[BioC] Read single channel GenePix in limma [was: Analyze miRNA experiment in Bioconductor]

Wed May 14 13:54:14 CEST 2008

Hi Gordon,

Thanks for you email. I've followed your steps and am getting some output now.

One problem though. When should the summarization step occur? What I
mean is that, between miRNA and control signals, my GPR file contains
about 3000 entries and when I am done with analysis topTable will
return all of these individually. But many of the miRNAs have multiple
entries in the ".gpr" file. So how, and when, should I go about
combining these into one value?

Thanks in advance,

-Paul

On Sun, May 11, 2008 at 4:59 AM, Gordon K Smyth <smyth at wehi.edu.au> wrote:
> Dear Paul,
>
>  The limma User's Guide doesn't discuss how to read single channel data, but
> how to do this has been described half a dozen times on this mailing list.
> Since limma is designed for two colours, you can fool it by giving two
> column names and ignoring the one you don't need.  If you only have the Cy3
> channel foreground for example you might use
>
>   Cy3 <- "F532 Mean"
>   RG <- read.maimages(source="genepix",columns=list(R=Cy3,G=Cy3))
>
>  then
>
>   RG$R <- NULL
>
>  to remove the extraneous values.
>
>  Then RG$G could be given as input to vsnMatrix() and the output analysed
> with lmFit().
>
>  Please don't edit your GenePix files manually, there's no need.  It's prone
> to introducing errors and is non-reproducible.
>
>  The error message "number of items to replace is not a multiple of
> replacement length" is not caused by having only one channel.  limma gives a
> far more informative message in that case.  The most likely explanation is
> that your GenePix files are not of equal lengths.  If that is indeed the
> problem, then the limma package doesn't offer any easy solution.  Your only
> approach would be to read the files in individually, then align the
> expression values yourself.
>
>  You cannot use read.maimages() with source="imagene" because you do not
> have ImaGene files.
>
>  Best wishes
>  Gordon
>
>
>
> > Date: Fri, 9 May 2008 15:54:39 +0100
> > From: "Paul Geeleher" <paulgeeleher at gmail.com>
> > Subject: Re: [BioC] Analyze miRNA experiment in Bioconductor
> > To: "Wolfgang Huber" <huber at ebi.ac.uk>
> > Cc: bioconductor at stat.math.ethz.ch
> >
> > Doesn't seem to be anything in the users guide specific to this kind
> > of analysis unfortunately.
> >
> > -Paul
> >
> > On Thu, May 8, 2008 at 10:31 AM, Wolfgang Huber <huber at ebi.ac.uk> wrote:
> >
> > > Dear Paul,
> > >
> > >
> > > > Hmm interesting. I might try introducing the extra columns into the
> > > > files and specifying all the values as 0. I can't see why that
> > > > shouldn't work?
> > > >
> > >
> > > It might, but Narendra's suggestion of reading the limma users guide is
> a
> > > worthwhile option to consider.
> > >
> > >  Best wishes
> > >       Wolfgang
> > >
> > > ------------------------------------------------------------------
> > > Wolfgang Huber  EBI/EMBL  Cambridge UK  http://www.ebi.ac.uk/huber
> > >
> > >
> > > >
> > > > -Paul
> > > >
> > > > On Wed, May 7, 2008 at 1:39 PM, Narendra Kaushik
> > > > <kaushiknk at cardiff.ac.uk> wrote:
> > > >
> > > > >
> > > > > You can specify your red channel like this:
> > > > >
> > > > >  RG <- read.maimages(files,source="genepix",  columns=list(R="F635
> > > > > Median",G="F532
> > > > >  Median",Rb="B635",Gb="B532"))
> > > > >
> > > > >  I will suggest you read limma guide.
> > > > >
> > > > >  But I think your have data from Imagene package which gives one
> file for
> > > > > each channel, you can:
> > > > >
> > > > >  files <- targets[,c("FileNameCy3","FileNameCy5")]
> > > > >  RG <- read.maimages(files, source="imagene")
> > > > >
> > > > >  Hope, this helps
> > > > >
> > > > >  Narendra
> > > > >
> > > > > >>> "Paul Geeleher" <paulgeeleher at gmail.com> 07/05/2008 13:24:01 >>>
> > > > >
> > > > >
> > > > > Hi Deepayan,
> > > > >
> > > > >  Thanks for your reply. I suppose my main concern is how I should
> read
> > > > >  in the data initially in order to be able to use the normal tools
> to
> > > > >  analyze the data. Reading the data normally like this:
> > > > >
> > > > >  RG <- read.maimages( files, source="genepix")
> > > > >
> > > > >  Gives the following error:
> > > > >
> > > > >  Error in RG[[a]][, i] <- obj[, columns[[a]]] :
> > > > >  number of items to replace is not a multiple of replacement length
> > > > >
> > > > >
> > > > >  I'm assuming this is down to the fact that the files only contain
> > > > >  intensity data for one color rather than two?
> > > > >
> > > > >  How should I go about reading the data?
> > > > >
> > > > >  Thanks alot,
> > > > >
> > > > >  -Paul.
> > > > >
> > > > >  On Tue, May 6, 2008 at 10:15 PM, Deepayan Sarkar
> > > > >  <deepayan.sarkar at gmail.com> wrote:
> > > > > > On 5/6/08, Paul Geeleher <paulgeeleher at gmail.com> wrote:
> > > > > > > Dear Members,
> > > > > > >
> > > > > > >  I've inherited a bunch of GenePix files from an miRNA
> experiment.
> > > > > They
> > > > > > >  are single color arrays, ( as opposed to 2 color as is the norm
> > > > > for
> > > > > > >  GenePix I think). There is a subset of 7 arrays and I wish to
> > > > > compare
> > > > > > >  a group of 4 of these to the other group of 3 and analyze
> > > > > differential
> > > > > > >  expression between the two groups. I was hoping somebody could
> > > > > point
> > > > > > >  me in the right direction of how I'd go about doing this with
> > > > > > >  Bioconductor? Is it possible using the Limma package? Is there
> any
> > > > > > >  code out there to assist me?
> > > > > > >
> > > > > > >  I've experience in analyzing Affymetrix data using Limma and
> PUMA,
> > > > > but
> > > > > > >  not GenePix, and the Limma Users Guide seems to focus on
> analyzing
> > > > > two
> > > > > > >  dye experiments.
> > > > > >
> > > > > >  Any analysis ultimately boils down to some sort of normalization,
> and
> > > > > >  the actual differential expression analysis. The second part in
> limma
> > > > > >  (lmFit, etc.) can work with any expression matrix, irrespective
> of
> > > > > >  whether it's 2-color or 1-color (or affy).
> > > > > >
> > > > > >  We have been working with a miRNA array dataset recently, and we
> used
> > > > > >  limma to read in the GPR files and do the differential expression
> > > > > >  analysis (on one channel). For normalization, many of the
> standard
> > > > > >  microarray algorithms probably don't make much sense, but VSN
> seems
> > > > > to
> > > > > >  work fine.
> > > > > >
> > > > > >  We don't really have code (beyond what's already in limma and
> vsn)
> > > > > >  that is generally useful; most of the work is in figuring out
> which
> > > > > >  rows are of interest (i.e., those representing human miRNAs),
> > > > > >  combining the replicates (you seem to have four of each), etc.
> I'm
> > > > > >  happy to give you more details if you are interested.
> > > > > >
> > > > > >  -Deepayan
> > > > >
> > > >
> > >
> >
>