[BioC] Confusion for choosing package for microarray data analysis

[Chris Wilkinson]

Hi Yi,

I'd suggest using either limma or the marray packages for reading in data,
normalising and visualising. There is a lot of overlap between these two
packages so either should be satisfactory. When it comes to assessing
differentially expressed genes, you can use limma (linear modelling
approach), siggenes (implements SAM) or whatever else you think is
appropriate.

My understanding is that sma was developed prior to Bioconductor (and
com.braju.sma is a variant of sma developed using a different object
oriented approach), and development of sma stopped when Bioconductor was put
together. I think both the marray packages and limma were developed using
sma as a basis.

I use limma since I'm interested in using the linear modelling approach, I
think it has good help, and is undergoing active development. However I
occasionally use functions in the marray packages, or more often write my
own code to do what I want.

As you get started I'd suggest that its well worth having a good look at the
documentation and browsing through the package description. When you start
the help (html help menu in windows RGui or start.help() in linux) goto the
package section and click on limma.

Read the overview carefully which explains how to do various things in
limma.
Then look over the Introduction, classes, reading data, normalisation,
linear models and diagnostics section. From there just browse through
different functions to see what they do.  I also find its worth having a
look through the R code for limma and marray packages. You can see how
things are done and it gives you ideas on how to write your own functions.

Both limma and marray packages contain references to papers regarding
normalisation and statistical issues in microarray analysis which you might
also want to look at.
You might also want to have a look at
http://www.statsci.org/micrarra/refs.html

Cheers
Chris

Dr Chris Wilkinson

Research Officer (Bioinformatics)        | Visiting Research Fellow
Child Health Research Institute (CHRI)   | Microarray Analysis Group
7th floor, Clarence Rieger Building      | Room 121
Women's and Children's Hospital          | School of Applied Mathematics
72 King William Rd, North Adelaide, 5006 | The University of Adelaide, 5005

Math's Office (Room 121)        Ph: 8303 3714
CHRI   Office (CR2 52A)         Ph: 8161 6363

Christopher.Wilkinson at adelaide.edu.au

http://mag.maths.adelaide.edu.au/crwilkinson.html

>
> From: Yi Zou <yzou1971 at netscape.net>
> Subject: [BioC] Confusion for choosing package for microarray data
> 	analysis
> To: bioconductor at stat.math.ethz.ch
> Message-ID: <40563DE5.1050000 at netscape.net>
> Content-Type: text/plain; charset=us-ascii; format=flowed
>
> Dear list members,
>
> I'm just starting using R to analyze my cDNA microarray data. After a
> few days experience, I found there are so many different packages
> available like marray, limma, sma, com.braju.sma, siggenes...etc. Some
> of them have many functions doing the same work, and definitely each
> package may provide its specific functions. So, I'm a little confused
> for choosing these packages firstly for my following analysis. Hopefully
> experienced members can give me a short answer for these two questions:
>
> 1) Do I have to use these packages together, or just choose one that I
> feel comfortable?
>
> 2) Can somebody give me a short comparison for those most commonly used
> packages like limma, marray, sma..., especially give me a introduction
> for those specific functions in a package which are not provided in
> other packages? Then I know which package I should choose at beginning.
>
> Any answers and suggestions is appreciated
>
> Yi