Help on Loading AgilentData into LIMMA
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Wendy Chen ▴ 40
@wendy-chen-2768
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Jarno Tuimala ▴ 140
@jarno-tuimala-1650
Last seen 9.6 years ago
Hello! > RG<-read.maimages("targets.txt", source="agilent", > columns=list(gBGMeanSignal="F635", gBGMeanSignal="F532", > bBGMedianSignal="B635 Median", bBGMedianSignal="B532 Median"), > annotation=c("Block", "Column", "Row", "Name", "ID")) You seem to have a datafile that has been created with GenePix program, so maybe setting source="genepix" in read.maimages() would help? In limma the source does not refer to the manufacturer of the chip, but to the program that was used to scan the image and produce the data file. > My data is read as an agilent single colour and therefore I've only a Cy3 > output. How then do I define the foreground for R? If you have a single color slide, then you probably need to change the default columns that read.maimages() uses: columns=list(R = "F635 Median", G = "F532 Median", Rb = "B635 Median", Gb = "B532 Median") into columns=list(R = "F635 Median", G = "F635 Median", Rb = "B635 Median", Gb = "B632 Median") So you put the only channel you have in as both red and green channels. > also what does F635 and B532 means? Chips are scanned using two wavelenghts, 635 and 532. These are the green and red colors/channels. Labels F and B in front of the wavelenghts refer to the Foreground and Background for that particular wavelenght. So, F635 is the foreground (spot) intensity for the green color, and B532 is the background for the red color. Best Regards, Jarno Tuimala Finland
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Hi Jarno, No my files were not created with a genePix program. My raw data were obtained with agilent's Feature extraction. That was why I was using source="agilent" I thought F635 and F532 were codes to imply foreground and background but I guess I was wrong. If my datafiles were not created with a GenePix program does that mean F635 and F532 does not apply? What should I use then? With RG<-read.maimages("targets.txt", columns=list(gBGMeanSignal="xxxxx", gBGMedianSignal="yyyyy"), annotation=c("Block", "Column", "Row", "Name", "ID")) I'll still get the error: columns must specify foreground G and R but I cannot put the only channel I have as both red and green channels as I only columns in my data for the green channel. i.e. I do not have a rBGMeanSignal or rBGMedianSignal. -----Original Message----- From: Jarno Tuimala [mailto:jtuimala@csc.fi] Sent: Tuesday, 22 April 2008 4:51 PM To: Wendy Chen Cc: bioconductor at stat.math.ethz.ch Subject: Re: [BioC] Help on Loading AgilentData into LIMMA Hello! > RG<-read.maimages("targets.txt", source="agilent", > columns=list(gBGMeanSignal="F635", gBGMeanSignal="F532", > bBGMedianSignal="B635 Median", bBGMedianSignal="B532 Median"), > annotation=c("Block", "Column", "Row", "Name", "ID")) You seem to have a datafile that has been created with GenePix program, so maybe setting source="genepix" in read.maimages() would help? In limma the source does not refer to the manufacturer of the chip, but to the program that was used to scan the image and produce the data file. > My data is read as an agilent single colour and therefore I've only a Cy3 > output. How then do I define the foreground for R? If you have a single color slide, then you probably need to change the default columns that read.maimages() uses: columns=list(R = "F635 Median", G = "F532 Median", Rb = "B635 Median", Gb = "B532 Median") into columns=list(R = "F635 Median", G = "F635 Median", Rb = "B635 Median", Gb = "B632 Median") So you put the only channel you have in as both red and green channels. > also what does F635 and B532 means? Chips are scanned using two wavelenghts, 635 and 532. These are the green and red colors/channels. Labels F and B in front of the wavelenghts refer to the Foreground and Background for that particular wavelenght. So, F635 is the foreground (spot) intensity for the green color, and B532 is the background for the red color. Best Regards, Jarno Tuimala Finland
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Hi Wendy! > No my files were not created with a genePix program. My raw data were > obtained with agilent's Feature extraction. That was why I was using > source="agilent" Sorry, my mistake! > I thought F635 and F532 were codes to imply foreground and background but I > guess I was wrong. If my datafiles were not created with a GenePix program > does that mean F635 and F532 does not apply? What should I use then? Yes, F still stands for foreground, and B for background. It seems that you have tried to read in your data with the following command: > RG<-read.maimages("targets.txt", source="agilent", columns=list(gBGMeanSignal="F635", gBGMeanSignal="F532", bBGMedianSignal="B635 Median", bBGMedianSignal="B532 Median"), annotation=c("Block", "Column", "Row", "Name", "ID")) For limma, you need the specify the columns argument as: columns=list(R="", G="", Rb"", Gb="") There have to be an entry for each of R, G, Rb and Gb. Maybe this is the reason for the error message. > but I cannot put the only channel I have as both red and green channels as I > only columns in my data for the green channel. i.e. I do not have a > rBGMeanSignal or rBGMedianSignal. And I meant is that you have to specify the same columns for both R and G and Rb and Gb in the columns argument. So, if your datafile is Agilent, something like this should work (you should have columns gMeanSignal, gBGMedianSignal and ProbeName in your datafile): RG<-read.maimages(files="targets.txt", columns=list(R="gMeanSignal", G="gMeanSignal", Rb="gBGMedianSignal", Gb="gBGMedianSignal"), annotation=c("ProbeName")) This reads the green channel intensities from the file to an limma object, where both red and green channels have exactly the same values. This is the way to read in one-color Agilent data using read.maimages(), since limma expects that there are two channels, and both have to be filled in. Best Regards, Jarno ---------------------------------------------------------------------- ------- Jarno Tuimala, PhD, bioinformatics, CSC, P.O.Box 405, FI-02101 Espoo, Finland tel.: +358 9 457 2226, fax: +358 9 457 2302, e-mail: jarno.tuimala at csc.fi CSC is the Finnish IT Center for Science, http://www.csc.fi/molbio
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