2.7. Transcription Factor Analysis

To identify activated transcription factors (TF) within one cell cluster, we applied R package SCENIC (version 1.2.4) and python package pySCENIC (version 0.11.2) for TF analyses. Firstly, using the GRNBoost2 function in pySCENIC, we established a co-expression network to find potential targets for TFs. RcisTarget was used for enrichment analyses of TF motifs (reference: 500bp-upstream-7species.mc9nr, from cisTarget database, https://resources.aertslab.org/cistarget/, accessed on 1 April 2022), and AUCell was used to quantify regulons. A binary matrix could be created with the cutoff obtained by AUC scoring for each regulon. In TF analyses, the significant TF was defined as more than 20% of cells activated with it within each cell cluster (except for those in stromal cells, for which 50% was set as the cutoff).