The KCRI network was downloaded as a Cytoscape file from (16 August 2019) (6), and the edges were exported as a tsv file for processing by a custom python script. To select a subset of regulatory genes from the KCRI network, we checked which genes were annotated as targeting the 100 most differentially expressed genes in our dataset. We began with a core set that included all genes annotated as regulating at least 1 of the top 100 genes and which were themselves differentially expressed by at least 45% (Irf5, Trerf1, Lef1, Myb, Aff3, Nr4a3, Egr3, Ar, Plxnc1, Gata3, Plxnd1, Nfkb2, Batf3, Sema4a, Lgr4, Maf, Inhba, Nfil3, Tiparp, Ahr, Fosl2, and Ssh2). Visualizing the network of interactions among these genes revealed two modules, which were extended to other genes showing interactions coherent with these modules and selected downstream genes. Ranking genes by annotated targets*differential expression, the two modules include all the top 10 genes and 23 of the top 30.

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