>>> Hello, >>>>>>> >>>>>>> I'm currently trying to normalize rBG values for a marray >>>>>>> object. Data origin is Agilent dual channel array. I've loaded >>>>>>> information with readAgilent() function. >>>>>>> >>>>>>> What's the correct way to normalize the data? I would like to >>>>>>> normalize background information first maNorm function manual >>>>>>> isn't very clarifying for me. >>>>>>> >>>>>>> Thanks ! >>>>>>> >>>>>>> Best regards, >>>>>>> Guillermo. > > ______________________________________________________________________ > The information in this email is confidential and inte...{{dropped:16}}
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@gordon-smyth
Last seen 37 minutes ago
WEHI, Melbourne, Australia
> Date: Mon, 15 Jul 2013 11:43:55 +0200 > From: Guillermo Marco Puche <guillermo.marco at="" sistemasgenomicos.com=""> > To: bioconductor at r-project.org > Subject: Re: [BioC] Normalize background on marray Agilent object > > Dear Gordon, > > That's the error message I'm getting while using your code: You still don't seem to have tried the code I suggested. I suggested read.maimages(), not read.Agilent(). Gordon > Error in 1:n : NA/NaN argument > > I detail all the commands I'm previously using to try to find the problem. > > library(marray) > > input <- c("Arrays/UR0267/FE File/252206034056_SLOT01_S01_CytoCGH_0105_May11_1_1.txt") > > Sys.setlocale('LC_ALL','C') > > maData = read.Agilent(fnames=input , path=NULL, name.Gf > ="gMedianSignal", name.Gb = "gBGMedianSignal", name.Rf ="rMedianSignal", > name.Rb = "rBGMedianSignal", name.W= NULL, layout =NULL, gnames = NULL, > targets = NULL, notes=NULL, skip=NULL, sep="\t", quote="\"", > DEBUG=FALSE, info.id=NULL) > > > Best regards, > Guillermo. > > On 07/04/2013 01:39 AM, Gordon K Smyth wrote: >> Dear Guillermo, >> >> I already gave you all the code you need to use. The code already >> parses the header for you. Could you not posssibly try it before >> asking more questions? >> >> Thanks >> Gordon >> >>> Date: Wed, 03 Jul 2013 09:59:42 +0200 >>> From: Guillermo Marco Puche <guillermo.marco at="" sistemasgenomicos.com=""> >>> To: bioconductor at r-project.org >>> Cc: "James W. MacDonald" <jmacdon at="" uw.edu=""> >>> Subject: Re: [BioC] Normalize background on marray Agilent object >>> >>> Hello, >>> >>> To read.maimages with Limma do you need to parse Agilent headers from >>> txt files ? I had some troubles with marray pacakge using >>> read.Agilent function. >>> >>> Best, >>> >>> Guillermo. >>> >>> On 06/21/2013 04:18 PM, James W. MacDonald wrote: >>>> Hi Guillermo, >>>> >>>> On 6/21/2013 3:06 AM, Guillermo Marco Puche wrote: >>>>> Dear Gordon, >>>>> >>>>> Thank you for your answer. I'll look further into Agilent array >>>>> image files with limma. >>>>> >>>>> As I said the problem is that i'm not currently reading image from >>>>> Agilent array, but the text data file with marray library and >>>>> loading it into a maData object like this: >>>> >>>> Please note that the read.maimages function doesn't read image files >>>> - it reads in the same text files you are reading with read.Agilent. >>>> >>>> Your original question had to do with the 'correct' background >>>> correction to use for your Agilent array data. Gordon has therefore >>>> suggested that you use the 'normexp' method in limma. This does of >>>> course require you to switch to a different package, but limma tends >>>> to get better support than marray, so you might be wise to make the >>>> switch. >>>> >>>> But to your original point, you are asking a question that might not >>>> have a definitive answer. There is no 'best' way to do a background >>>> correction. There are methods that seem to do a reasonable job over >>>> a range of experiments, and if I understand correctly, this is why >>>> Gordon is suggesting you use normexp. But which method might be best >>>> for your particular situation will be difficult for anybody to predict. >>>> >>>> Best, >>>> >>>> Jim >>>> >>>> >>>>> >>>>> maData = read.Agilent(fnames=input , path=NULL, name.Gf = >>>>> "gMedianSignal", name.Gb = "gBGMedianSignal", name.Rf = >>>>> "rMedianSignal", name.Rb = "rBGMedianSignal", name.W= NULL, layout = >>>>> NULL, gnames = NULL, targets = NULL, notes=NULL, skip=NULL, sep="\t", >>>>> quote="\"", DEBUG=FALSE, info.id=NULL) >>>>> >>>>> >>>>> >>>>> >>>>>> On 06/20/2013 01:11 PM, Gordon K Smyth wrote: >>>>>>> Dera Guillermo, >>>>>>> >>>>>>> The usual process is to (1) background correct the foreground >>>>>>> intensities with respect to the background, then (2) normalize the >>>>>>> M-values (log-ratios). >>>>>>> >>>>>>> For an Agilent two colour array, I do this by: >>>>>>> >>>>>>> library(limma) >>>>>>> RG<- read.maimages(files, source="agilent") >>>>>>> RGb<- backgroundCorrect(RG, method="normexp") >>>>>>> MA<- normalizeWithinArrays(RGb, method="loess") >>>>>>> >>>>>>> although it is sometimes a good idea to remove positive control >>>>>>> probes before the normalization step. >>>>>>> >>>>>>> A recent example using this pipeline is: >>>>>>> >>>>>>> http://www.biomedcentral.com/1471-2105/14/165 >>>>>>> >>>>>>> Best wishes >>>>>>> Gordon >>>>>>> >>>>>>>> Date: Wed, 19 Jun 2013 22:38:34 +0200 >>>>>>>> From: Guillermo Marco Puche<guillermo.marco at="" sistemasgenomicos.com=""> >>>>>>>> To: "bioconductor at r-project.org"<bioconductor at="" r-project.org=""> >>>>>>>> Subject: [BioC] Normalize background on marray Agilent object >>>>>>>> >>>>>>>> Hello, >>>>>>>> >>>>>>>> I'm currently trying to normalize rBG values for a marray >>>>>>>> object. Data origin is Agilent dual channel array. I've loaded >>>>>>>> information with readAgilent() function. >>>>>>>> >>>>>>>> What's the correct way to normalize the data? I would like to >>>>>>>> normalize background information first maNorm function manual >>>>>>>> isn't very clarifying for me. >>>>>>>> >>>>>>>> Thanks ! >>>>>>>> >>>>>>>> Best regards, >>>>>>>> Guillermo. ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
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