How to best normalize your data depends on the particulars of your 
experiment (number of replicates, high/low counts) and what you are 
trying to achieve (differential expression). I don't believe there is a 
universally accepted best way and it is a topic of much discussion. If 
you are able to work with counts instead of coverage you could look at 
DESeq and edgeR, both of which offer normalization methods. The package 
vignettes explain the methods and assumptions in detail.

Here is a  recent discussion thread on this topic. There are others ..

https://stat.ethz.ch/pipermail/bioconductor/2011-May/039235.html


Valerie





On 11/09/2011 12:09 PM, rohan bareja wrote:
> Hi Valerie,
>
> Thats what I wanted to do but I dont know how to write a normalization function for Coverage..
> Would it be somewhat calculating RPKMs ??If yes how should I do that?
>
> Thanks,
> Rohan
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