[BioC] AgiMicroRna for new Agilent Chip format

Gordon K Smyth smyth at wehi.EDU.AU
Mon Feb 25 02:31:38 CET 2013


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/doc/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
>

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