Re: [aroma.affymetrix] Re: FIRMA score for each transcript
Hi Libing.
I'm afraid that aroma.affymetrix will not work on TXT files. I
suggest you check out the following functions in the 'affxparser'
package:
?readCel (just so you know what is stored)
?createCel (to create the file)
?updateCel (to store intensities in the file)
Once you figure out the inputs for those functions It should be pretty
straightforward to take your simulated data and push it into a CEL file.
Hope that helps.
Cheers,
Mark
On 16-Dec-09, at 5:14 AM, Libing Wang wrote:
> Hi Mark,
>
> Thanks a lot for your help!
> Now I want to work with some simulated data with aroma to calculate
> summarized intensities of probesets. The problem is that I only have
> a txt file with original probe signal intensities but aroma could be
> only fed by cel files. Is it possible let aroma work with txt files?
> If not, are there any ways to construct cel files from txt files?
> Thanks! /Libing
>
> On Fri, Nov 6, 2009 at 6:35 AM, Mark Robinson
> wrote:
> Hi Libing.
>
> Are you after the probe IDs from the probe.tab file? For example:
>
> Probe IDProbe Set IDprobe x probe y assembly
> seqname start stop
> strand probe sequence target strandedness category
> 4485910 2315252 789 1752build-34/hg16 chr1407616
> 407640 +
> GTAATGCTTGCCACATAGAGCACAG Sense main
> 2412400 2315252 879 942 build-34/hg16 chr1408027
> 408051 +
> AAGCTGTCCAACACATTAGGGCCAC Sense main
> 4260180 2315252 339 1664build-34/hg16 chr1408088
> 408112 +
> GAACTGCAATCTGTAGGTGTCGGTA Sense main
> 5750312 2315252 551 2246build-34/hg16 chr1408300
> 408324 +
> TCCATCTGTGAATTAGGGTGTGGCC Sense main
> 2959753 2315253 392 1156build-34/hg16 chr1408431
> 408455 +
> AGATCCTCTTGTAAATCACTAGCTG Sense main
> 294823 2315253 422 115 build-34/hg16 chr1408433
> 408457 +
> TGAGATCCTCTTGTAAATCACTAGC Sense main
> 5504333 2315253 332 2150build-34/hg16 chr1408434
> 408458 +
> ATGAGATCCTCTTGTAAATCACTAG Sense main
> 1224013 2315253 332 478 build-34/hg16 chr1408436
> 408460 +
> TTATGAGATCCTCTTGTAAATCACT Sense main
>
>
> If so, you could make a lookup table from that and match them to the
> info in your CDF file. For example:
>
> > cdf <- AffymetrixCdfFile$byChipType("HuEx-1_0-st-v2",
> tag="coreR3,A20071112,EP")
> > u <- readUnits(cdf, units=1, readBases=FALSE, readExpos=FALSE,
> readType=FALSE, readDirection=FALSE)
> > u
> $`2315251`
> $`2315251`$groups
> $`2315251`$groups$`2315252`
> $`2315251`$groups$`2315252`$x
> [1] 789 339 879 551
>
> $`2315251`$groups$`2315252`$y
> [1] 1752 1664 942 2246
>
>
> $`2315251`$groups$`2315253`
> $`2315251`$groups$`2315253`$x
> [1] 332 422 392 332
>
> $`2315251`$groups$`2315253`$y
> [1] 2150 115 1156 478
>
> ... so if you read your BG adjusted intensities into a matrix, you
> could annotate each row with the probe ID.
>
> Is that what you had in mind? If so, hope that gets you started.
>
> Cheers,
> Mark
>
>
>
> On 3-Nov-09, at 6:50 AM, Libing Wang wrote:
>
> > Hi Mark,
> >
> > Thanks for your help so far! Now I have a quick question for you. Is
> > there any ways to get the probe ID for background corrected probe
> > intensities? If I have finish the following steps:
> >
> > bc <- RmaBackgroundCorrection(cs, tag="core,A20071112,EP")
> > csBC <- process(bc, verbose=verbose)
> >
> > Thanks!
> >
> > Libing
> >
> > On Wed, Jun 17, 2009 at 6:18 PM, Mark Robinson
> > wrote:
> >
> >
> > 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 23152521 11 1.1150999
> > 2 2315251 23152531 22 0.9551846
> > 3 2315373 23153742 13 1.5354252
> > 4 2315373 23153752 24 0.6288152
> > 5 2315373 23153762 35 1.5658265
> > 6 2315373 23153772 46 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
> > 11 11 1.1150999 0.8552212
> > 0.9177643
> > 21 22 0.9551846 1.1747438
> > 0.8580346
> > 32 13 1.5354252 1.0427089
> > 1.6461661
> > 42 24 0.6288152 0.7053325
> > 0.6999596
> > 52 35 1.5658265 1.0576524
> > 1.1404822
> > 62 46 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 uni
Re: [aroma.affymetrix] Re: FIRMA score for each transcript
Hi Mark,
Thanks a lot for your help!
Now I want to work with some simulated data with aroma to calculate
summarized intensities of probesets. The problem is that I only have a txt
file with original probe signal intensities but aroma could be only fed by
cel files. Is it possible let aroma work with txt files? If not, are there
any ways to construct cel files from txt files? Thanks! /Libing
On Fri, Nov 6, 2009 at 6:35 AM, Mark Robinson wrote:
> Hi Libing.
>
> Are you after the probe IDs from the probe.tab file? For example:
>
> Probe IDProbe Set IDprobe x probe y assemblyseqname
> start stop
> strand probe sequence target strandedness category
> 4485910 2315252 789 1752build-34/hg16 chr1407616 407640 +
> GTAATGCTTGCCACATAGAGCACAG Sense main
> 2412400 2315252 879 942 build-34/hg16 chr1408027 408051 +
> AAGCTGTCCAACACATTAGGGCCAC Sense main
> 4260180 2315252 339 1664build-34/hg16 chr1408088 408112 +
> GAACTGCAATCTGTAGGTGTCGGTA Sense main
> 5750312 2315252 551 2246build-34/hg16 chr1408300 408324 +
> TCCATCTGTGAATTAGGGTGTGGCC Sense main
> 2959753 2315253 392 1156build-34/hg16 chr1408431 408455 +
> AGATCCTCTTGTAAATCACTAGCTG Sense main
> 294823 2315253 422 115 build-34/hg16 chr1408433 408457 +
> TGAGATCCTCTTGTAAATCACTAGC Sense main
> 5504333 2315253 332 2150build-34/hg16 chr1408434 408458 +
> ATGAGATCCTCTTGTAAATCACTAG Sense main
> 1224013 2315253 332 478 build-34/hg16 chr1408436 408460 +
> TTATGAGATCCTCTTGTAAATCACT Sense main
>
>
> If so, you could make a lookup table from that and match them to the
> info in your CDF file. For example:
>
> > cdf <- AffymetrixCdfFile$byChipType("HuEx-1_0-st-v2",
> tag="coreR3,A20071112,EP")
> > u <- readUnits(cdf, units=1, readBases=FALSE, readExpos=FALSE,
> readType=FALSE, readDirection=FALSE)
> > u
> $`2315251`
> $`2315251`$groups
> $`2315251`$groups$`2315252`
> $`2315251`$groups$`2315252`$x
> [1] 789 339 879 551
>
> $`2315251`$groups$`2315252`$y
> [1] 1752 1664 942 2246
>
>
> $`2315251`$groups$`2315253`
> $`2315251`$groups$`2315253`$x
> [1] 332 422 392 332
>
> $`2315251`$groups$`2315253`$y
> [1] 2150 115 1156 478
>
> ... so if you read your BG adjusted intensities into a matrix, you
> could annotate each row with the probe ID.
>
> Is that what you had in mind? If so, hope that gets you started.
>
> Cheers,
> Mark
>
>
>
> On 3-Nov-09, at 6:50 AM, Libing Wang wrote:
>
> > Hi Mark,
> >
> > Thanks for your help so far! Now I have a quick question for you. Is
> > there any ways to get the probe ID for background corrected probe
> > intensities? If I have finish the following steps:
> >
> > bc <- RmaBackgroundCorrection(cs, tag="core,A20071112,EP")
> > csBC <- process(bc, verbose=verbose)
> >
> > Thanks!
> >
> > Libing
> >
> > On Wed, Jun 17, 2009 at 6:18 PM, Mark Robinson
> > wrote:
> >
> >
> > 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 23152521 11 1.1150999
> > 2 2315251 23152531 22 0.9551846
> > 3 2315373 23153742 13 1.5354252
> > 4 2315373 23153752 24 0.6288152
> > 5 2315373 23153762 35 1.5658265
> > 6 2315373 23153772 46 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
> > 11 11 1.1150999 0.8552212
> > 0.9177643
> > 21 22 0.9551846 1.1747438
> > 0.8580346
> > 32 13 1.5354252 1.0427089
> > 1.6461661
> > 42 24 0.6288152 0.7053325
> > 0.6999596
> > 52 35 1.5658265 1.0576524
> > 1.1404822
> > 62 46 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
> > > 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
> > > differenti
Re: [aroma.affymetrix] Re: FIRMA score for each transcript
Hi Mark,
Thanks for your help so far! Now I have a quick question for you. Is there
any ways to get the probe ID for background corrected probe intensities? If
I have finish the following steps:
bc <- RmaBackgroundCorrection(cs, tag="core,A20071112,EP")
csBC <- process(bc, verbose=verbose)
Thanks!
Libing
On Wed, Jun 17, 2009 at 6:18 PM, Mark Robinson wrote:
>
>
> 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 23152521 11 1.1150999
> 2 2315251 23152531 22 0.9551846
> 3 2315373 23153742 13 1.5354252
> 4 2315373 23153752 24 0.6288152
> 5 2315373 23153762 35 1.5658265
> 6 2315373 23153772 46 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
> 11 11 1.1150999 0.8552212 0.9177643
> 21 22 0.9551846 1.1747438 0.8580346
> 32 13 1.5354252 1.0427089 1.6461661
> 42 24 0.6288152 0.7053325 0.6999596
> 52 35 1.5658265 1.0576524 1.1404822
> 62 46 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
> > 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
> >
> > > 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?
> > >> >
>
[aroma.affymetrix] Re: FIRMA score for each transcript
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 23152521 11 1.1150999
2 2315251 23152531 22 0.9551846
3 2315373 23153742 13 1.5354252
4 2315373 23153752 24 0.6288152
5 2315373 23153762 35 1.5658265
6 2315373 23153772 46 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
11 11 1.1150999 0.8552212 0.9177643
21 22 0.9551846 1.1747438 0.8580346
32 13 1.5354252 1.0427089 1.6461661
42 24 0.6288152 0.7053325 0.6999596
52 35 1.5658265 1.0576524 1.1404822
62 46 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
> 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
>
> > 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
> >> > 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)
> >
[aroma.affymetrix] Re: FIRMA score for each transcript
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 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
> > 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
> >> > 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
[aroma.affymetrix] Re: FIRMA score for each transcript
Hi Mark, is there any chance to get more info on your just accepted for publication gene-level splicing score? I would be highly interested. I have a number of exon-array data from brain tumors of different severities and would like to get a score for genes likely differentially spliced between severity groups. Best regards, Peter. On Apr 7, 11:35 pm, Mark Robinson 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 > -- --~--~-~--~~~---~--~~ 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 -~--~~~~--~~--~--~---
[aroma.affymetrix] Re: FIRMA score for each transcript
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
> 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
>> > 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 9
[aroma.affymetrix] Re: FIRMA score for each transcript
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 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
> > 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
> --
>
>
>
>
>
> >
>
--~--~-~--~~~---~--~~
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
-~--~~~~--~~--~--~---
[aroma.affymetrix] Re: FIRMA score for each transcript
Hi Mark, Thanks for your reply! Now I am wondering if it is possible to test if expression level of each transcript is different between chips using probeset intensities. Thanks! /Libing On Tue, Apr 7, 2009 at 5:54 PM, Mark Robinson 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 > > 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 > -- > > > > > > > > --~--~-~--~~~---~--~~ 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 -~--~~~~--~~--~--~---
[aroma.affymetrix] Re: FIRMA score for each transcript
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 > 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 -- --~--~-~--~~~---~--~~ 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 -~--~~~~--~~--~--~---
[aroma.affymetrix] Re: FIRMA score for each transcript
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 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 > -- > > > > > > > > --~--~-~--~~~---~--~~ 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 -~--~~~~--~~--~--~---
[aroma.affymetrix] Re: FIRMA score for each transcript
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 -- --~--~-~--~~~---~--~~ 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 -~--~~~~--~~--~--~---
