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aertslab / pySCENIC

pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.
http://scenic.aertslab.org
GNU General Public License v3.0
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[results] Using df2regulon vs auxillary function derive_regulon #179

Closed Annika18 closed 4 years ago

Annika18 commented 4 years ago

Hi, I have followed the tutorial for pySCENIC and am now implementing the scenic protocol for my data set.

I noticed that the Protocol uses the auxillary function derive_regulon to get a list of regulons, while the tutorial (and other examples I've looked at) just seem to use the df2regulon built in function. What is the difference and potential benefit of one over the other? How much would it change the actual resulting list of regulons? (And relatedly, would this have a significant impact on the results of AUCell?)

Thanks so much for any help.

cflerin commented 4 years ago

Hi @Annika18 ,

The df2regulon function creates regulons from enriched features. The majority of the work is done prior to this in the main prune2df function.

The derive_regulons function in the cancer tutorial has some settings that are specific to that dataset (you can see some of this from the comments in that function).

For a typical analysis, I would start with the standard pySCENIC steps, which use the prune2df and df2regulon. Then, if you want to apply more filters to the regulons found there, you can do so.