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.
In order to explore the regulons identified in my data with pySCENIC, I used the list of target genes for select regulons and analyzed them using iRegulon. However, after running the "Predict regulators and target" with those genes for the TF of interest, I do not get back the original TF as one of the enriched tfs. To illustrate:
tf = 'E2F7'
tf_mods = [ x for x in modules if x.transcription_factor==tf ]
for i,mod in enumerate( tf_mods ):
print( f'{tf} module {str(i)}: {len(mod.genes)} genes' )
print( f'{tf} regulon: {len(regulons[tf+"_(+)"])} genes' )
strawberry789
commented
3 years ago
Hello,
In order to explore the regulons identified in my data with pySCENIC, I used the list of target genes for select regulons and analyzed them using iRegulon. However, after running the "Predict regulators and target" with those genes for the TF of interest, I do not get back the original TF as one of the enriched tfs. To illustrate:
1- From https://github.com/aertslab/SCENICprotocol/blob/master/notebooks/PBMC10k_downstream-analysis.ipynb :
E2f7 module 0: 511 genes E2f7 module 1: 255 genes E2f7 module 2: 51 genes E2f7 module 3: 53 genes E2f7 module 4: 115 genes E2f7 module 5: 509 genes E2f7 regulon: 386 genes
2- I write it to a text file E2f7_regulon.txt and use this for iRegulon in Cytoscape - "Predict regulators and target" Analysis
3- iRegulon results
Why does E2F7 not show up as one of the enriched TFs?
This also happened with other regulons that I exported the same way. Please Advise.