Sarah,
Okay. I am a little confused about how to proceed. How do I substitute my
anno object for the Dilution dataset, when in these following lines of the
code, as it appears that info from the fake dataset was extracted.. ?
sample.info <- data.frame( + spl=paste('A', 1:8, sep=''), +
stat=rep(c('cancer' , 'healthy'), each=4))
>>
>> ##Then a meta data.frame object was created to give more intelligible
labels##
>>
>> > meta.info <- data.frame (labelDescription = + c('Sample Name' ,
'Cancer Status')) Then we put them all together: > pheno <-
new("AnnotatedDataFrame", + data = sample.info, + varMetadata = meta.info)
>>
>> ##Which was then aggregated together##
>>
>> > pheno <- new("AnnotatedDataFrame", + data = sample.info, + varMetadata
= meta.info)
>>
>> >my.experiments <- new("ExpressionSet", + exprs=fake.data,
phenoData=pheno)
>> > my.experiments
>> ExpressionSet (storageMode: lockedEnvironment) assayData: 200 features,
8 samples element names: exprs
>>
>> ##The following deals with further manipulating the phenoData##
>> phenoData
>> sampleNames: 1, 2, ..., 8 (8 total) varLabels and varMetadata
description: spl: Sample Name stat: Cancer Status
>>
>> featureData
>> featureNames: 1, 2, ..., 200 (200 total) fvarLabels and fvarMetadata
description: none
>> experimentData: use 'experimentData(object)'
>> Annotation:
>>
>> ##At this point is when the dataset 'Dilution was read in through
data(Dilution)
>>
>> which was made an object of the AnnotatedDataFrame via
>>
>> >phenoData(Dilution)
On Fri, Jul 19, 2019 at 1:32 PM Sarah Goslee <sarah.gos...@gmail.com> wrote:
> You don't need fake.data or rnorm(), which was used to generate the fake
> data.
>
> You need to use your real data for the analysis, not anything randomly
> generated for example purposes, or anything included with a package
> for example purposes.
>
> In both cases, those are just worked examples.You need to analyze your
> own comparable data.
>
> Sarah
>
> On Fri, Jul 19, 2019 at 12:17 PM Spencer Brackett
> <spbracket...@saintjosephhs.com> wrote:
> >
> > Sarah,
> >
> > Thank you for the reference to ?data. Upon further research into the
> matter, I think I can provide a simpler explanation than the one previously
> provided. I am trying to reproduce the following code with an object --
> 'anno' -- in my data frame/environment.
> >
> > >fake.data <- matrix(rnorm(8*200), ncol=8)
> >
> > I found the number of columns with >ncol(anno) , which is 3
> >
> > How do I find rnorm when I don't have the data table (saved as the
> 'anno' object) mean or standard dev. ?
> >
> > I will try reading in the data object through read.table() now, though
> won't that just print the data or a subset thereof into my R console?
> >
> >
> >
> > On Fri, Jul 19, 2019 at 10:46 AM Spencer Brackett <
> spbracket...@saintjosephhs.com> wrote:
> >>
> >> Sarah,
> >>
> >> I am trying to extract phenoData (ie sample information) from the
> object as part of a procedure to analyze my array for probe sets, which I
> realize is under the BioConducter package Biobase and not relevant to this
> mailing list.
> >>
> >> Yes the original procedure uses data from the Dilution dataset hosted
> in the AffyBatch package affydata. Previous to this part of the procedure,
> a dataset was create via..
> >>
> >> >fake.data <- matrix(rnorm(8*200), ncol=8)
> >> ##Then phenotype (sample) data was generated in this example through...
> ##
> >>
> >> sample.info <- data.frame( + spl=paste('A', 1:8, sep=''), +
> stat=rep(c('cancer' , 'healthy'), each=4))
> >>
> >> ##Then a meta data.frame object was created to give more intelligible
> labels##
> >>
> >> > meta.info <- data.frame (labelDescription = + c('Sample Name' ,
> 'Cancer Status')) Then we put them all together: > pheno <-
> new("AnnotatedDataFrame", + data = sample.info, + varMetadata = meta.info)
> >>
> >> ##Which was then aggregated together##
> >>
> >> > pheno <- new("AnnotatedDataFrame", + data = sample.info, +
> varMetadata = meta.info)
> >>
> >> >my.experiments <- new("ExpressionSet", + exprs=fake.data,
> phenoData=pheno)
> >> > my.experiments
> >> ExpressionSet (storageMode: lockedEnvironment) assayData: 200 features,
> 8 samples element names: exprs
> >>
> >> ##The following deals with further manipulating the phenoData##
> >> phenoData
> >> sampleNames: 1, 2, ..., 8 (8 total) varLabels and varMetadata
> description: spl: Sample Name stat: Cancer Status
> >>
> >> featureData
> >> featureNames: 1, 2, ..., 200 (200 total) fvarLabels and fvarMetadata
> description: none
> >> experimentData: use 'experimentData(object)'
> >> Annotation:
> >>
> >> ##At this point is when the dataset 'Dilution was read in through
> data(Dilution)
> >>
> >> which was made an object of the AnnotatedDataFrame via
> >>
> >> >phenoData(Dilution)
> >>
> >> My apologies in advance as I know the above info. pertains to functions
> carried out strictly through BioConducor, but is the only context I can
> provide for what I am trying to do.
> >>
> >> Best,
> >>
> >> Spencer
> >>
> >>
> >> On Fri, Jul 19, 2019 at 10:23 AM Sarah Goslee <sarah.gos...@gmail.com>
> wrote:
> >>>
> >>> Hi Spencer,
> >>>
> >>> Your description doesn't make any sense to me. If anno is already an R
> >>> object, what are you trying to do with it?
> >>>
> >>> data() is for loading datasets that come with packages; if your object
> >>> is already an R object in your environment, then there's no need for
> >>> it.
> >>>
> >>> It sounds like you are possibly working through an example provided
> >>> elsewhere, that has sample data loaded with data(). If so, then you do
> >>> not need that step for your own data. You just need to import it into
> >>> R in the correct format.
> >>>
> >>> If that doesn't help, then I think we need more information on what
> >>> you're trying to do.
> >>>
> >>> Sarah
> >>>
> >>> On Fri, Jul 19, 2019 at 10:18 AM Spencer Brackett
> >>> <spbracket...@saintjosephhs.com> wrote:
> >>> >
> >>> > Hello,
> >>> >
> >>> > I am trying to create a data set from an object called ‘anno’ in my
> >>> > environment. I’ve tried arguments like saveRDS(anno, file = “”) and
> >>> > save(anno, file “.RData”) to save the object as a file to see if
> that will
> >>> > work, but it seems for the particular procedure I am trying to carry
> out, I
> >>> > need to transpose the object to a data set. Any ideas as to how I
> might do
> >>> > this? For reference, my next step in manipulating the data contained
> in the
> >>> > object is data(), which evidently does not work for reading in data
> frame
> >>> > objects as data(“file/object name).
> >>> >
> >>> > Best,
> >>> >
> >>> > Spencer
> >>> >
> >>> > [[alternative HTML version deleted]]
> >>> >
> >>> > ______________________________________________
> >>> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >>> > 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.
> >>>
> >>>
>
[[alternative HTML version deleted]]
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