[BioC] edgeR query
shravanthipsg at gmail.com
Wed Sep 5 14:16:13 CEST 2012
Thanks a lot for correcting my error. I have downloaded the Limma
package(it seems to be majorly for spotted microarray as opposed to
oligonucleotides microarry). I am having trouble even reading my data
into R. I have the tab delimited format file for a series (eg GSE9936)
.How do I read and initialize it to an object in R? And how to I
define groups within this file for a comparison.Limma user manual
directed me to use the affy package for normalizing data.Can I not use
the already available normalized data ?
I have a time constraint and was hoping to avoid this step.
My aim is to find the up regulated and downregulated genes in breast
cancer cells when treated with Genistein on a time progression basis
(with a constant concentration)
On 9/5/12, Steve Lianoglou <mailinglist.honeypot at gmail.com> wrote:
> Hi Shravanthi,
> On Tue, Sep 4, 2012 at 6:33 AM, Shravanthi P <shravanthipsg at gmail.com>
>> I am new to using R and my project is on differential gene expression .I
>> was told to use Edger but I am having trouble reading a tab delimited
>> format data for affy oligonucleotide microarray data .
>> How can I read the data into R ? and how can I identify the upregulated
>> downregulated genes ?
> The bad news is that you've got a long way to go before you can get
> from where you are to where you want to be. The good news is that
> there are a lot of resources available for your self study that can
> help you get to where you want to be.
> It would be in your best interest to learn more about R first (start
> with an intro to R) before you try to do anything more serious.
> After you do that, and you then read the (very helpful) edgeR user
> manual (as Wenhuo already suggested) -- you'll probably come to the
> realization that edgeR is the wrong tool for this job. You have
> microarray data and edgeR is used for sequencing data.
> In this case, you'll find that the limma package is probably what
> you're after. Fortunately for you, there is a very thorough limma user
> guide that you can read through that gives you some idea of how to
> process different types of microarray data. The goods at the link
> below (and the associated packages) are worth some study as well:
> Steve Lianoglou
> Graduate Student: Computational Systems Biology
> | Memorial Sloan-Kettering Cancer Center
> | Weill Medical College of Cornell University
> Contact Info: http://cbio.mskcc.org/~lianos/contact
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