Hi Libing.
Doesn't 'addNames=TRUE' already do this for you?
> fs1 <- extractDataFrame(fs, units=1:2, addNames=TRUE)
> head(fs1[,1:6])
unitName groupName unit group cell huex_wta_breast_A
1 2315251 2315252 1 1 1 1.1150999
2 2315251 2315253 1 2 2 0.9551846
3 2315373 2315374 2 1 3 1.5354252
4 2315373 2315375 2 2 4 0.6288152
5 2315373 2315376 2 3 5 1.5658265
6 2315373 2315377 2 4 6 1.2131032
> fs2 <- extractDataFrame(fs, units=1:2, addNames=FALSE)
> head(fs2[,1:6])
unit group cell huex_wta_breast_A huex_wta_breast_B huex_wta_breast_C
1 1 1 1 1.1150999 0.8552212 0.9177643
2 1 2 2 0.9551846 1.1747438 0.8580346
3 2 1 3 1.5354252 1.0427089 1.6461661
4 2 2 4 0.6288152 0.7053325 0.6999596
5 2 3 5 1.5658265 1.0576524 1.1404822
6 2 4 6 1.2131032 1.0494679 0.7729633
If not, please send your entire script and the output of sessionInfo().
Cheers,
Mark
On 18/06/2009, at 1:02 AM, Libing Wang wrote:
> Hi Mark,
>
> I am wondering if it is possible to get the actual unit
> id(transcript cluster id) and group id(probeset id) for each firma
> score instead of artificial number from 1 to whatever in the firma
> score data frame.
>
> Thanks,
>
> Libing
>
> On Sat, Apr 11, 2009 at 5:48 PM, Mark Robinson
> <mrobin...@wehi.edu.au> wrote:
>
> Hi Libing.
>
> As the error message suggests, there are no degrees of freedom for the
> fit, meaning you have no replicates. It appears you only have 2 total
> samples, one for each group. You wouldn't be able to use limma to do
> differential expression on any experiment with only 2 1-channel chips.
>
> If that is all the data you have, perhaps you are best off looking for
> large (positive or negative) values of the difference:
>
> fsdf <- extractDataFrame(fs, addNames=TRUE)
> fsdf[,6:ncol(fsdf)] <- log2(fsdf[,6:ncol(fsdf)])
>
> fsdf[,7] - fsdf[,6] # B-A, assuming you've already taken logs
>
> Cheers,
> mark
>
>
>
> > Hi Mark,
> >
> > I am trying to find differences of FIRMA scores between two chips
> and
> > don't
> > know what's wrong:
> >
> >> cls <- c("A","B")
> >> mm <- model.matrix(~cls)
> > Warning message:
> > In model.matrix.default(~cls) : variable 'cls' converted to a factor
> >> fit <- lmFit(fsdf[,6:7], mm)
> > Warning message:
> > In lmFit(fsdf[, 6:7], mm) :
> > Some coefficients not estimable: coefficient interpretation may
> vary.
> >> fit <- eBayes(fit)
> > Error in ebayes(fit = fit, proportion = proportion, stdev.coef.lim =
> > stdev.coef.lim) :
> > No residual degrees of freedom in linear model fits
> >
> > Thanks,
> >
> > Libing
> >
> > On Tue, Apr 7, 2009 at 5:54 PM, Mark Robinson
> <mrobin...@wehi.edu.au>
> > wrote:
> >
> >>
> >> Hi Libing.
> >>
> >> limma has quite an extensive user manual. See link to it:
> >> http://www.bioconductor.org/packages/release/bioc/html/limma.html
> >>
> >> Your response still puzzles me. You say your wording should've
> been
> >> 'splicing' not 'expression', but then you go on to say that you
> want
> >> to do differential *expression* with limma.
> >>
> >> However, note that you can use limma on FIRMA scores as well, as
> >> discussed previously. If that is what you are interested in, you
> >> might check the following thread:
> >>
> >> http://groups.google.com/group/aroma-affymetrix/browse_thread/thread/36d8c59d742fc503/
> >>
> >> If you give a more detailed description of what it is you are
> doing or
> >> want to do, I might be better able to help.
> >>
> >> Cheers,
> >> Mark
> >>
> >> On 08/04/2009, at 8:10 AM, Libing Wang wrote:
> >>
> >> > Hi Mark,
> >> >
> >> > Thank you for your reply!
> >> > Sorry for my wrong wording! It should be "splicing" not
> "expression".
> >> >
> >> > ... then you can use log2 of the chip effects here for an
> analysis of
> >> > differential expression with an appropriate design matrix with
> limma.
> >> > Is that what you are after?
> >> >
> >> > Yes, this is what I want. I think I need process Affymetrix
> probeset
> >> > file to correlate probesets and transcripts, then use limma to do
> >> > the analysis. I am pretty new to limma, do you have any
> suggestions?
> >> >
> >> > Thanks,
> >> >
> >> > Libing
> >> >
> >> > On Tue, Apr 7, 2009 at 4:35 PM, Mark Robinson
> >> > <mrobin...@wehi.edu.au> wrote:
> >> >
> >> > Hi Libing.
> >> >
> >> >
> >> > On 08/04/2009, at 1:42 AM, Libing Wang wrote:
> >> >
> >> > > Hi,
> >> > >
> >> > > I am wondering if there is a way to compute a FIRMA score for
> each
> >> > > transcript. Currently I only have FIRMA score for each
> probeset or
> >> > > group. I did as follows:
> >> > >
> >> > > 1. plmTr <- ExonRmaPlm(csN, mergeGroups=TRUE)
> >> > > 2. fit(plmTr)
> >> > > 3. firma<-FirmaModel(plmTr)
> >> > > 4.fit(firma)
> >> > > 5.fs<-getFirmaScores(firma)
> >> >
> >> > The short answer is that FIRMA scores are really a probeset-level
> >> > statistic, not a gene/transcript-level statistic. This is the
> >> > recommended use of FIRMA.
> >> >
> >> >
> >> > > Or with the FIRMA score of each probeset, find out which
> >> > > transcripts are differentially expressed.
> >> >
> >> > This statement puzzles me. FIRMA is really going after
> differential
> >> > *splicing*, not differential expression. If you want
> differential
> >> > expression, you could do something like:
> >> >
> >> > ces <- getChipEffectSet(plmTr)
> >> > gExprs <- extractDataFrame(ces, addNames=TRUE)
> >> >
> >> > ... then you can use log2 of the chip effects here for an
> analysis of
> >> > differential expression with an appropriate design matrix with
> limma.
> >> > Is that what you are after?
> >> >
> >> > Alternatively, I am working on a gene-level score for splicing,
> just
> >> > accepted for publication. This is meant to be applied to the
> Affy
> >> > Gene 1.0 ST arrays (or similar) but could be applied to the Exon
> >> > arrays. This would give a gene-level scoring of splicing.
> >> >
> >> > Cheers,
> >> > Mark
> >> >
> >> >
> >> > >
> >> > > Now I am trying to use limma to solve my problems and want some
> >> > > directions if anyone knows.
> >> > >
> >> > > Thanks,
> >> > >
> >> > > Libing
> >> > >
> >> > > >
> >> > >
> >> >
> >> > ------------------------------
> >> > 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
> >> ------------------------------
> >>
> >>
> >>
> >>
> >>
> >> >
> >>
> >
> > >
> >
>
>
>
>
> >
>
------------------------------
Mark Robinson, PhD (Melb)
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
------------------------------
--~--~---------~--~----~------------~-------~--~----~
When reporting problems on aroma.affymetrix, make sure 1) to run the latest
version of the package, 2) to report the output of sessionInfo() and
traceback(), and 3) to post a complete code example.
You received this message because you are subscribed to the Google Groups
"aroma.affymetrix" group.
To post to this group, send email to aroma-affymetrix@googlegroups.com
To unsubscribe from this group, send email to
aroma-affymetrix-unsubscr...@googlegroups.com
For more options, visit this group at
http://groups.google.com/group/aroma-affymetrix?hl=en
-~----------~----~----~----~------~----~------~--~---
