I've since seen your followup a more detailed explanation may help.
The path through the code for your argument list does not go where you
quoted, and there is a reason for it.
Generally when you extract in R and ask for an non-existent index you get
NA or NULL as the result (and no warning), e.g.
> y <- list(x=1, y=2)
> y[["z"]]
NULL
Because data frames 'must' have (column) names, they are a partial
exception and when the result is a data frame you get an error if it would
contain undefined columns.
But in the case of foo[, "FileName"], the result is a single column and so
will not have a name: there seems no reason to be different from
> foo[["FileName"]]
NULL
> foo$FileName
NULL
which similarly select a single column. At one time they were different
in R, for no documented reason.
On Fri, 3 Aug 2007, Prof Brian Ripley wrote:
> You are reading the wrong part of the code for your argument list:
>
>> foo["FileName"]
> Error in `[.data.frame`(foo, "FileName") : undefined columns selected
>
> [.data.frame is one of the most complex functions in R, and does many
> different things depending on which arguments are supplied.
>
>
> On Fri, 3 Aug 2007, Steven McKinney wrote:
>
>> Hi all,
>>
>> What are current methods people use in R to identify
>> mis-spelled column names when selecting columns
>> from a data frame?
>>
>> Alice Johnson recently tackled this issue
>> (see [BioC] posting below).
>>
>> Due to a mis-spelled column name ("FileName"
>> instead of "Filename") which produced no warning,
>> Alice spent a fair amount of time tracking down
>> this bug. With my fumbling fingers I'll be tracking
>> down such a bug soon too.
>>
>> Is there any options() setting, or debug technique
>> that will flag data frame column extractions that
>> reference a non-existent column? It seems to me
>> that the "[.data.frame" extractor used to throw an
>> error if given a mis-spelled variable name, and I
>> still see lines of code in "[.data.frame" such as
>>
>> if (any(is.na(cols)))
>> stop("undefined columns selected")
>>
>>
>>
>> In R 2.5.1 a NULL is silently returned.
>>
>>> foo <- data.frame(Filename = c("a", "b"))
>>> foo[, "FileName"]
>> NULL
>>
>> Has something changed so that the code lines
>> if (any(is.na(cols)))
>> stop("undefined columns selected")
>> in "[.data.frame" no longer work properly (if
>> I am understanding the intention properly)?
>>
>> If not, could "[.data.frame" check an
>> options() variable setting (say
>> warn.undefined.colnames) and throw a warning
>> if a non-existent column name is referenced?
>>
>>
>>
>>
>>> sessionInfo()
>> R version 2.5.1 (2007-06-27)
>> powerpc-apple-darwin8.9.1
>>
>> locale:
>> en_CA.UTF-8/en_CA.UTF-8/en_CA.UTF-8/C/en_CA.UTF-8/en_CA.UTF-8
>>
>> attached base packages:
>> [1] "stats" "graphics" "grDevices" "utils" "datasets" "methods"
>> "base"
>>
>> other attached packages:
>> plotrix lme4 Matrix lattice
>> "2.2-3" "0.99875-4" "0.999375-0" "0.16-2"
>>>
>>
>>
>>
>> Steven McKinney
>>
>> Statistician
>> Molecular Oncology and Breast Cancer Program
>> British Columbia Cancer Research Centre
>>
>> email: smckinney +at+ bccrc +dot+ ca
>>
>> tel: 604-675-8000 x7561
>>
>> BCCRC
>> Molecular Oncology
>> 675 West 10th Ave, Floor 4
>> Vancouver B.C.
>> V5Z 1L3
>> Canada
>>
>>
>>
>>
>> -----Original Message-----
>> From: [EMAIL PROTECTED] on behalf of Johnstone, Alice
>> Sent: Wed 8/1/2007 7:20 PM
>> To: [EMAIL PROTECTED]
>> Subject: Re: [BioC] read.phenoData vs read.AnnotatedDataFrame
>>
>> For interest sake, I have found out why I wasn't getting my expected
>> results when using read.AnnotatedDataFrame
>> Turns out the error was made in the ReadAffy command, where I specified
>> the filenames to be read from my AnnotatedDataFrame object. There was a
>> typo error with a capital N ($FileName) rather than lowercase n
>> ($Filename) as in my target file..whoops. However this meant the
>> filename argument was ignored without the error message(!) and instead
>> of using the information in the AnnotatedDataFrame object (which
>> included filenames, but not alphabetically) it read the .cel files in
>> alphabetical order from the working directory - hence the wrong file was
>> given the wrong label (given by the order of Annotated object) and my
>> comparisons were confused without being obvious as to why or where.
>> Our solution: specify that filename is as.character so assignment of
>> file to target is correct(after correcting $Filename) now that using
>> read.AnnotatedDataFrame rather than readphenoData.
>>
>> Data<-ReadAffy(filenames=as.character(pData(pd)$Filename),phenoData=pd)
>>
>> Hurrah!
>>
>> It may be beneficial to others, that if the filename argument isn't
>> specified, that filenames are read from the phenoData object if included
>> here.
>>
>> Thanks!
>>
>> -----Original Message-----
>> From: Martin Morgan [mailto:[EMAIL PROTECTED]
>> Sent: Thursday, 26 July 2007 11:49 a.m.
>> To: Johnstone, Alice
>> Cc: [EMAIL PROTECTED]
>> Subject: Re: [BioC] read.phenoData vs read.AnnotatedDataFrame
>>
>> Hi Alice --
>>
>> "Johnstone, Alice" <[EMAIL PROTECTED]> writes:
>>
>>> Using R2.5.0 and Bioconductor I have been following code to analysis
>>> Affymetrix expression data: 2 treatments vs control. The original
>>> code was run last year and used the read.phenoData command, however
>>> with the newer version I get the error message Warning messages:
>>> read.phenoData is deprecated, use read.AnnotatedDataFrame instead The
>>> phenoData class is deprecated, use AnnotatedDataFrame (with
>>> ExpressionSet) instead
>>>
>>> I use the read.AnnotatedDataFrame command, but when it comes to the
>>> end of the analysis the comparison of the treatment to the controls
>>> gets mixed up compared to what you get using the original
>>> read.phenoData ie it looks like the 3 groups get labelled wrong and so
>>
>>> the comparisons are different (but they can still be matched up).
>>> My questions are,
>>> 1) do you need to set up your target file differently when using
>>> read.AnnotatedDataFrame - what is the standard format?
>>
>> I can't quite tell where things are going wrong for you, so it would
>> help if you can narrow down where the problem occurs. I think
>> read.AnnotatedDataFrame should be comparable to read.phenoData. Does
>>
>>> pData(pd)
>>
>> look right? What about
>>
>>> pData(Data)
>>
>> and
>>
>>> pData(eset.rma)
>>
>> ? It's not important but pData(pd)$Target is the same as pd$Target.
>> Since the analysis is on eset.rma, it probably makes sense to use the
>> pData from there to construct your design matrix
>>
>>> targs<-factor(eset.rma$Target)
>>> design<-model.matrix(~0+targs)
>>> colnames(design)<-levels(targs)
>>
>> Does design look right?
>>
>>> I have three columns sample, filename and target.
>>> 2) do you need to use a different model matrix to what I have?
>>> 3) do you use a different command for making the contrasts?
>>
>> Depends on the question! If you're performing the same analysis as last
>> year, then the model matrix and contrasts have to be the same!
>>
>>> I have included my code below if that is of any assistance.
>>> Many Thanks!
>>> Alice
>>>
>>>
>>>
>>> ##Read data
>>> pd<-read.AnnotatedDataFrame("targets.txt",header=T,row.name="sample")
>>> Data<-ReadAffy(filenames=pData(pd)$FileName,phenoData=pd)
>>> ##normalisation
>>> eset.rma<-rma(Data)
>>> ##analysis
>>> targs<-factor(pData(pd)$Target)
>>> design<-model.matrix(~0+targs)
>>> colnames(design)<-levels(targs)
>>> fit<-lmFit(eset.rma,design)
>>> cont.wt<-makeContrasts("treatment1-control","treatment2-control",level
>>> s=
>>> design)
>>> fit2<-contrasts.fit(fit,cont.wt)
>>> fit2.eb<-eBayes(fit2)
>>> testconts<-classifyTestsF(fit2.eb,p.value=0.01)
>>> topTable(fit2.eb,coef=2,n=300)
>>> topTable(fit2.eb,coef=1,n=300)
>>>
>>>
>>> [[alternative HTML version deleted]]
>>>
>>> _______________________________________________
>>> Bioconductor mailing list
>>> [EMAIL PROTECTED]
>>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>>> Search the archives:
>>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>>
>> --
>> Martin Morgan
>> Bioconductor / Computational Biology
>> http://bioconductor.org
>>
>> _______________________________________________
>> Bioconductor mailing list
>> [EMAIL PROTECTED]
>> https://stat.ethz.ch/mailman/listinfo/bioconductor
>> Search the archives:
>> http://news.gmane.org/gmane.science.biology.informatics.conductor
>>
>> ______________________________________________
>> R-help@stat.math.ethz.ch mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
______________________________________________
R-help@stat.math.ethz.ch mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
