Hi! Have a question about using DiffBind for ChIP-seq data with drosophila spike-ins.

I already have computed peaks from usage of control data and spike-in normalisation coefficients for a cohort of target samples across two conditions. The spike-in coefficients computation is based on drosophila alignment results as described in ActiveMotif documentation for down-sampling (adjustment based on minimum).

Is there an easy way to use these computed coefficients for the DiffBind analysis? I found this post, but there is a link to pipeline which starts from reads, while I would like only to correct the computed scores matrix before differential analysis. The matrix is computed from original samples without subsampling, but with the usage of control.

Thanks a lot for the reply! My further question: how to create the object with adjusted coefficients for further processing? Is there a specific way to set the reference? Here's my code example:

Would be grateful for comments

You can read in pre-set counts for a consensus peak set using

`dba()`

or`dba.peakset()`

. The documentation is in the help page for`dba.peakset()`

(see`counts`

parameter), but I usually do this using`dba()`

and a samplesheet with a column labelled`Counts`

.