Question: Reading Agilent files using read.maimages
0
gravatar for Steve Taylor
12.3 years ago by
Steve Taylor100
Steve Taylor100 wrote:
Hi, I am trying to read a set of Agilent (Human 1A Microarray(V2)[G4110B] (A-AGIL-9)) files from ArrayExpress, accession E-MEXP-668, using read.maimages. I haven't processed Agilent files before (or used read.maimages for that matter!) so sorry if this a basic question but I am wondering if there is a problem parsing the data or perhaps I am doing something wrong.... I downloaded the raw data from ArrayExpress. I then read in the data like this: > RG<-read.maimages(targets$FileName,path=".",source="agilent"); Read ./E-MEXP-668-raw-data-921408043.txt Read ./E-MEXP-668-raw-data-921408048.txt Read ./E-MEXP-668-raw-data-921408053.txt Read ./E-MEXP-668-raw-data-921408058.txt Read ./E-MEXP-668-raw-data-921408063.txt Read ./E-MEXP-668-raw-data-921408068.txt Read ./E-MEXP-668-raw-data-921408073.txt Read ./E-MEXP-668-raw-data-921408078.txt Read ./E-MEXP-668-raw-data-921408083.txt Read ./E-MEXP-668-raw-data-921408088.txt Read ./E-MEXP-668-raw-data-921408093.txt Read ./E-MEXP-668-raw-data-921408098.txt Read ./E-MEXP-668-raw-data-921408103.txt Read ./E-MEXP-668-raw-data-921408108.txt Read ./E-MEXP-668-raw-data-921408113.txt Read ./E-MEXP-668-raw-data-921408118.txt Read ./E-MEXP-668-raw-data-921408123.txt Read ./E-MEXP-668-raw-data-921408128.txt Read ./E-MEXP-668-raw-data-921408133.txt Read ./E-MEXP-668-raw-data-921408138.txt Read ./E-MEXP-668-raw-data-921408143.txt Querying the object... > names(RG) [1] "G" "Gb" "R" "Rb" "targets" "source" > dim(RG) [1] 0 21 >RG$R E-MEXP-668-raw-data-921408043 E-MEXP-668-raw-data-921408048 E-MEXP-668-raw-data-921408053 E-MEXP-668-raw-data-921408058 E-MEXP-668-raw-data-921408063 E-MEXP-668-raw-data-921408068 E-MEXP-668-raw-data-921408073 E-MEXP-668-raw-data-921408078 E-MEXP-668-raw-data-921408083 E-MEXP-668-raw-data-921408088 E-MEXP-668-raw-data-921408093 E-MEXP-668-raw-data-921408098 E-MEXP-668-raw-data-921408103 E-MEXP-668-raw-data-921408108 E-MEXP-668-raw-data-921408113 E-MEXP-668-raw-data-921408118 E-MEXP-668-raw-data-921408123 E-MEXP-668-raw-data-921408128 E-MEXP-668-raw-data-921408133 E-MEXP-668-raw-data-921408138 E-MEXP-668-raw-data-921408143 > RG$G E-MEXP-668-raw-data-921408043 E-MEXP-668-raw-data-921408048 E-MEXP-668-raw-data-921408053 E-MEXP-668-raw-data-921408058 E-MEXP-668-raw-data-921408063 E-MEXP-668-raw-data-921408068 E-MEXP-668-raw-data-921408073 E-MEXP-668-raw-data-921408078 E-MEXP-668-raw-data-921408083 E-MEXP-668-raw-data-921408088 E-MEXP-668-raw-data-921408093 E-MEXP-668-raw-data-921408098 E-MEXP-668-raw-data-921408103 E-MEXP-668-raw-data-921408108 E-MEXP-668-raw-data-921408113 E-MEXP-668-raw-data-921408118 E-MEXP-668-raw-data-921408123 E-MEXP-668-raw-data-921408128 E-MEXP-668-raw-data-921408133 E-MEXP-668-raw-data-921408138 E-MEXP-668-raw-data-921408143 A typical header for one of these raw files is CompositeSequence Identifier Database ebi.ac.uk:Database:embl Database ebi.ac.uk:Database:ensembl Database ebi.ac.uk:Database:locus Database ebi.ac.uk:Database:refseq Database ebi.ac.uk:Database:tigr_thc Database www.chem.agilent.com:Database:agc Database www.chem.agilent.com:Database:agp Feature coordinates: metaColumn metaRow column row Reporter control type Reporter group Reporter identifier Reporter name Reporter sequence type H_C1 A_mock A and B/FEATURES H_C1 A_mock A and B/FeatureNum H_C1 A_mock A and B/gbpri H_C1 A_mock A and B/gp H_C1 A_mock A and B/sp H_C1 A_mock A and B/ProbeUID H_C1 A_mock A and B/ControlType H_C1 A_mock A and B/ProbeName H_C1 A_mock A and B/GeneName H_C1 A_mock A and B/SystematicName H_C1 A_mock A and B/Description H_C1 A_mock A and B/LogRatio H_C1 A_mock A and B/LogRatioError H_C1 A_mock A and B/PValueLogRatio H_C1 A_mock A and B/gSurrogateUsed H_C1 A_mock A and B/rSurrogateUsed H_C1 A_mock A and B/gIsFound H_C1 A_mock A and B/rIsFound H_C1 A_mock A and B/gProcessedSignal H_C1 A_mock A and B/rProcessedSignal H_C1 A_mock A and B/gProcessedSigError H_C1 A_mock A and B/rProcessedSigError H_C1 A_mock A and B/gNumPixOLHi H_C1 A_mock A and B/rNumPixOLHi H_C1 A_mock A and B/gNumPixOLLo H_C1 A_mock A and B/rNumPixOLLo H_C1 A_mock A and B/gNumPix H_C1 A_mock A and B/rNumPix H_C1 A_mock A and B/gMeanSignal H_C1 A_mock A and B/rMeanSignal H_C1 A_mock A and B/gMedianSignal H_C1 A_mock A and B/rMedianSignal H_C1 A_mock A and B/gPixSDev H_C1 A_mock A and B/rPixSDev H_C1 A_mock A and B/gBGNumPix H_C1 A_mock A and B/rBGNumPix H_C1 A_mock A and B/gBGMeanSignal H_C1 A_mock A and B/rBGMeanSignal H_C1 A_mock A and B/gBGMedianSignal H_C1 A_mock A and B/rBGMedianSignal H_C1 A_mock A and B/gBGPixSDev H_C1 A_mock A and B/rBGPixSDev H_C1 A_mock A and B/gNumSatPix H_C1 A_mock A and B/rNumSatPix H_C1 A_mock A and B/gIsSaturated H_C1 A_mock A and B/rIsSaturated H_C1 A_mock A and B/PixCorrelation H_C1 A_mock A and B/BGPixCorrelation H_C1 A_mock A and B/gIsFeatNonUnifOL H_C1 A_mock A and B/rIsFeatNonUnifOL H_C1 A_mock A and B/gIsBGNonUnifOL H_C1 A_mock A and B/rIsBGNonUnifOL H_C1 A_mock A and B/gIsFeatPopnOL H_C1 A_mock A and B/rIsFeatPopnOL H_C1 A_mock A and B/gIsBGPopnOL H_C1 A_mock A and B/rIsBGPopnOL H_C1 A_mock A and B/IsManualFlag H_C1 A_mock A and B/gBGSubSignal H_C1 A_mock A and B/rBGSubSignal H_C1 A_mock A and B/gBGSubSigError H_C1 A_mock A and B/rBGSubSigError H_C1 A_mock A and B/BGSubSigCorrelation H_C1 A_mock A and B/gIsPosAndSignif H_C1 A_mock A and B/rIsPosAndSignif H_C1 A_mock A and B/gPValFeatEqBG H_C1 A_mock A and B/rPValFeatEqBG H_C1 A_mock A and B/gNumBGUsed H_C1 A_mock A and B/rNumBGUsed H_C1 A_mock A and B/gIsWellAboveBG H_C1 A_mock A and B/rIsWellAboveBG H_C1 A_mock A and B/IsUsedBGAdjust H_C1 A_mock A and B/gBGUsed H_C1 A_mock A and B/rBGUsed H_C1 A_mock A and B/gBGSDUsed H_C1 A_mock A and B/rBGSDUsed H_C1 A_mock A and B/IsNormalization H_C1 A_mock A and B/gDyeNormSignal H_C1 A_mock A and B/rDyeNormSignal H_C1 A_mock A and B/gDyeNormError H_C1 A_mock A and B/rDyeNormError H_C1 A_mock A and B/DyeNormCorrelation H_C1 A_mock A and B/ErrorModel Does this look correct? How do I get access to the intensities, for example to do a boxplot? Thanks in advance for any help, Steve > sessionInfo() R version 2.5.1 (2007-06-27) sparc-sun-solaris2.9 locale: C attached base packages: [1] "tcltk" "splines" "tools" "stats" "graphics" "grDevices" [7] "utils" "datasets" "methods" "base" other attached packages: convert marray tkWidgets DynDoc widgetTools arrayMagic "1.10.0" "1.14.0" "1.14.0" "1.14.0" "1.12.0" "1.14.0" genefilter survival vsn affy affyio limma "1.14.1" "2.32" "2.2.0" "1.14.2" "1.4.1" "2.10.5" Biobase "1.14.1"
ADD COMMENTlink modified 12.3 years ago by Scott Reagan Franklin20 • written 12.3 years ago by Steve Taylor100
Answer: Reading Agilent files using read.maimages
0
gravatar for Sean Davis
12.3 years ago by
Sean Davis21k
United States
Sean Davis21k wrote:
Steve Taylor wrote: > Hi, > > I am trying to read a set of Agilent (Human 1A Microarray(V2)[G4110B] (A-AGIL-9)) files from ArrayExpress, accession E-MEXP-668, using read.maimages. I haven't processed Agilent files before (or used > read.maimages for that matter!) so sorry if this a basic question but I am wondering if there is a problem parsing the data or perhaps I am doing something wrong.... > > I downloaded the raw data from ArrayExpress. I then read in the data like this: > > > RG<-read.maimages(targets$FileName,path=".",source="agilent"); > Read ./E-MEXP-668-raw-data-921408043.txt > Read ./E-MEXP-668-raw-data-921408048.txt > Read ./E-MEXP-668-raw-data-921408053.txt > Read ./E-MEXP-668-raw-data-921408058.txt > Read ./E-MEXP-668-raw-data-921408063.txt > Read ./E-MEXP-668-raw-data-921408068.txt > Read ./E-MEXP-668-raw-data-921408073.txt > Read ./E-MEXP-668-raw-data-921408078.txt > Read ./E-MEXP-668-raw-data-921408083.txt > Read ./E-MEXP-668-raw-data-921408088.txt > Read ./E-MEXP-668-raw-data-921408093.txt > Read ./E-MEXP-668-raw-data-921408098.txt > Read ./E-MEXP-668-raw-data-921408103.txt > Read ./E-MEXP-668-raw-data-921408108.txt > Read ./E-MEXP-668-raw-data-921408113.txt > Read ./E-MEXP-668-raw-data-921408118.txt > Read ./E-MEXP-668-raw-data-921408123.txt > Read ./E-MEXP-668-raw-data-921408128.txt > Read ./E-MEXP-668-raw-data-921408133.txt > Read ./E-MEXP-668-raw-data-921408138.txt > Read ./E-MEXP-668-raw-data-921408143.txt > > Querying the object... > > names(RG) > [1] "G" "Gb" "R" "Rb" "targets" "source" > > > dim(RG) > [1] 0 21 > > > >RG$R > E-MEXP-668-raw-data-921408043 E-MEXP-668-raw-data-921408048 > E-MEXP-668-raw-data-921408053 E-MEXP-668-raw-data-921408058 > E-MEXP-668-raw-data-921408063 E-MEXP-668-raw-data-921408068 > E-MEXP-668-raw-data-921408073 E-MEXP-668-raw-data-921408078 > E-MEXP-668-raw-data-921408083 E-MEXP-668-raw-data-921408088 > E-MEXP-668-raw-data-921408093 E-MEXP-668-raw-data-921408098 > E-MEXP-668-raw-data-921408103 E-MEXP-668-raw-data-921408108 > E-MEXP-668-raw-data-921408113 E-MEXP-668-raw-data-921408118 > E-MEXP-668-raw-data-921408123 E-MEXP-668-raw-data-921408128 > E-MEXP-668-raw-data-921408133 E-MEXP-668-raw-data-921408138 > E-MEXP-668-raw-data-921408143 > > > RG$G > E-MEXP-668-raw-data-921408043 E-MEXP-668-raw-data-921408048 > E-MEXP-668-raw-data-921408053 E-MEXP-668-raw-data-921408058 > E-MEXP-668-raw-data-921408063 E-MEXP-668-raw-data-921408068 > E-MEXP-668-raw-data-921408073 E-MEXP-668-raw-data-921408078 > E-MEXP-668-raw-data-921408083 E-MEXP-668-raw-data-921408088 > E-MEXP-668-raw-data-921408093 E-MEXP-668-raw-data-921408098 > E-MEXP-668-raw-data-921408103 E-MEXP-668-raw-data-921408108 > E-MEXP-668-raw-data-921408113 E-MEXP-668-raw-data-921408118 > E-MEXP-668-raw-data-921408123 E-MEXP-668-raw-data-921408128 > E-MEXP-668-raw-data-921408133 E-MEXP-668-raw-data-921408138 > E-MEXP-668-raw-data-921408143 > > > A typical header for one of these raw files is > > CompositeSequence Identifier Database ebi.ac.uk:Database:embl Database ebi.ac.uk:Database:ensembl Database ebi.ac.uk:Database:locus Database ebi.ac.uk:Database:refseq Database > ebi.ac.uk:Database:tigr_thc Database www.chem.agilent.com:Database:agc Database www.chem.agilent.com:Database:agp Feature coordinates: metaColumn metaRow column row Reporter control > type Reporter group Reporter identifier Reporter name Reporter sequence type H_C1 A_mock A and B/FEATURES H_C1 A_mock A and B/FeatureNum H_C1 A_mock A and B/gbpri H_C1 A_mock A and > B/gp H_C1 A_mock A and B/sp H_C1 A_mock A and B/ProbeUID H_C1 A_mock A and B/ControlType H_C1 A_mock A and B/ProbeName H_C1 A_mock A and B/GeneName H_C1 A_mock A and B/SystematicName > H_C1 A_mock A and B/Description H_C1 A_mock A and B/LogRatio H_C1 A_mock A and B/LogRatioError H_C1 A_mock A and B/PValueLogRatio H_C1 A_mock A and B/gSurrogateUsed H_C1 A_mock A > and B/rSurrogateUsed H_C1 A_mock A and B/gIsFound H_C1 A_mock A and B/rIsFound H_C1 A_mock A and B/gProcessedSignal H_C1 A_mock A and B/rProcessedSignal H_C1 A_mock A and > B/gProcessedSigError H_C1 A_mock A and B/rProcessedSigError H_C1 A_mock A and B/gNumPixOLHi H_C1 A_mock A and B/rNumPixOLHi H_C1 A_mock A and B/gNumPixOLLo H_C1 A_mock A and B/rNumPixOLLo H_C1 > A_mock A and B/gNumPix H_C1 A_mock A and B/rNumPix H_C1 A_mock A and B/gMeanSignal H_C1 A_mock A and B/rMeanSignal H_C1 A_mock A and B/gMedianSignal H_C1 A_mock A and B/rMedianSignal > H_C1 A_mock A and B/gPixSDev H_C1 A_mock A and B/rPixSDev H_C1 A_mock A and B/gBGNumPix H_C1 A_mock A and B/rBGNumPix H_C1 A_mock A and B/gBGMeanSignal H_C1 A_mock A and > B/rBGMeanSignal H_C1 A_mock A and B/gBGMedianSignal H_C1 A_mock A and B/rBGMedianSignal H_C1 A_mock A and B/gBGPixSDev H_C1 A_mock A and B/rBGPixSDev H_C1 A_mock A and B/gNumSatPix > H_C1 A_mock A and B/rNumSatPix H_C1 A_mock A and B/gIsSaturated H_C1 A_mock A and B/rIsSaturated H_C1 A_mock A and B/PixCorrelation H_C1 A_mock A and B/BGPixCorrelation H_C1 > A_mock A and B/gIsFeatNonUnifOL H_C1 A_mock A and B/rIsFeatNonUnifOL H_C1 A_mock A and B/gIsBGNonUnifOL H_C1 A_mock A and B/rIsBGNonUnifOL H_C1 A_mock A and B/gIsFeatPopnOL H_C1 > A_mock A and B/rIsFeatPopnOL H_C1 A_mock A and B/gIsBGPopnOL H_C1 A_mock A and B/rIsBGPopnOL H_C1 A_mock A and B/IsManualFlag H_C1 A_mock A and B/gBGSubSignal H_C1 A_mock A and > B/rBGSubSignal H_C1 A_mock A and B/gBGSubSigError H_C1 A_mock A and B/rBGSubSigError H_C1 A_mock A and B/BGSubSigCorrelation H_C1 A_mock A and B/gIsPosAndSignif H_C1 A_mock A and > B/rIsPosAndSignif H_C1 A_mock A and B/gPValFeatEqBG H_C1 A_mock A and B/rPValFeatEqBG H_C1 A_mock A and B/gNumBGUsed H_C1 A_mock A and B/rNumBGUsed H_C1 A_mock A and B/gIsWellAboveBG > H_C1 A_mock A and B/rIsWellAboveBG H_C1 A_mock A and B/IsUsedBGAdjust H_C1 A_mock A and B/gBGUsed H_C1 A_mock A and B/rBGUsed H_C1 A_mock A and B/gBGSDUsed H_C1 A_mock A and > B/rBGSDUsed H_C1 A_mock A and B/IsNormalization H_C1 A_mock A and B/gDyeNormSignal H_C1 A_mock A and B/rDyeNormSignal H_C1 A_mock A and B/gDyeNormError H_C1 A_mock A and > B/rDyeNormError H_C1 A_mock A and B/DyeNormCorrelation H_C1 A_mock A and B/ErrorModel This is not an Agilent Raw Data file, I do not think. The column names are similar, but ArrayExpress has significantly changed the file from its original format. That said, the columns with "LogRatio", "rProcessedSignal" and "gProcessedSignal" are the columns of interest that have already been background corrected and, typically, a normalization method applied (not sure which one without some more description of the scanner settings). > Does this look correct? How do I get access to the intensities, for example to do a boxplot? I'm not sure if the files loaded correctly, given my comments above. RG$R and RG$G contain the Red and Green intensities, if it loaded correctly. Sean
ADD COMMENTlink written 12.3 years ago by Sean Davis21k
Hi Sean, >>A typical header for one of these raw files is >> >>CompositeSequence Identifier Database ebi.ac.uk:Database:embl Database ebi.ac.uk:Database:ensembl Database ebi.ac.uk:Database:locus Database ebi.ac.uk:Database:refseq Database >>ebi.ac.uk:Database:tigr_thc Database www.chem.agilent.com:Database:agc Database www.chem.agilent.com:Database:agp Feature coordinates: metaColumn metaRow column row Reporter control >>type Reporter group Reporter identifier Reporter name Reporter sequence type H_C1 A_mock A and B/FEATURES H_C1 A_mock A and B/FeatureNum H_C1 A_mock A and B/gbpri H_C1 A_mock A and >>B/gp H_C1 A_mock A and B/sp H_C1 A_mock A and B/ProbeUID H_C1 A_mock A and B/ControlType H_C1 A_mock A and B/ProbeName H_C1 A_mock A and B/GeneName H_C1 A_mock A and B/SystematicName >>H_C1 A_mock A and B/Description H_C1 A_mock A and B/LogRatio H_C1 A_mock A and B/LogRatioError H_C1 A_mock A and B/PValueLogRatio H_C1 A_mock A and B/gSurrogateUsed H_C1 A_mock A >>and B/rSurrogateUsed H_C1 A_mock A and B/gIsFound H_C1 A_mock A and B/rIsFound H_C1 A_mock A and B/gProcessedSignal H_C1 A_mock A and B/rProcessedSignal H_C1 A_mock A and >>B/gProcessedSigError H_C1 A_mock A and B/rProcessedSigError H_C1 A_mock A and B/gNumPixOLHi H_C1 A_mock A and B/rNumPixOLHi H_C1 A_mock A and B/gNumPixOLLo H_C1 A_mock A and B/rNumPixOLLo H_C1 >>A_mock A and B/gNumPix H_C1 A_mock A and B/rNumPix H_C1 A_mock A and B/gMeanSignal H_C1 A_mock A and B/rMeanSignal H_C1 A_mock A and B/gMedianSignal H_C1 A_mock A and B/rMedianSignal >> H_C1 A_mock A and B/gPixSDev H_C1 A_mock A and B/rPixSDev H_C1 A_mock A and B/gBGNumPix H_C1 A_mock A and B/rBGNumPix H_C1 A_mock A and B/gBGMeanSignal H_C1 A_mock A and >>B/rBGMeanSignal H_C1 A_mock A and B/gBGMedianSignal H_C1 A_mock A and B/rBGMedianSignal H_C1 A_mock A and B/gBGPixSDev H_C1 A_mock A and B/rBGPixSDev H_C1 A_mock A and B/gNumSatPix >>H_C1 A_mock A and B/rNumSatPix H_C1 A_mock A and B/gIsSaturated H_C1 A_mock A and B/rIsSaturated H_C1 A_mock A and B/PixCorrelation H_C1 A_mock A and B/BGPixCorrelation H_C1 >>A_mock A and B/gIsFeatNonUnifOL H_C1 A_mock A and B/rIsFeatNonUnifOL H_C1 A_mock A and B/gIsBGNonUnifOL H_C1 A_mock A and B/rIsBGNonUnifOL H_C1 A_mock A and B/gIsFeatPopnOL H_C1 >>A_mock A and B/rIsFeatPopnOL H_C1 A_mock A and B/gIsBGPopnOL H_C1 A_mock A and B/rIsBGPopnOL H_C1 A_mock A and B/IsManualFlag H_C1 A_mock A and B/gBGSubSignal H_C1 A_mock A and >>B/rBGSubSignal H_C1 A_mock A and B/gBGSubSigError H_C1 A_mock A and B/rBGSubSigError H_C1 A_mock A and B/BGSubSigCorrelation H_C1 A_mock A and B/gIsPosAndSignif H_C1 A_mock A and >>B/rIsPosAndSignif H_C1 A_mock A and B/gPValFeatEqBG H_C1 A_mock A and B/rPValFeatEqBG H_C1 A_mock A and B/gNumBGUsed H_C1 A_mock A and B/rNumBGUsed H_C1 A_mock A and B/gIsWellAboveBG >> H_C1 A_mock A and B/rIsWellAboveBG H_C1 A_mock A and B/IsUsedBGAdjust H_C1 A_mock A and B/gBGUsed H_C1 A_mock A and B/rBGUsed H_C1 A_mock A and B/gBGSDUsed H_C1 A_mock A and >>B/rBGSDUsed H_C1 A_mock A and B/IsNormalization H_C1 A_mock A and B/gDyeNormSignal H_C1 A_mock A and B/rDyeNormSignal H_C1 A_mock A and B/gDyeNormError H_C1 A_mock A and >>B/rDyeNormError H_C1 A_mock A and B/DyeNormCorrelation H_C1 A_mock A and B/ErrorModel > > > This is not an Agilent Raw Data file, I do not think. The column names > are similar, but ArrayExpress has significantly changed the file from > its original format. That said, the columns with "LogRatio", > "rProcessedSignal" and "gProcessedSignal" are the columns of interest > that have already been background corrected and, typically, a > normalization method applied (not sure which one without some more > description of the scanner settings). > Ok. Thanks. That's useful information. In the protocols section of AE it says 'Default settings' (http://www.ebi.ac.uk/aerep/details?class=MAGE.Experiment_protocols&cr iteria=Experiment%3D921408317&contextClass=MAGE.Protocol&templateName= Protocol.vm). If that means it has been normalised I will have a look at LogRatio, rProcessedSignal and gProcessedSignal, though it would be nice to know how it had been processed... > >>Does this look correct? How do I get access to the intensities, for example to do a boxplot? > > > I'm not sure if the files loaded correctly, given my comments above. > RG$R and RG$G contain the Red and Green intensities, if it loaded correctly. > That's what I thought. Thanks for the advice, Steve
ADD REPLYlink written 12.3 years ago by Steve Taylor100
Hi Steve, It would seem that most of the columns that you have are also present in an Agilent output file (Except for the "H_C1 A_mock A and B/"-part). You apparently have all the columns necessary to do the analysis: (I'll remove the extra header part to keep a more clear overview, perhaps it's a good idea to remove these parts from your files as well) - r/gMeanSignal (Mean Signal intensity for red/green channel) - r/gBGMeanSignal (Mean Background Signal Intensity for red/green channel) - r/gMedianSignal (Median Signal r/g) - r/gBGMedianSignal (Median Background Signal r/g) - r/gBGUsed (Estimated background using a specific algorithm called spatial detrending. This value is usually lower compared to r/gBGMe(di)an signal, and should be used during the background subtraction (if you intend to use that), in my humble opinion. So what I usually do then is the following: # Read the Target file (experimental description) - See Limma user guide for more information on this targets <- readTargets("description.txt", sep="\t", quote="\"") # Reading the Images Agilent.RG <- read.maimages(targets$FileName, source="agilent", path=datapath, names=targets$Description, columns= list( R = "rMeanSignal", G = "gMeanSignal", Rb = "rBGUsed", Gb = "gBGUsed", Rb.real = "rBGMeanSignal", Gb.real = "gBGMeanSignal"), annotation = c("FeatureNum","Row","Col","ProbeName","ControlType","GeneName", "Description","SystematicName")) This way you can check both background values (estimated (Agilent.RG$Rb, Agilent.RG$Gb) vs really measured (Agilent.RG$Rb.real, Agilent.RG$Gb.real)) during my quality control checks. As Sean mentioned, the normalization used for the r/gProcessedSignals is dependant on the Scanner type and software used for image conversion, but if the original Feature Annotation Software (and Agilent Scanner) has been used, then I would think in the direction of a LOESS algorithm (for within-array normalisation) followed by scaling to a reference value. If I recall correctly (but I keep forgetting the minor details), then the Processed signal (i.e. for red) is calculated using ( rMeanSignal - rBGUsed ) --> corrected through LOESS Normalization --> Scaling --> Processed Value. I think each Feature Extraction Software comes with a built-in manual where these procedures are more clearly explained. I would suggest reading that. The ratio between rProcessedSignal and gProcessedSignal is then calculated and transformed into a log10-scale! (Note: Bioconductor often uses a log2 scale, so don't compare the Agilent LogRatio directly with the Ratio (LogOdds) you will get while using for instance the limma package in R. I hope that this clarifies a bit. -- Stan -----Original Message----- From: bioconductor-bounces@stat.math.ethz.ch [mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of Steve Taylor Sent: 15 August 2007 10:03 To: Sean Davis Cc: Bioconductor Subject: Re: [BioC] Reading Agilent files using read.maimages Hi Sean, >>A typical header for one of these raw files is >> >>CompositeSequence Identifier Database ebi.ac.uk:Database:embl Database ebi.ac.uk:Database:ensembl Database ebi.ac.uk:Database:locus Database ebi.ac.uk:Database:refseq Database >>ebi.ac.uk:Database:tigr_thc Database www.chem.agilent.com:Database:agc Database www.chem.agilent.com:Database:agp Feature coordinates: metaColumn metaRow column row Reporter control >>type Reporter group Reporter identifier Reporter name Reporter sequence type H_C1 A_mock A and B/FEATURES H_C1 A_mock A and B/FeatureNum H_C1 A_mock A and B/gbpri H_C1 A_mock A and >>B/gp H_C1 A_mock A and B/sp H_C1 A_mock A and B/ProbeUID H_C1 A_mock A and B/ControlType H_C1 A_mock A and B/ProbeName H_C1 A_mock A and B/GeneName H_C1 A_mock A and B/SystematicName >>H_C1 A_mock A and B/Description H_C1 A_mock A and B/LogRatio H_C1 A_mock A and B/LogRatioError H_C1 A_mock A and B/PValueLogRatio H_C1 A_mock A and B/gSurrogateUsed H_C1 A_mock A >>and B/rSurrogateUsed H_C1 A_mock A and B/gIsFound H_C1 A_mock A and B/rIsFound H_C1 A_mock A and B/gProcessedSignal H_C1 A_mock A and B/rProcessedSignal H_C1 A_mock A and >>B/gProcessedSigError H_C1 A_mock A and B/rProcessedSigError H_C1 A_mock A and B/gNumPixOLHi H_C1 A_mock A and B/rNumPixOLHi H_C1 A_mock A and B/gNumPixOLLo H_C1 A_mock A and B/rNumPixOLLo H_C1 >>A_mock A and B/gNumPix H_C1 A_mock A and B/rNumPix H_C1 A_mock A and B/gMeanSignal H_C1 A_mock A and B/rMeanSignal H_C1 A_mock A and B/gMedianSignal H_C1 A_mock A and B/rMedianSignal >> H_C1 A_mock A and B/gPixSDev H_C1 A_mock A and B/rPixSDev H_C1 A_mock A and B/gBGNumPix H_C1 A_mock A and B/rBGNumPix H_C1 A_mock A and B/gBGMeanSignal H_C1 A_mock A and >>B/rBGMeanSignal H_C1 A_mock A and B/gBGMedianSignal H_C1 A_mock A and B/rBGMedianSignal H_C1 A_mock A and B/gBGPixSDev H_C1 A_mock A and B/rBGPixSDev H_C1 A_mock A and B/gNumSatPix >>H_C1 A_mock A and B/rNumSatPix H_C1 A_mock A and B/gIsSaturated H_C1 A_mock A and B/rIsSaturated H_C1 A_mock A and B/PixCorrelation H_C1 A_mock A and B/BGPixCorrelation H_C1 >>A_mock A and B/gIsFeatNonUnifOL H_C1 A_mock A and B/rIsFeatNonUnifOL H_C1 A_mock A and B/gIsBGNonUnifOL H_C1 A_mock A and B/rIsBGNonUnifOL H_C1 A_mock A and B/gIsFeatPopnOL H_C1 >>A_mock A and B/rIsFeatPopnOL H_C1 A_mock A and B/gIsBGPopnOL H_C1 A_mock A and B/rIsBGPopnOL H_C1 A_mock A and B/IsManualFlag H_C1 A_mock A and B/gBGSubSignal H_C1 A_mock A and >>B/rBGSubSignal H_C1 A_mock A and B/gBGSubSigError H_C1 A_mock A and B/rBGSubSigError H_C1 A_mock A and B/BGSubSigCorrelation H_C1 A_mock A and B/gIsPosAndSignif H_C1 A_mock A and >>B/rIsPosAndSignif H_C1 A_mock A and B/gPValFeatEqBG H_C1 A_mock A and B/rPValFeatEqBG H_C1 A_mock A and B/gNumBGUsed H_C1 A_mock A and B/rNumBGUsed H_C1 A_mock A and B/gIsWellAboveBG >> H_C1 A_mock A and B/rIsWellAboveBG H_C1 A_mock A and B/IsUsedBGAdjust H_C1 A_mock A and B/gBGUsed H_C1 A_mock A and B/rBGUsed H_C1 A_mock A and B/gBGSDUsed H_C1 A_mock A and >>B/rBGSDUsed H_C1 A_mock A and B/IsNormalization H_C1 A_mock A and B/gDyeNormSignal H_C1 A_mock A and B/rDyeNormSignal H_C1 A_mock A and B/gDyeNormError H_C1 A_mock A and >>B/rDyeNormError H_C1 A_mock A and B/DyeNormCorrelation H_C1 A_mock A and B/ErrorModel > > > This is not an Agilent Raw Data file, I do not think. The column names > are similar, but ArrayExpress has significantly changed the file from > its original format. That said, the columns with "LogRatio", > "rProcessedSignal" and "gProcessedSignal" are the columns of interest > that have already been background corrected and, typically, a > normalization method applied (not sure which one without some more > description of the scanner settings). > > >Ok. Thanks. That's useful information. In the protocols section of AE it says 'Default settings' >(http://www.ebi.ac.uk/aerep/details?class=MAGE.Experiment_protocols&c ri teria=Experiment%>3D921408317&contextClass=MAGE.Protocol&templateName= Pr otocol.vm). If that means it has been normalised I will >have a look at LogRatio, rProcessedSignal and gProcessedSignal, though it would be nice to know how it had been processed... > > >>Does this look correct? How do I get access to the intensities, for example to do a boxplot? > > > I'm not sure if the files loaded correctly, given my comments above. > RG$R and RG$G contain the Red and Green intensities, if it loaded correctly. > That's what I thought. Thanks for the advice, Steve _______________________________________________ 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
ADD REPLYlink written 12.3 years ago by Gaj Stan BIGCAT100
Answer: Reading Agilent files using read.maimages
0
gravatar for Scott Reagan Franklin
12.3 years ago by
Scott Reagan Franklin20 wrote:
Steve: It should be noted that when you are using read.maimages with source="agilent" and you are using the actual Agilent Raw Data file, you will, by default, have RG$R and RG$G equal to the rMeanSignal and gMeanSignal. In order to specify that they be equal to the rProcessedSignal and gProcessedSignal you need to add an option to read.maimages: RG<-read.maimages(targets$FileName,path=".",columns=list(R="rProcessed Signal",G="gProcessedSignal)); You can also specify which background signal is used as well by including in Rb and Gb in the list above. By default Rb and Gb are chosen as the median background signals. -- Scott Franklin, Ph.D. -------------------------------------------------- Bioinformaticist Post-Doctoral Research Associate Plant and Soil Science Texas Tech University -------------------------------------------------- Adjunct Professor of Mathematics Wayland Baptist University -------------------------------------------------- http://blog.drscottfranklin.net Steve Taylor wrote: > Hi, > > I am trying to read a set of Agilent (Human 1A Microarray(V2)[G4110B] (A-AGIL-9)) files from ArrayExpress, accession E-MEXP-668, using read.maimages. I haven't processed Agilent files before (or used > read.maimages for that matter!) so sorry if this a basic question but I am wondering if there is a problem parsing the data or perhaps I am doing something wrong.... > > I downloaded the raw data from ArrayExpress. I then read in the data like this: > > > RG<-read.maimages(targets$FileName,path=".",source="agilent"); > Read ./E-MEXP-668-raw-data-921408043.txt > Read ./E-MEXP-668-raw-data-921408048.txt > Read ./E-MEXP-668-raw-data-921408053.txt > Read ./E-MEXP-668-raw-data-921408058.txt > Read ./E-MEXP-668-raw-data-921408063.txt > Read ./E-MEXP-668-raw-data-921408068.txt > Read ./E-MEXP-668-raw-data-921408073.txt > Read ./E-MEXP-668-raw-data-921408078.txt > Read ./E-MEXP-668-raw-data-921408083.txt > Read ./E-MEXP-668-raw-data-921408088.txt > Read ./E-MEXP-668-raw-data-921408093.txt > Read ./E-MEXP-668-raw-data-921408098.txt > Read ./E-MEXP-668-raw-data-921408103.txt > Read ./E-MEXP-668-raw-data-921408108.txt > Read ./E-MEXP-668-raw-data-921408113.txt > Read ./E-MEXP-668-raw-data-921408118.txt > Read ./E-MEXP-668-raw-data-921408123.txt > Read ./E-MEXP-668-raw-data-921408128.txt > Read ./E-MEXP-668-raw-data-921408133.txt > Read ./E-MEXP-668-raw-data-921408138.txt > Read ./E-MEXP-668-raw-data-921408143.txt > > Querying the object... > > names(RG) > [1] "G" "Gb" "R" "Rb" "targets" "source" > > > dim(RG) > [1] 0 21 > > > >RG$R > E-MEXP-668-raw-data-921408043 E-MEXP-668-raw-data-921408048 > E-MEXP-668-raw-data-921408053 E-MEXP-668-raw-data-921408058 > E-MEXP-668-raw-data-921408063 E-MEXP-668-raw-data-921408068 > E-MEXP-668-raw-data-921408073 E-MEXP-668-raw-data-921408078 > E-MEXP-668-raw-data-921408083 E-MEXP-668-raw-data-921408088 > E-MEXP-668-raw-data-921408093 E-MEXP-668-raw-data-921408098 > E-MEXP-668-raw-data-921408103 E-MEXP-668-raw-data-921408108 > E-MEXP-668-raw-data-921408113 E-MEXP-668-raw-data-921408118 > E-MEXP-668-raw-data-921408123 E-MEXP-668-raw-data-921408128 > E-MEXP-668-raw-data-921408133 E-MEXP-668-raw-data-921408138 > E-MEXP-668-raw-data-921408143 > > > RG$G > E-MEXP-668-raw-data-921408043 E-MEXP-668-raw-data-921408048 > E-MEXP-668-raw-data-921408053 E-MEXP-668-raw-data-921408058 > E-MEXP-668-raw-data-921408063 E-MEXP-668-raw-data-921408068 > E-MEXP-668-raw-data-921408073 E-MEXP-668-raw-data-921408078 > E-MEXP-668-raw-data-921408083 E-MEXP-668-raw-data-921408088 > E-MEXP-668-raw-data-921408093 E-MEXP-668-raw-data-921408098 > E-MEXP-668-raw-data-921408103 E-MEXP-668-raw-data-921408108 > E-MEXP-668-raw-data-921408113 E-MEXP-668-raw-data-921408118 > E-MEXP-668-raw-data-921408123 E-MEXP-668-raw-data-921408128 > E-MEXP-668-raw-data-921408133 E-MEXP-668-raw-data-921408138 > E-MEXP-668-raw-data-921408143 > > > A typical header for one of these raw files is > > CompositeSequence Identifier Database ebi.ac.uk:Database:embl Database ebi.ac.uk:Database:ensembl Database ebi.ac.uk:Database:locus Database ebi.ac.uk:Database:refseq Database > ebi.ac.uk:Database:tigr_thc Database www.chem.agilent.com:Database:agc Database www.chem.agilent.com:Database:agp Feature coordinates: metaColumn metaRow column row Reporter control > type Reporter group Reporter identifier Reporter name Reporter sequence type H_C1 A_mock A and B/FEATURES H_C1 A_mock A and B/FeatureNum H_C1 A_mock A and B/gbpri H_C1 A_mock A and > B/gp H_C1 A_mock A and B/sp H_C1 A_mock A and B/ProbeUID H_C1 A_mock A and B/ControlType H_C1 A_mock A and B/ProbeName H_C1 A_mock A and B/GeneName H_C1 A_mock A and B/SystematicName > H_C1 A_mock A and B/Description H_C1 A_mock A and B/LogRatio H_C1 A_mock A and B/LogRatioError H_C1 A_mock A and B/PValueLogRatio H_C1 A_mock A and B/gSurrogateUsed H_C1 A_mock A > and B/rSurrogateUsed H_C1 A_mock A and B/gIsFound H_C1 A_mock A and B/rIsFound H_C1 A_mock A and B/gProcessedSignal H_C1 A_mock A and B/rProcessedSignal H_C1 A_mock A and > B/gProcessedSigError H_C1 A_mock A and B/rProcessedSigError H_C1 A_mock A and B/gNumPixOLHi H_C1 A_mock A and B/rNumPixOLHi H_C1 A_mock A and B/gNumPixOLLo H_C1 A_mock A and B/rNumPixOLLo H_C1 > A_mock A and B/gNumPix H_C1 A_mock A and B/rNumPix H_C1 A_mock A and B/gMeanSignal H_C1 A_mock A and B/rMeanSignal H_C1 A_mock A and B/gMedianSignal H_C1 A_mock A and B/rMedianSignal > H_C1 A_mock A and B/gPixSDev H_C1 A_mock A and B/rPixSDev H_C1 A_mock A and B/gBGNumPix H_C1 A_mock A and B/rBGNumPix H_C1 A_mock A and B/gBGMeanSignal H_C1 A_mock A and > B/rBGMeanSignal H_C1 A_mock A and B/gBGMedianSignal H_C1 A_mock A and B/rBGMedianSignal H_C1 A_mock A and B/gBGPixSDev H_C1 A_mock A and B/rBGPixSDev H_C1 A_mock A and B/gNumSatPix > H_C1 A_mock A and B/rNumSatPix H_C1 A_mock A and B/gIsSaturated H_C1 A_mock A and B/rIsSaturated H_C1 A_mock A and B/PixCorrelation H_C1 A_mock A and B/BGPixCorrelation H_C1 > A_mock A and B/gIsFeatNonUnifOL H_C1 A_mock A and B/rIsFeatNonUnifOL H_C1 A_mock A and B/gIsBGNonUnifOL H_C1 A_mock A and B/rIsBGNonUnifOL H_C1 A_mock A and B/gIsFeatPopnOL H_C1 > A_mock A and B/rIsFeatPopnOL H_C1 A_mock A and B/gIsBGPopnOL H_C1 A_mock A and B/rIsBGPopnOL H_C1 A_mock A and B/IsManualFlag H_C1 A_mock A and B/gBGSubSignal H_C1 A_mock A and > B/rBGSubSignal H_C1 A_mock A and B/gBGSubSigError H_C1 A_mock A and B/rBGSubSigError H_C1 A_mock A and B/BGSubSigCorrelation H_C1 A_mock A and B/gIsPosAndSignif H_C1 A_mock A and > B/rIsPosAndSignif H_C1 A_mock A and B/gPValFeatEqBG H_C1 A_mock A and B/rPValFeatEqBG H_C1 A_mock A and B/gNumBGUsed H_C1 A_mock A and B/rNumBGUsed H_C1 A_mock A and B/gIsWellAboveBG > H_C1 A_mock A and B/rIsWellAboveBG H_C1 A_mock A and B/IsUsedBGAdjust H_C1 A_mock A and B/gBGUsed H_C1 A_mock A and B/rBGUsed H_C1 A_mock A and B/gBGSDUsed H_C1 A_mock A and > B/rBGSDUsed H_C1 A_mock A and B/IsNormalization H_C1 A_mock A and B/gDyeNormSignal H_C1 A_mock A and B/rDyeNormSignal H_C1 A_mock A and B/gDyeNormError H_C1 A_mock A and > B/rDyeNormError H_C1 A_mock A and B/DyeNormCorrelation H_C1 A_mock A and B/ErrorModel
ADD COMMENTlink written 12.3 years ago by Scott Reagan Franklin20
Hi Steve, I have download the files and it seems that each file has its own header. By this I mean that a prefix has been add to each standard column. For example, for file "E-MEXP-668-raw-data-921408043.txt" every column start with "H_C1 A_mock A and B/" whereas in file "E-MEXP-668-raw-data-921408128.txt" it is "H_C52 B_mock A and B/". In order to make the read.maimages work you should remove those prefixes. I have changed it for a couple of slides and it worked for me. targets <-read.("AE.csv", path=".",sep=",") RG <- read.maimages(targets$FileName[c(1,16)]),path=".",source="agilent") Read ./E-MEXP-668-raw-data-921408043.txt Read ./E-MEXP-668-raw-data-921408118.txt > str(RG$G) num [1:22153, 1:2] 960.4 73.1 83.3 648.1 132.9 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:2] "E-MEXP-668-raw-data-921408043" "E-MEXP-668-raw-data-921408118" Hope it helps, Nolwenn Scott Reagan Franklin wrote: > Steve: > > It should be noted that when you are using read.maimages with > source="agilent" and you are using the actual Agilent Raw Data file, > you will, by default, have RG$R and RG$G equal to the rMeanSignal and > gMeanSignal. In order to specify that they be equal to the > rProcessedSignal and gProcessedSignal you need to add an option to > read.maimages: > > RG<-read.maimages(targets$FileName,path=".",columns=list(R="rProcess edSignal",G="gProcessedSignal)); > > You can also specify which background signal is used as well by > including in Rb and Gb in the list above. By default Rb and Gb are > chosen as the median background signals. > > > -- -- Nolwenn Le Meur, PhD. Computational Biology, Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N., M2-876 P.O. Box 19024 Seattle, WA 98109-1024 Tel. (206) 667-5434
ADD REPLYlink written 12.3 years ago by Nolwenn LeMeur140
Hi, I removed the prefixes from the file headers and they eventually read in. I did get: Read ./E-MEXP-668-raw-data-921408043.txt Read ./E-MEXP-668-raw-data-921408048.txt Read ./E-MEXP-668-raw-data-921408053.txt Read ./E-MEXP-668-raw-data-921408058.txt Error in RG[[a]][, i] <- obj[, columns[[a]]] : number of items to replace is not a multiple of replacement length which I think is due to inconsistent numbers of columns in some files (and read.maimages doesn't seem to cope with), but I managed to get round this by reording the targets file. I have got the data to normalise now. Thank you all very much for helping me on this problem. Steve > I have download the files and it seems that each file has its own > header. By this I mean that a prefix has been add to each standard column. > For example, for file "E-MEXP-668-raw-data-921408043.txt" every column > start with "H_C1 A_mock A and B/" whereas in file > "E-MEXP-668-raw-data-921408128.txt" it is "H_C52 B_mock A and B/". In > order to make the read.maimages work you should remove those prefixes. I > have changed it for a couple of slides and it worked for me. > > targets <-read.("AE.csv", path=".",sep=",") > RG <- read.maimages(targets$FileName[c(1,16)]),path=".",source="agilent") > Read ./E-MEXP-668-raw-data-921408043.txt > Read ./E-MEXP-668-raw-data-921408118.txt > >>str(RG$G) > > num [1:22153, 1:2] 960.4 73.1 83.3 648.1 132.9 ... > - attr(*, "dimnames")=List of 2 > ..$ : NULL > ..$ : chr [1:2] "E-MEXP-668-raw-data-921408043" > "E-MEXP-668-raw-data-921408118" > > Hope it helps, > Nolwenn > > Scott Reagan Franklin wrote: > >>Steve: >> >>It should be noted that when you are using read.maimages with >>source="agilent" and you are using the actual Agilent Raw Data file, >>you will, by default, have RG$R and RG$G equal to the rMeanSignal and >>gMeanSignal. In order to specify that they be equal to the >>rProcessedSignal and gProcessedSignal you need to add an option to >>read.maimages: >> >>RG<-read.maimages(targets$FileName,path=".",columns=list(R="rProcess edSignal",G="gProcessedSignal)); >> >>You can also specify which background signal is used as well by >>including in Rb and Gb in the list above. By default Rb and Gb are >>chosen as the median background signals. >> >> >> >
ADD REPLYlink written 12.3 years ago by Steve Taylor100
Dear Steve et al, The files you downloaded from ArrayExpress are in fact in its own format. For this experiment, in case you might find it useful, we placed the original Agilent raw data files as given to us by the submitter at ftp://ftp.ebi.ac.uk/pub/databases/microarray/data/ experiment/MEXP/E-MEXP-668/E-MEXP-668.original-raw-data.tar.gz. Hope this helps. --Misha K. Microarray Informatics Team, EBI On 16 Aug 2007, at 14:35, Steve Taylor wrote: > Hi, > > I removed the prefixes from the file headers and they eventually > read in. > > I did get: > > Read ./E-MEXP-668-raw-data-921408043.txt > Read ./E-MEXP-668-raw-data-921408048.txt > Read ./E-MEXP-668-raw-data-921408053.txt > Read ./E-MEXP-668-raw-data-921408058.txt > Error in RG[[a]][, i] <- obj[, columns[[a]]] : > number of items to replace is not a multiple of > replacement length > > which I think is due to inconsistent numbers of columns in some > files (and read.maimages doesn't seem to cope with), but I managed > to get round this by reording the targets file. I have got the data > to normalise now. > > Thank you all very much for helping me on this problem. > > Steve > > >> I have download the files and it seems that each file has its own >> header. By this I mean that a prefix has been add to each standard >> column. >> For example, for file "E-MEXP-668-raw-data-921408043.txt" every >> column >> start with "H_C1 A_mock A and B/" whereas in file >> "E-MEXP-668-raw-data-921408128.txt" it is "H_C52 B_mock A and B/". In >> order to make the read.maimages work you should remove those >> prefixes. I >> have changed it for a couple of slides and it worked for me. >> >> targets <-read.("AE.csv", path=".",sep=",") >> RG <- read.maimages(targets$FileName[c >> (1,16)]),path=".",source="agilent") >> Read ./E-MEXP-668-raw-data-921408043.txt >> Read ./E-MEXP-668-raw-data-921408118.txt >> >>> str(RG$G) >> >> num [1:22153, 1:2] 960.4 73.1 83.3 648.1 132.9 ... >> - attr(*, "dimnames")=List of 2 >> ..$ : NULL >> ..$ : chr [1:2] "E-MEXP-668-raw-data-921408043" >> "E-MEXP-668-raw-data-921408118" >> >> Hope it helps, >> Nolwenn >> >> Scott Reagan Franklin wrote: >> >>> Steve: >>> >>> It should be noted that when you are using read.maimages with >>> source="agilent" and you are using the actual Agilent Raw Data file, >>> you will, by default, have RG$R and RG$G equal to the rMeanSignal >>> and >>> gMeanSignal. In order to specify that they be equal to the >>> rProcessedSignal and gProcessedSignal you need to add an option to >>> read.maimages: >>> >>> RG<-read.maimages(targets$FileName,path=".",columns=list >>> (R="rProcessedSignal",G="gProcessedSignal)); >>> >>> You can also specify which background signal is used as well by >>> including in Rb and Gb in the list above. By default Rb and Gb are >>> chosen as the median background signals. >>> >>> >>> >> > > _______________________________________________ > 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
ADD REPLYlink written 12.3 years ago by Misha Kapushesky130
Hi Misha, > > The files you downloaded from ArrayExpress are in fact in its own > format. For this experiment, in case you might find it useful, we > placed the original Agilent raw data files as given to us by the > submitter at ftp://ftp.ebi.ac.uk/pub/databases/microarray/data/ > experiment/MEXP/E-MEXP-668/E-MEXP-668.original-raw-data.tar.gz. Yes, that would have been useful to know. It would be nice if this was clearer in ArrayExpress, since it is confusing if you don't know the format... Regards, Steve > > Hope this helps. > > --Misha K. > Microarray Informatics Team, EBI > > On 16 Aug 2007, at 14:35, Steve Taylor wrote: > >> Hi, >> >> I removed the prefixes from the file headers and they eventually read >> in. >> >> I did get: >> >> Read ./E-MEXP-668-raw-data-921408043.txt >> Read ./E-MEXP-668-raw-data-921408048.txt >> Read ./E-MEXP-668-raw-data-921408053.txt >> Read ./E-MEXP-668-raw-data-921408058.txt >> Error in RG[[a]][, i] <- obj[, columns[[a]]] : >> number of items to replace is not a multiple of replacement >> length >> >> which I think is due to inconsistent numbers of columns in some files >> (and read.maimages doesn't seem to cope with), but I managed to get >> round this by reording the targets file. I have got the data >> to normalise now. >> >> Thank you all very much for helping me on this problem. >> >> Steve >> >> >>> I have download the files and it seems that each file has its own >>> header. By this I mean that a prefix has been add to each standard >>> column. >>> For example, for file "E-MEXP-668-raw-data-921408043.txt" every column >>> start with "H_C1 A_mock A and B/" whereas in file >>> "E-MEXP-668-raw-data-921408128.txt" it is "H_C52 B_mock A and B/". In >>> order to make the read.maimages work you should remove those >>> prefixes. I >>> have changed it for a couple of slides and it worked for me. >>> >>> targets <-read.("AE.csv", path=".",sep=",") >>> RG <- read.maimages(targets$FileName[c >>> (1,16)]),path=".",source="agilent") >>> Read ./E-MEXP-668-raw-data-921408043.txt >>> Read ./E-MEXP-668-raw-data-921408118.txt >>> >>>> str(RG$G) >>> >>> >>> num [1:22153, 1:2] 960.4 73.1 83.3 648.1 132.9 ... >>> - attr(*, "dimnames")=List of 2 >>> ..$ : NULL >>> ..$ : chr [1:2] "E-MEXP-668-raw-data-921408043" >>> "E-MEXP-668-raw-data-921408118" >>> >>> Hope it helps, >>> Nolwenn >>> >>> Scott Reagan Franklin wrote: >>> >>>> Steve: >>>> >>>> It should be noted that when you are using read.maimages with >>>> source="agilent" and you are using the actual Agilent Raw Data file, >>>> you will, by default, have RG$R and RG$G equal to the rMeanSignal and >>>> gMeanSignal. In order to specify that they be equal to the >>>> rProcessedSignal and gProcessedSignal you need to add an option to >>>> read.maimages: >>>> >>>> RG<-read.maimages(targets$FileName,path=".",columns=list >>>> (R="rProcessedSignal",G="gProcessedSignal)); >>>> >>>> You can also specify which background signal is used as well by >>>> including in Rb and Gb in the list above. By default Rb and Gb are >>>> chosen as the median background signals. >>>> >>>
ADD REPLYlink written 12.3 years ago by Steve Taylor100
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 16.09
Traffic: 174 users visited in the last hour