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Old 09-09-2017, 08:14 AM   #1
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Default Bayesian network analysis to infer gene regulatory relationships

I am currently using RNA-seq to examine the roles of a few key proteins in the transcriptional response underlying a certain condition. I came across this interesting article ( where Bayesian Network Analysis (using the R package "deal") was used to analyze RNA-seq data to infer which genes are acting "upstream" or "downstream" of their gene of interest. This seems really useful as it would provide me with some potential candidate genes as upstream regulators of a poorly-understood gene in the condition that I am studying, which I can test using knockdowns and etc.

I'm a bit suspicious because the Bayesian Network Analysis method this paper used seems to be too simple/not well-described. Also, I have not been able to find other recent papers using the same method/approach. I am wondering if this is a methodologically sound way of identifying potentially causal regulatory relationships between genes that then can be tested using wet lab experiments?

P.S. I tried to look on Biostars for similar threads, but those don't seem to get any answers.

Thank you very much for any light you can shed on this!
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bayesian inference, gene regulatory network, rna-seq, transcription factor

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