Performance assessment of sample-specific network control methods for bulk and single-cell biological data analysis
Fig 3
Evaluation of SSC workflows for driver gene identification on nine TCGA bulk cancer gene expression datasets.
By using dissimilar combinations of sample-specific network and reference network, different sample-specific state transition networks can be obtained, e.g., (A) CSN_Net1, (B) CSN_Net2, (C) SSN_Net1, (D) SSN_Net2, (E) SPCC_Net1, (F) SPCC_Net2, (G) LIONESS_Net1, and (H) LIONESS_Net2. Then the performance of four network structural control methods based on these sample-specific state transition networks were evaluated, representing the performances of different SSC analysis workflows.