[R] How to create a data set from object/data frame?

[Spencer Brackett]

Thank you for the advice

On Fri, Jul 19, 2019 at 2:25 PM Sarah Goslee <sarah.goslee using gmail.com> wrote:

> Okay, at this point I have three suggestions, because you're clearly
> not yet understanding the R workflow.
>
> 1. Read at least the Intro to R manual.
> https://cran.r-project.org/doc/manuals/R-intro.pdf
> 2. Go through your sample code carefully, step by step, using
> functions like str() and head() to look at the R objects produced at
> each step, using ? to investigate functions you aren't familiar with,
> and thinking as you go how those R objects do and don't resemble the
> data you have.
> 3. If 1 and 2 don't help, you need to consult with your advisor,
> mentor, or if there's nobody local to you that can help, the author of
> the sample code you're using.
>
> I don't have your sample code, don't have your data, am not familiar
> with the specific functions you are using, and don't have time to
> become familiar. You need to both improve your R understanding and
> seek out guidance, ideally from someone whose job it is to help you.
>
> Best,
> Sarah
>
> On Fri, Jul 19, 2019 at 1:47 PM Spencer Brackett
> <spbrackett20 using saintjosephhs.com> wrote:
> >
> > Okay. I am a little confused as to how to proceed with that. The next
> part of the procedure as seen below appears to be substituting information
> from this fake data set into the following arguments in order to
> >
> >  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)
> >
> >  >library(affydata)
> >  > data(Dilution)
> >
> > which was made an object of the AnnotatedDataFrame via
> > >Dilution
> > >phenoData(Dilution)
> > >pData(Dilution)
> >
> > ##To access the probesets###
> >
> >  > geneNames(Dilution)[1:3] [1] "100_g_at" "1000_at" "1001_at"
> > > random.affyid <- sample(geneNames(Dilution), 1)
> > > # random.affyid <- '34803_at'
> > > ps <- probeset(Dilution, random.affyid)[[1]]
> >
> > How would I substitute in my anno object to achieve this?
> >
> >
> >
> >
> > On Fri, Jul 19, 2019 at 1:32 PM Sarah Goslee <sarah.goslee using 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
> >> <spbrackett20 using 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 <
> spbrackett20 using 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.goslee using 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
> >> >>> <spbrackett20 using 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
> >> >>> >\
>
>
>
> --
> Sarah Goslee (she/her)
> http://www.numberwright.com
>

	[[alternative HTML version deleted]]