Thank you for the advice On Fri, Jul 19, 2019 at 2:25 PM Sarah Goslee <sarah.gos...@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 > <spbracket...@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.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 > >> >>> >\ > > > > -- > Sarah Goslee (she/her) > http://www.numberwright.com > [[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.
