Thanks Rory and Heidi for replying.
Would read subtraction is enough in order to account for the difference in
gene expression?
Mali

On Wed, Jan 4, 2012 at 2:11 PM, Rory Stark <Rory.Stark@cancer.org.uk> wrote:

> Hi Mali-
>
> You can try this pretty easily using DiffBind. I suggest calling peaks on
> each IP separately (each IP and its matching RNA-Seq control) and read
> these four peaksets into DiffBind (you could also use two peak callers and
> read in all eight peaksets to identify more potential sites). DiffBind lets
> you derive an overall set of peaks (either a superset of all the peaks, or
> any that overlap in at least two [or more] peaksets), does the read
> counting (by default subtracting reads in the matching RNA-seq controls),
> runs edgeR and/or DESeq to identify differentially bound regions, and
> offers several plots and reports to characterize the results.
>
> A couple of caveats: With only two replicates of each condition, your
> power to reliably identify significant differences is limited. Also, while
> the IP reads will be normalized, the control reads will not be (unless you
> do some normalization separately prior to loading it into DiffBind).
> However this does seem to be a a good place to start!
>
> Cheers-
> Rory
>
>
> ----------------------------------------------------------------------------
> Dr. Rory Stark
>
> Principal Bioinformatics  Analyst
>
> Cambridge Research Institute - Cancer Research UK
> Robinson Way
> Cambridge CB2 0RE
> United Kingdom
>  +44 1223 404 311
>
> rory.stark@cancer.org.uk
>
> ----------------------------------------------------------------------------
>
> On 04/01/2012 13:37, "mali salmon" <shalmom1@gmail.com<mailto:
> shalmom1@gmail.com>> wrote:
>
> Dear Users
> We have RNA-IP-seq for two conditions with two biological replicates each.
> So in total we have 8 samples:
> 2 for condition1 IP
> 2 for condition1 Input
> 2 for condition2 IP
> 2 for condition2 Input
> We would like to find differential binding between the two conditions which
> are not influenced from differences in gene expression (Input samples are
> actually regular RNA-seq).
> I thought of first finding peak regions (maybe by pooling all IP and all
> Input samples) and run ChIP-seq peak caller, count how many reads fall
> within these regions in each of the samples, and then run DESeq and edgeR
> in order to find differential binding.
> Is this can be done with edgeR and DESeq (again the Input is different for
> the two conditions, and we would like to cancel out differential gene
> expression)?
> Thanks
> Mali
>
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