Blocking factors for differential binding analysis with DiffBind
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@mthabisi-moyo-9721
Last seen 10 weeks ago
United States

I have performed ChIP-seq for multiple transcription factors on samples from multiple patients. All ChIPs for each patient where sequenced on different sequencing runs (i.e. TF1, TF2, TF3 for patient 1 was on one flowcell and  TF1, TF2, TF3 for patient 2 was on a separate flowcell etc). I am looking at how each transcription factor's binding affinity is changing in disease vs. normal. As such, I will be using DBA_REPLICATE as a blocking factor when I look at differential TF binding sites to account for the batch effects of each replicate being on a different flowcell. 

When dealing with a matched design for tissue samples (i.e. normal vs disease, with normal and disease being defined in the Tissue metadata column of the sample sheet), is there a need to set up a blocking factor if the category being used for dba.contrast() is the tissue type i.e normal vs disease?

Is it okay to use:

dba.contrast(x, categories = DBA_TISSUE, block = DBA_REPLICATE)

Or do you also need to include DBA_TISSUE as a blocking factor?

dba.contrast(x, categories = DBA_TISSUE, block = c(DBA_REPLICATE,DBA_TISSUE))

Thanks!

diffbind • 781 views
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Rory Stark ★ 5.2k
@rory-stark-5741
Last seen 4 weeks ago
Cambridge, UK

If you have normal and disease for each patient, and all the patient ChIPs (both normal and disease) were done in the same run, then the second one is correct.

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