[BioC] Analyze miRNA experiment in Bioconductor

Paul Geeleher paulgeeleher at gmail.com
Fri May 9 16:54:39 CEST 2008


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
>>>  >
>



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