[BioC] filter high-throughput microarray data with noise

[J.delasHeras at ed.ac.uk]

Quoting Weiwei Shi <helprhelp at gmail.com>:

> Dear Listers:
>
> Currently I am doing a research using a microarray data. I have two
> questions and hope I can get some help from here:
>
> 1. I have a dataset like the following, in which V1 is geneid,
> v3...are the fold changes of expression levels for different patients.
> There are multiple probes for one gene, so there are multiple rows.
> You can see from column V11 and V13, the fold changes are very
> different. Is it very common in microarray data analysis? Generally
> how to deal with that? I don't want to use a p-value or something like
> threshold to discretize them in this step yet.
>
>            V1        V3             V5              V7        V9
>      V11        V13
> -2147022884  3.967828  5.010724  3.356568  1.227882   1.481481   1.870871
> -2147022884 -4.031250 -1.441341 -1.036145 -3.583333  -8.953125  -3.201117
> -2147022884 -2.016835 -1.568063 -1.079279 -1.288172 -50.875421 -39.554974
>
> here is the variance
>> x2.var[2,]
>       Group.1       V3       V5       V7       V9      V11      V13
> -2147022884 17.30989 14.15427 6.495755 5.791014 767.9342 510.5714
>
> 2. Is there any good reference on this kind of things? like online
> materials or book.
>
> thanks,
> --
> Weiwei Shi, Ph.D
> Research Scientist
> GeneGO, Inc.
>
> "Did you always know?"
> "No, I did not. But I believed..."
> ---Matrix III


You can have big variability for low intensity spots. If you have a 
gene that becomes either silenced or activated, you can get big fold 
change differences.

I am sure there are other possibilities, but I think you should 
consider these too.

Jose


-- 
Dr. Jose I. de las Heras                      Email: J.delasHeras at ed.ac.uk
The Wellcome Trust Centre for Cell Biology    Phone: +44 (0)131 6513374
Institute for Cell & Molecular Biology        Fax:   +44 (0)131 6507360
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