Hi all,
I have been using limma now for a couple of weeks, and I think I have
pretty
much got the hang of most of it. However, now I want to analyse a
slightly
more complex experiment, can anyone give me some guidance as how to
deal
with this.
Firstly the experimental design is as follows, there are four
samples
wildtype tissue A, wildtype tissue B, mutant tissue A and mutant
tissue B.
Each sample has been compared to eachother in triplicate (inlcuding a
dye
swap, and one independant sample). To complicate things further an
additional set of WT A v WT B was also done in triplicate using a
different
method.
The slides are 7.5k oligos spotted in duplicate ( the duplicates
are in
the same block 10 rows below the first copy), although there are
control
genes which appear more than twice on the arrays. My files are imagene
output files where the cy5 and cy3 are contained in separate files.
Also
the imagene output contains spots which are flagged and would need to
be
removed from the analysis (meaning that a particular gene could have
none
one or two measurements for it).
What do you think the best strategy to deal with this design is?
Cheers
Pete
At 10:04 AM 28/10/2003, Pete wrote:
>Hi all,
>I have been using limma now for a couple of weeks, and I think I have
pretty
>much got the hang of most of it. However, now I want to analyse a
slightly
>more complex experiment, can anyone give me some guidance as how to
deal
>with this.
> Firstly the experimental design is as follows, there are four
samples
>wildtype tissue A, wildtype tissue B, mutant tissue A and mutant
tissue B.
>Each sample has been compared to eachother in triplicate (inlcuding a
dye
>swap, and one independant sample). To complicate things further an
>additional set of WT A v WT B was also done in triplicate using a
different
>method.
> The slides are 7.5k oligos spotted in duplicate ( the duplicates
are in
>the same block 10 rows below the first copy), although there are
control
>genes which appear more than twice on the arrays. My files are
imagene
>output files where the cy5 and cy3 are contained in separate files.
Also
>the imagene output contains spots which are flagged and would need to
be
>removed from the analysis (meaning that a particular gene could have
none
>one or two measurements for it).
>
>What do you think the best strategy to deal with this design is?
Well, everything in your experiment is straight down the line as far
as
limma is concerned. You haven't really said what is is about this
experiment which you're not sure how to deal with. Is the problem the
design matrix or something else?
Gordon
>Cheers
>
>Pete
Sorry I didn't explain that particularly well, firstly how do I create
a
design matrix for this experiment?
Also as far as I can see the read.imagene function doesn't read in the
flag
information for each file, in imagene each spot can have a flag value
from
0-8? and in this case we want to ignore completely anything which is
non
zero. Presumably this could be specified in the wt.fun argument, but
i'm
unsure precisely how to do this? I have tried to modify the wtflags
function
but without success.
Cheers
Pete
----- Original Message -----
From: "Gordon Smyth" <smyth@wehi.edu.au>
To: "Pete" <p.underhill@har.mrc.ac.uk>
Cc: <bioconductor@stat.math.ethz.ch>
Sent: Tuesday, October 28, 2003 2:50 AM
Subject: Re: [BioC] Limma analysis
> At 10:04 AM 28/10/2003, Pete wrote:
> >Hi all,
> >I have been using limma now for a couple of weeks, and I think I
have
pretty
> >much got the hang of most of it. However, now I want to analyse a
slightly
> >more complex experiment, can anyone give me some guidance as how to
deal
> >with this.
> > Firstly the experimental design is as follows, there are four
samples
> >wildtype tissue A, wildtype tissue B, mutant tissue A and mutant
tissue
B.
> >Each sample has been compared to eachother in triplicate (inlcuding
a dye
> >swap, and one independant sample). To complicate things further an
> >additional set of WT A v WT B was also done in triplicate using a
different
> >method.
> > The slides are 7.5k oligos spotted in duplicate ( the
duplicates are
in
> >the same block 10 rows below the first copy), although there are
control
> >genes which appear more than twice on the arrays. My files are
imagene
> >output files where the cy5 and cy3 are contained in separate files.
Also
> >the imagene output contains spots which are flagged and would need
to be
> >removed from the analysis (meaning that a particular gene could
have none
> >one or two measurements for it).
> >
> >What do you think the best strategy to deal with this design is?
>
> Well, everything in your experiment is straight down the line as far
as
> limma is concerned. You haven't really said what is is about this
> experiment which you're not sure how to deal with. Is the problem
the
> design matrix or something else?
>
> Gordon
>
> >Cheers
> >
> >Pete
>
> _______________________________________________
> Bioconductor mailing list
> Bioconductor@stat.math.ethz.ch
> https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
>
At 02:25 PM 30/10/2003, Pete wrote:
>Sorry I didn't explain that particularly well, firstly how do I
create a
>design matrix for this experiment?
I simply haven't been clever enough to figure out a way to automate
the
process of creating the design matrix for direct designs with two-
colour
arrays. Send me offline (1) your targets file (see the limma 1.3.0
manual
for the meaning of a targets file) and (2) what comparisons you want
to
make between your samples or questions you want to answer, and I will
try
to get someone to suggest a design matrix.
>Also as far as I can see the read.imagene function doesn't read in
the flag
>information for each file, in imagene each spot can have a flag value
from
>0-8? and in this case we want to ignore completely anything which is
non
>zero. Presumably this could be specified in the wt.fun argument, but
i'm
>unsure precisely how to do this? I have tried to modify the wtflags
function
>but without success.
mywtfun <- function(x) {
as.numeric(x[,"Flag"] == 0)
}
RG <- read.maimages(files, source="imagene", wt.fun=mywtfun)
Please note: I do not personally recommend ignoring flagged points in
this
way. I would personally down-weight them somewhat but would not ignore
them
completely. I don't think that spots split cleanly in this way into
good
and bad spots and I don't have anything like this sort of faith in
Imagene's (or any other program's) ability to pick one from the other.
Regards
Gordon
>Cheers
>Pete
>
>
>----- Original Message -----
>From: "Gordon Smyth" <smyth@wehi.edu.au>
>To: "Pete" <p.underhill@har.mrc.ac.uk>
>Cc: <bioconductor@stat.math.ethz.ch>
>Sent: Tuesday, October 28, 2003 2:50 AM
>Subject: Re: [BioC] Limma analysis
>
>
> > At 10:04 AM 28/10/2003, Pete wrote:
> > >Hi all,
> > >I have been using limma now for a couple of weeks, and I think I
have
>pretty
> > >much got the hang of most of it. However, now I want to analyse a
>slightly
> > >more complex experiment, can anyone give me some guidance as how
to deal
> > >with this.
> > > Firstly the experimental design is as follows, there are
four
>samples
> > >wildtype tissue A, wildtype tissue B, mutant tissue A and mutant
tissue
>B.
> > >Each sample has been compared to eachother in triplicate
(inlcuding a dye
> > >swap, and one independant sample). To complicate things further
an
> > >additional set of WT A v WT B was also done in triplicate using a
>different
> > >method.
> > > The slides are 7.5k oligos spotted in duplicate ( the
duplicates are
>in
> > >the same block 10 rows below the first copy), although there are
control
> > >genes which appear more than twice on the arrays. My files are
imagene
> > >output files where the cy5 and cy3 are contained in separate
files. Also
> > >the imagene output contains spots which are flagged and would
need to be
> > >removed from the analysis (meaning that a particular gene could
have none
> > >one or two measurements for it).
> > >
> > >What do you think the best strategy to deal with this design is?
> >
> > Well, everything in your experiment is straight down the line as
far as
> > limma is concerned. You haven't really said what is is about this
> > experiment which you're not sure how to deal with. Is the problem
the
> > design matrix or something else?
> >
> > Gordon
> >
> > >Cheers
> > >
> > >Pete
