Question: AgiMicroRna for new Agilent Chip format
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gravatar for Gordon Smyth
6.5 years ago by
Gordon Smyth38k
Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia
Gordon Smyth38k wrote:
Dear Constanze, You can't RMA normalize an Agilent microarray, because the RMA algorithm is only defined for Affymetrix chips. Nor would I guess that you can use the AgiMicroRna package, because it is specifically for microRNA arrays, which your array is not. But the limma package will read and process any version of Agilent array that I know of. See Sections 4.5 and 15.4 of the limma User's Guide: http://www.bioconductor.org/packages/2.11/bioc/vignettes/limma/inst/do c/usersguide.pdf It will work fine with the features that you have extracted. Best wishes Gordon > Date: Sat, 23 Feb 2013 13:10:01 -0800 (PST) > From: "Constanze [guest]" <guest at="" bioconductor.org=""> > To: bioconductor at r-project.org, constanze.schmitt at in.tum.de > Subject: [BioC] AgiMicroRna for new Agilent Chip format - columns > gTotalGeneSignal and gTotalProbeSignal missing > > > Dear All, > > i have Agilent gene expression data (SurePrint G3 Human Gene Expression > 8x60K v2 Microarray; chip type G4858A-039494) data. Feature extraction > was done setting TextOutPkgType="Full". I want to rma-normalize this > data but realize i'm missing two of the columns required by > readMicroRnaAFE in AgiMicroRna : gTotalGeneSignal and gTotalProbeSignal. > > Here is the list of features i have on the chip: > FEATURES FeatureNum Row Col accessions chr_coord > SubTypeMask SubTypeName Start Sequence ProbeUID ControlType ProbeName > GeneName SystematicName Description PositionX PositionY gSurrogateUsed > gIsFound gProcessedSignal gProcessedSigError gNumPixOLHi gNumPixOLLo > gNumPix gMeanSignal gMedianSignal gPixSDev gPixNormIQR gBGNumPix > gBGMeanSignal gBGMedianSignal gBGPixSDev gBGPixNormIQR gNumSatPix > gIsSaturated gIsFeatNonUnifOL gIsBGNonUnifOL gIsFeatPopnOL gIsBGPopnOL > IsManualFlag gBGSubSignal gBGSubSigError gIsPosAndSignif gPValFeatEqBG > gNumBGUsed gIsWellAboveBG gBGUsed gBGSDUsed ErrorModel > gSpatialDetrendIsInFilteredSet gSpatialDetrendSurfaceValue SpotExtentX > SpotExtentY gNetSignal gMultDetrendSignal gProcessedBackground > gProcessedBkngError IsUsedBGAdjust gInterpolatedNegCtrlSub > gIsInNegCtrlRange gIsUsedInMD > > > If AgiMicroRna is not adapted for this type of data, are there any good > alternatives? > > > Thanks very much, > > Constanze > > > > -- output of sessionInfo(): > > R version 2.15.1 (2012-06-22) > Platform: i686-pc-linux-gnu (32-bit) > > locale: > [1] LC_CTYPE=de_CH.UTF-8 LC_NUMERIC=C > [3] LC_TIME=de_CH.UTF-8 LC_COLLATE=de_CH.UTF-8 > [5] LC_MONETARY=de_CH.UTF-8 LC_MESSAGES=de_DE.UTF-8 > [7] LC_PAPER=C LC_NAME=C > [9] LC_ADDRESS=C LC_TELEPHONE=C > [11] LC_MEASUREMENT=de_CH.UTF-8 LC_IDENTIFICATION=C > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] AgiMicroRna_2.6.0 affycoretools_1.28.0 KEGG.db_2.7.1 > [4] GO.db_2.7.1 RSQLite_0.11.2 DBI_0.2-5 > [7] AnnotationDbi_1.18.4 preprocessCore_1.18.0 affy_1.34.0 > [10] limma_3.12.3 Biobase_2.16.0 BiocGenerics_0.2.0 > > loaded via a namespace (and not attached): > [1] affyio_1.24.0 annaffy_1.28.0 annotate_1.34.1 > [4] BiocInstaller_1.4.9 biomaRt_2.12.0 Biostrings_2.24.1 > [7] Category_2.22.0 gcrma_2.28.0 genefilter_1.38.0 > [10] GOstats_2.22.0 graph_1.34.0 grid_2.15.1 > [13] GSEABase_1.18.0 IRanges_1.14.4 lattice_0.20-10 > [16] RBGL_1.32.1 RCurl_1.95-3 splines_2.15.1 > [19] stats4_2.15.1 survival_2.36-14 tools_2.15.1 > [22] XML_3.95-0.1 xtable_1.7-0 zlibbioc_1.2.0 > ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}
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