[BioC] edgeR normalization factors

Naomi Altman naomi at stat.psu.edu
Tue Jun 29 04:21:13 CEST 2010


And yes, you should use the normalized data for 
DE and clustering.  Otherwise, highly expressing 
genes in your sample will depress the expression 
of other genes relative to the size of the 
library, inducing spurious "differential" 
expression.  I have been simulating data to try to understand this better.


At 11:19 PM 6/27/2010, 王孆 wrote:
>I have a question about using TMM normalization 
>factors. I want to modify the count for each 
>gene after normalization. Should I just need to 
>divide the count of each gene by the
>normalization factor for its library? Then, I 
>may use the normalized data for DE
>analysis and other further analysis (e.g. clustering).
>Thanks a lot,
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111

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