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Old 04-13-2012, 07:50 AM   #1
himanshu04
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Location: New York

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Default Affymetrix HT 430 Mouse genome data

Hello everyone,
This might be a very simple question to all but I am new to this field and want to learn about the high throughput analysis.
I have two cel files generated from Affy HT430MG arrays. One is a control and other is the treated . I want a list of differentially expressed genes in the treatment as compared to the control.
For this , I used the affy package in R/Bioconductor and used rma for normalization and background correction. I got a .txt file with the different expression levels.
But now I want to annotate the probes and find out in what way do they affect certain pathways.
What will be a good approach to go ahead with it.?
Any help is much appreciated.
Thanks a lot,
Himanshu
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Old 04-13-2012, 09:33 AM   #2
TonyBrooks
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You're on the wrong forum. This is for high throughput sequencing, not microarray work.
I'll attempt to answer your question anyway.
Firstly, you should really have run replicates as statistically the results from a 2 array experiment will be pretty useless as you have no idea how the expression of each gene is distributed so you can't generate p-values.
Secondly, I believe you can download the probe annotations from the Affy website. You'll then need to use a pathway analysis tool (there are many - (free and not free), we use Ingenuity) but you'll need a list of deferentially expressed genes - which will be difficult to generate because of my first point.
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Old 04-13-2012, 10:32 AM   #3
himanshu04
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Dear Tony ,
Thanks a lot for your prompt reply. Actually , the experiment ran for a number of replicates . But this is just for my practice and so my professor gave me a 1,1 file for trial. The experiment had many replicates.
I used rma function from the affy library and got a list of genes that are up or down regulated as compared to the control. Can I now annotate the genes and use Pathway analysis tools like Ingenuity. What approach would you take in this kind of situation?.
Once again thanks a lot for the reply. I hope to hear back from you.
Thanks,
Himanshu Sharma.
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