Dear Pedro, and BioCers
similar to these 2 posts, i'm having problems running AgiMicroRna,  
because my Agilent TXT files are missing these three columns:  
gMeanSignal, gBGUsed, chr_coord.
https://www.stat.math.ethz.ch/pipermail/bioconductor/2010-August/035136.html
http://comments.gmane.org/gmane.science.biology.informatics.conductor/28101

Here was my first attempt
 > library("AgiMicroRna")
 > targets.micro=readTargets(infile="/Volumes/****/projects/****/ 
targets.txt") (sorry - paranoid collaborator)
 > dd.micro=readMicroRnaAFE(targets.micro,verbose=TRUE)
Error in readGenericHeader(fullname, columns = columns, sep = sep) :
   Specified column headings not found in file

I then tried to recreate my own readMicroRnaAFE which constructed  
dummy chr_coord, BGKus objects, but then I wasn't able to run the  
cvArray function:
 > library("AgiMicroRna")
 > targets.micro=readTargets(infile="/Volumes/external/projects/LW/ 
targets.txt")
 > dd.micro=readMicroRnaAFE(targets.micro,verbose=TRUE)
# QC plots ran OK
 > cvArray(dd.micro,"MeanSignal",targets.micro,verbose=TRUE)
Foreground: MeanSignal

	FILTERING BY ControlType FLAG

  RAW DATA: 			 15739
Error in object$other[[k]][i, , drop = FALSE] :
   incorrect number of dimensions
 > cvArray(dd.micro,"ProcessedSignal",targets.micro,verbose=TRUE)
Foreground: ProcessedSignal

	FILTERING BY ControlType FLAG

  RAW DATA: 			 15739
Error in object$other[[k]][i, , drop = FALSE] :
   incorrect number of dimensions

I gave up on this approach, and instead I followed Pedro's advice in  
the first URL that I mentioned, and used gTotalSignal instead of  
gMeanSignal, and removed instances of chr_coord and gBGUsed, but then  
I can't get TGS, or RMA normalization to work

 > library("AgiMicroRna")
 > targets.micro=readTargets(infile="/Volumes/****/projects/****/ 
targets.txt") (sorry - paranoid collaborator)
ddaux=read.maimages(files=targets.micro$FileName,source="agilent",
+                             
other.columns=list(IsGeneDetected="gIsGeneDetected",
+ 
                                                                         IsSaturated 
="gIsSaturated",
+ 
                                                                         IsFeatNonUnifOF 
="gIsFeatNonUnifOL",
+ 
                                                                         IsFeatPopnOL 
="gIsFeatPopnOL",
+ 
                                                                         BGKmd 
="gBGMedianSignal"),
+                          columns=list(Rf="gTotalGeneSignal",
+                                                          
Gf="gTotalProbeSignal",
+                                                          
Rb="gTotalGeneSignal",
+                                                          
Gb="gProcessedSignal"),
+                          verbose=TRUE,sep="\t",quote="")
 > ddNORM = tgsNormalization(ddTGS, "quantile", makePLOTpre = T,  
makePLOTpost = T, targets.micro, verbose = TRUE)
Error in density.default(object[, n], na.rm = TRUE) :
   need at least 2 points to select a bandwidth automatically
 >
 > ddNORM = tgsNormalization(ddTGS, "quantile", makePLOTpre = F,  
makePLOTpost = F, targets.micro, verbose = TRUE)
Error in xy.coords(x, y) : 'x' and 'y' lengths differ
 >
 >
 > ddTGS.rma = rmaMicroRna(ddaux, normalize = TRUE, background = TRUE)
Error in split.default(0:(length(pNList) - 1), pNList) :
   Group length is 0 but data length > 0
# this takes quite a few minutes to process, then gives this error

I've seen quite a bit of Agilent microRNA data through our centre, and  
can't recall ever seeing a chr_coord column, so is this to do with  
different versions of Agilent Feature Extraction, or different  
defaults set by the array facility?

I'd really like to RMA normalize these data, so any help would be  
really appreciated

cheers,
Mark


sessionInfo()
R version 2.11.1 (2010-05-31)
i386-apple-darwin9.8.0

locale:
[1] en_AU.UTF-8/en_AU.UTF-8/C/C/en_AU.UTF-8/en_AU.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] AgiMicroRna_1.2.0     preprocessCore_1.10.0 affy_1.26.1            
limma_3.4.3           Biobase_2.8.0

loaded via a namespace (and not attached):
[1] affyio_1.16.0 tools_2.11.1
 >


-----------------------------------------------------
Mark Cowley, PhD

Peter Wills Bioinformatics Centre
Garvan Institute of Medical Research, Sydney, Australia
-----------------------------------------------------


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