[BioC] for running arrayQualityMetrics
whuber at embl.de
Fri Mar 9 14:17:16 CET 2012
for your second question, did you have look at the HTML table at the top
of the page? This table shows what you ask for.
If you want to programmatically process the outlier detection, then
please have a look at the vignette "Advanced topics: Customizing
arrayQualityMetrics reports and programmatic processing of the output".
Also, the R object that is returned by the arrayQualityMetrics function
contains all the information shown in the report, including the outlier
Benilton Carvalho scripsit 03/09/2012 11:18 AM:
> There was no attachment with your message and I often think that's a
> good thing... I rather have the description of your environment and
> commands that you tried in the body of the email.
> Regardless, using R-2.14.1, I ran the commands that the vignette
> suggested using the MLL.A and everything worked as expected... but
> you have to open the file index.html with your browser. If you open
> only the pca.svg file with your browser, I wouldn't expect it to
> work... So, be sure to open the index.html.
> I'm not in a position to comment on your 2nd question... I'll leave
> that for Wolfgang, Audrey and others more experienced on the package
> 2012/3/9<10916037 at zju.edu.cn>:
>> hi benilton,
>> When using arrayQualityMetrics on MLL.A, an object of class
>> AffyBatch provided in the data package ALLMLL, I can get the result
>> report (Report_for_nMLL), but the report of pca.svg looks something
>> wrong, when it be opened by firefox, only plot picture appeared,
>> when moving the mouse over the points, no corresponding array's
>> metadata was displayed in a table, so would u tell me what wrong
>> with my running steps.The attachment is the result report i got,the
>> commands and sessionInfo() i used.
>> Another question, can i get all the individual array outlier
>> detection result in a table with a single call or a single run,
>> rather then moving the mouse over the points suppose i can get the
>> right pca.svg.
>> thinks very much.
>> your's henlen
>>> From: Benilton Carvalho<beniltoncarvalho at gmail.com> Reply-To: To:
>>> "henlen [guest]"<guest at bioconductor.org> Subject: Re: [BioC]
>>> arrayQualityMetrics unable to find an inherited method
>>> forfunction \\\"platformspecific\\\", for signature
>>> \\\"character\\\" Date: Thu, 8 Mar 2012 13:05:16 +0000
>>> your call is expected to be
>>> arrayQualityMetrics(expressionset = ntest, outdir =
>>> "Report_ntest", force = TRUE)
>>> note: no quotes around ntest.
>>> On 8 March 2012 12:12, henlen [guest]
>>>> when i running arrayQualityMetrics, i met a broblem like this,
>>>> Error in function (classes, fdef, mtable): unable to find an
>>>> inherited method for function "platformspecific", for signature
>>>> "character". I want to use arrayQualityMetrics to analyse
>>>> Affymetrix data- after preprocessing.
>>>> Before using arrayQualityMetrics, i used ReadAffy on my CEL
>>>> file to get an AffyBatch abject, then used RMA algorithm on the
>>>> object to obtain a preprocessed dataset, finally called
>>>> arrayQualityMetrics to analyse the preprocessed, then the error
>>>> when called ReadAffy and rma, no erros found, and i can call
>>>> the arrayQualityMetrics on the MLL.A subject provided in the
>>>> data package ALLMLL without any error.
>>>> Following is the commonds i used and the results, GSM162264.CEL
>>>> is the CEL file got from GEO.
>>>> celfile.path=NULL, sampleNames=NULL, phenoData=NULL,
>>>> description=NULL, notes="", rm.mask=FALSE, rm.outliers=FALSE,
>>>> rm.extra=FALSE, verbose=FALSE,sd=FALSE, cdfname = NULL)
>>>>> ntest = rma(test)
>>>>> arrayQualityMetrics(expressionset = "ntest",
>>>> outdir = "Report_ntest", force = TRUE) The report will be
>>>> written into directory 'Report_ntest'. Error in function
>>>> (classes, fdef, mtable) : unable to find an inherited method
>>>> for function "platformspecific", for signature "character"
>>>> AffyBatch object size of arrays=732x732 features (17 kb)
>>>> cdf=Maize (17734 affyids) number of samples=1 number of
>>>> genes=17734 annotation=maize notes=
>>>> ExpressionSet (storageMode: lockedEnvironment) assayData: 17734
>>>> features, 1 samples element names: exprs protocolData
>>>> sampleNames: GSM162264.CEL varLabels: ScanDate varMetadata:
>>>> labelDescription phenoData sampleNames: GSM162264.CEL
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