Hi Fraser,
thanks for reporting this issue.
We are aware of this issue. Reason is that since
R versions R-3.x.x AffyBatch does no longer support
particular array types.
We are modifying the FARMS package that array
types that no longer supported by AffyBatch objects
can be used via the oligo package.
Enclosed you will find a workaround to use FARMS for
summarization and also I/NI calls filtering. Please notice,
that the I/NI call filter will not work for probe sets which
contain less than three probes.
Let me know, if you have any problems.
Cheers,
Okko
The code is:
library(oligo)
library(farms)
farms <- function(object, background=FALSE, normalize=TRUE,
subset=NULL, target="core", weight=.5,
mu=0, weighted.mean=FALSE, laplacian=FALSE,
robust=TRUE,
correction=0, centering=c("median","mean"),
spuriousCorrelation=0, verbose=TRUE )
{
target <- match.arg(target, c("core", "probeset"))
featureInfo <- oligo:::stArrayPmInfo(object,
target=target)
theClass <- class(exprs(object))
pmi <- featureInfo[["fid"]]
pnVec <- as.character(featureInfo[["fsetid"]])
if ("matrix" %in% theClass){
pms <- exprs(object)[pmi,, drop=FALSE]
dimnames(pms) <- NULL
colnames(pms) <- sampleNames(object)
theExprs <- basicFARMS(pms, pnVec, normalize,
background, weight=weight, mu=mu, weighted.mean=weighted.mean,
laplacian=laplacian, robust=robust,
correction=correction, centering=centering,
spuriousCorrelation=spuriousCorrelation)
rm(pms)
}
else{
stop("farms is currently not implemented for '",
theClass, "' objects.")
}
colnames(theExprs$exprs) <- colnames(theExprs$se.exprs) <-
sampleNames(object)
rownames(theExprs$exprs) <- rownames(theExprs$se.exprs) <-
unique(pnVec)
out <- new("ExpressionSet",
phenoData=phenoData(object),
experimentData=experimentData(object),
exprs=theExprs$exprs,
se.exprs=theExprs$se.exprs,
annotation=annotation(object),
protocolData=protocolData(object))
if (validObject(out)){
return(out)
}else{
stop("Resulting object is invalid.")
}
}
basicFARMS <- function(pmMat, pnVec, normalize, background, weight,
mu, weighted.mean,
laplacian, robust, correction, centering,
spuriousCorrelation){
pns <- unique(pnVec)
nPn <- length(unique(pnVec))
pnVec <- split(1:(length(pnVec)), pnVec)
narray <- ncol(pmMat)
if(background){
pmMat <- oligo:::backgroundCorrect(pmMat)
}
if(normalize){
pmMat <- oligo:::normalize(pmMat)
}
ini.mat <- matrix(NA, nPn, narray )
exprs.mat <- matrix(0, nPn, narray )
message("Summarizing... ", appendLF=FALSE)
for(i in 1:length(pnVec)){
if(length(pnVec[[i]])<3){
if(length(pnVec[[i]])==1){
exprs.mat[i,] <- pmMat[pnVec[[i]],]
}
else
{
exprs.mat[i,] <- colMeans(pmMat[pnVec[[i]],])
}
}
else{
res <-
generateExprVal.method.farms(probes=pmMat[pnVec[[i]],], weight=weight,
mu=mu, cyc=30, tol=0.00001,
weighted.mean=weighted.mean, robust=robust,
minNoise=minNoise, correction=correction,
laplacian=laplacian, centering=centering,
spuriousCorrelation=spuriousCorrelation)
exprs.mat[i,] <- res$exprs
ini.mat[i,] <- res$se.exprs
}
}
message("OK")
return(list(exprs=exprs.mat, se.exprs=ini.mat))
}
--
Djork-Arné Clevert, PhD
Phone: +49 30 6883 5306
Fax: +49 30 6883 5307
Email: okko@clevert.de
Am 13.11.2013 um 14:32 schrieb Fraser Sim <fjsim@buffalo.edu>:
> Hi,
>
>
>
> I am analyzing Affymetrix hugene2.0st arrays using the oligo package
and had
> hoped to be able to use informative/non-informative probe calling
(FARMS,
> Tolloen et 2007) as a means on filtering data. I had used this on
older 3'
> biased arrays analyzed with affy but the farms package only works
with an
> affyBatch object. Is this possible with another package or should I
be
> considering a different approach to filter array data on the newer
Affy
> arrays?
>
>
>
> Cheers,
>
> Fraser
>
>
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>
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