[BioC] Affy! From raw data files to Summary expression value without expresso!
James W. MacDonald
jmacdon at med.umich.edu
Tue Dec 5 15:11:54 CET 2006
The problem with doing your own method is that you have to watch closely
what you are doing, and be very familiar with the help pages.
The Höning wrote:
> Dear list,
> I calculated correction values for each probe cell. I do the following:
> Reading the cel-files in an AffyBatch:
> Expfiles <- c("1.CEL","2.CEL","3.CEL","4.CEL")
> chips = ReadAffy(filenames = Expfiles)
> Performing background correction:
> Chips.bg.mas <- bg.correct(chips, method ="mas")
> Performing normalization:
> Chips.norm.quantile.mas <- normalize(Chips.bg.mas, method ="constant")
> Performing correction
> Chips.norm.quantile.mas at exprs <- Chips.norm.quantile.mas at exprs*correctionMAS
Not sure what correctionMAS is here, but let's assume it is either a
scalar or a vector.
> ### Not done when I tried express.summary.stat..
> performing pmcorrection
> Chips.PM.Mas <- pmcorrect.mas(Chips.norm.quantile.mas)
Now if you do class(Chips.PM.Mas), you will get 'matrix'.
> And now I want to use the method "computeExprSet" to calculate an ExprSet.
Unfortunately, the arguments for computeExprSet are
x: a 'AffyBatch' holding the probe level informations to
generate the expression values.
But you are passing a matrix, hence you get the following error.
> But I receive the following error:
> error in ......
> no direct or inherited method for function '...' for this call
> The same when I try
> error in express.summary.stat(Chips.norm.quantile.mas, summary = "mas", :
> no direct or inherited method for function 'express.summary.stat' for this call
Again, the help page for this function states:
x: a ('ProbeSet'
But you are passing an AffyBatch, not a ProbeSet. NB - this is an old
function (as are all functions that take a ProbeSet as their input), and
may not work as intended any longer.
Most of the 'roll-your-own' functions in the affy package were developed
in the days when people were still arguing over the best method to use
for affy data. In the intervening time it appears (to me at least) that
people have settled on their favorite method, so these legacy functions
are no longer used as much and hence might not be maintained as
rigorously as e.g., rma(). In fact, last I heard Rafa was considering
taking expresso() and friends out of the affy package because they don't
appear to be used much, and are a pain to maintain.
> Any ideas ?
> Gunther Höning
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
James W. MacDonald, M.S.
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
Ann Arbor MI 48109
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