I was wondering if it's possible to account for multiple factors when analyzing samples in DiffBind. I want to block for potential batch effects as well as treatment conditions, but I'm unsure how to do so (or if it's even possible). The docs make it clear how to block for one factor, but don't make any mention of multiple. Hoping Rory will pop in here and clarify.

The relevant portions of my samplesheet (I'd like to block for Treatment and Tissue while using Condition for the actual contrast):

You can specify multiple factors for blocking:

> h3k27ac <- dba.contrast(h3k27ac, categories=DBA_CONDITION, 
                          block=c(DBA_TISSUE,DBA_TREATMENT))

While this may be useful to get a quick look, it probably doesn't do what you really want however. It will create a factor for each unique TISSUE-TREATMENT combination and fit a model for each. It would be more correct to fit a TISSUE model and a TREATMENT model. I'm looking at updating DiffBind to handle factor designs more appropriately, but in the meantime you may want to model this directly in DESeq2 or edgeR.

-Rory

The latest release of DiffBind now support unrestricted model designs and contrasts for both edgeR and DESeq2, as well as extensive options for controlling normalization. The updated vignette goes through these changes in detail.