Hi Xinjun.
Comments below.
On 28/04/2009, at 12:25 PM, Xinjun Zhang wrote:
> Hi Mark:
>
> Thanks very much for your clarification! Now I have approached to
> limma analysis of FIRMA score to get differentially spliced genes
> ( and also splicing pattern of each ). But I still have some
> difficulty to understand the code ( in red ) below in Limma analysis:
>
> #fs is the 'standard' FirmaSet-object
> fsDF <- extractDataFrame(fs, addNames=TRUE)
> fsDF[,-c(1:5)] <- log2(fsDF[,-c(1:5)]) # I know why log2
> is here but confused by fsDF[,c(1:5)] .... what does this expression
> mean?
Note that it is -c(1:5), meaning operate on (here, take logs) all of
the columns except 1:5 ... that is, because extractDataFrame gives
some extra columns at the beginning that are NOT data, we only want to
log that columns that have actual data.
> design <- cbind(Grp1=1,Grp2=c(rep(0,n_1),rep(1,n_2)))
> fit<-lmFit(fsDF[,-c(1:5)],design)
> fit<-eBayes(fit)
> fit$genes<-fsDF[,1] # Can I also get seperate splicing
> patterns for the two differentially spliced genes from two group
> (control and treatment )?
I'm not sure what you are asking here. The probesets where the "Grp2"
coefficient is significantly different from 0 may highlight
differentially spliced exons. Does that help?
Mark
> Thanks in advance!
>
> Xinjun
>
> On Mon, Apr 27, 2009 at 6:19 AM, Mark Robinson
> <mrobin...@wehi.edu.au> wrote:
>
>
> Hi Xinjun.
>
> Quick comments below.
>
>
> > Hi Mark:
> >
> > Thanks very much for your help and I have have got a quick start
> on a
> > small
> > dataset that each group (control and treatment ) contains 4
> arrays. I have
> > set up a file structure like this:
> > =================================================
> > rawDate/
> > controlGroup/
> > HuEx-1_0-st-v1/
> > GSMXXXXXX.CEL
> > GSMXXXXXX.CEL
> > ............................
> >
> > treatmentGroup/
> > HuEx-1_0-st-v1/
> > GSMXXXXXX.CEL
> > GSMXXXXXX.CEL
> > ............................
> > ==================================================*
>
>
> This setup will need to be changed. You will want to put ALL samples
> together to do the PLM fitting, normalization, FIRMA scoring, etc.
>
> Something like:
>
> rawData/
> thisExperiment/
> HuEx-1_0-st-v1/
> sample1.CEL
> sample2.CEL
> ...
> sampleN.CEL
>
>
> > This is my code ( my questions are in red):*
> >
> > library(aroma.affymetrix)
> >
> > #Getting annotation data files
> > chipType <- "HuEx-1_0-st-v1"
> > cdf <- AffymetrixCdfFile$byChipType(chipType)
> > print(cdf)
> >
> > #Defining CEL set
> > cs <- AffymetrixCelSet$byName("controlGroup", cdf=cdf)
> > print(cs)
> >
> > #Background Adjustment and Normalization
> > bc <- RmaBackgroundCorrection(cs)
> > csBC <- process(bc,verbose=verbose)
> >
> > #quantile normalization
> > qn <- QuantileNormalization(csBC, typesToUpdate="pm") ### I set the
> > second
> > parameter as "pm" as the chip type is Affymetrix exon array, is that
> > right?
> > print(qn)
> > csN <- process(qn, verbose=verbose)
>
> This is fine.
>
> >
> > #Summarization
> > getCdf(csN)
> > ## * Fit exon-by-exon*, change the value of mergeGroups to FALSE
> in the
> > ExonRmaPlm() call above.
> > *plmEx *<- ExonRmaPlm(csN, mergeGroups=*FALSE*)
> > print(*plmEx*)
> > #To fit the PLM to all of the data, do:
> > fit(*plmEx*, verbose=verbose)
> > *
> > And here is my problem:*
> > firma <- FirmaModel(plmTr) # I have noticd that FIRMA analysis
> ONLY works
> > from the PLM based on transcripts. So when the parameter is plmTr, I
> > wonder
> > how can it detect the splicing events of genes ? Should not the
> parameter
> > be
> > plmEx?
> > fit(firma, verbose=verbose)
> > fs <- getFirmaScores(firma)
>
> Like it says on the group web page for Exon arrays: "The FIRMA
> analysis
> ONLY works from the PLM based on transcripts". This is NOT an error.
> That's the way it works.
>
> The manuscript gives more details for why this is the case:
> http://bioinformatics.oxfordjournals.org/cgi/content/abstract/24/15/1707
>
> Hope that helps.
>
> Cheers,
> Mark
>
>
>
>
>
>
>
> >
> >
> > On Fri, Apr 24, 2009 at 5:24 PM, Mark Robinson
> > <mrobin...@wehi.edu.au>wrote:
> >
> >>
> >> Hi Xinjun.
> >>
> >> Here is a quick sketch of what I might do.
> >>
> >> 1. Run everything to get FIRMA scores. See group page for running
> >> details and the Purdom Bioinformatics 2008 paper for methodological
> >> details.
> >>
> >> 2a. If Nn or Nc > 1, use 'limma' to look for a difference in FIRMA
> >> scores between your two groups. See threads:
> >>
> >> http://groups.google.com/group/aroma-affymetrix/browse_thread/thread/36d8c59d742fc503/
> >>
> >> http://groups.google.com/group/aroma-affymetrix/browse_thread/thread/7d2645bd76cc2023/
> >>
> >> 2b. If you have say patient samples (and a good number of them),
> you
> >> might expect only a subset of your C or N patients to have a
> splicing
> >> aberration. In this case, maybe you just want to look for large-
> in-
> >> magnitude FIRMA scores.
> >>
> >> ... maybe you also want to look at interesting probesets via
> >> GenomeGraphs:
> >>
> >> http://groups.google.com/group/aroma-affymetrix/web/using-the-genomegraphs-package-with-firma
> >>
> >> Cheers,
> >> Mark
> >>
> >>
> >> On 24/04/2009, at 1:01 AM, liszt wrote:
> >>
> >> >
> >> > Hi:
> >> >
> >> > Now I have N CEL files from both normal and cancer tissue. The
> two
> >> > groups contains Nn and Nc CEL files separately (Nn = Nc). I
> want to
> >> > investigate the difference in gene's splicing pattern between
> normal
> >> > tissue and cancerous tissue. Would you give me some tips? ( I
> have
> >> > read the document and got no answers) Thanks!
> >> >
> >> > Xinjun
> >> > >
> >>
> >> ------------------------------
> >> Mark Robinson
> >> Epigenetics Laboratory, Garvan
> >> Bioinformatics Division, WEHI
> >> e: m.robin...@garvan.org.au
> >> e: mrobin...@wehi.edu.au
> >> p: +61 (0)3 9345 2628
> >> f: +61 (0)3 9347 0852
> >> ------------------------------
> >>
> >>
> >>
> >>
> >>
> >> >
> >>
> >
> > >
> >
>
>
>
>
>
>
> >
>
------------------------------
Mark Robinson
Epigenetics Laboratory, Garvan
Bioinformatics Division, WEHI
e: m.robin...@garvan.org.au
e: mrobin...@wehi.edu.au
p: +61 (0)3 9345 2628
f: +61 (0)3 9347 0852
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