To benchmark this state-of-the-art method, we first applied scTIGER to scRNA-seq datasets from patient samples with prostate cancer and specifically focused on identifying the dynamic regulatory networks of AR, ERG, PTEN, and ATF3 for the same-cell type between prostatic cancerous and normal conditions, and two-cell types within the cancerous prostatic environment. The gene discussed is ATF3; the disease is prostate cancer.