. 2020 Aug 18;21:361. doi: 10.1186/s12859-020-03707-y

Table 2.

Results from simulation studies using data generated from the NORTA algorithm. The value of F for HBFM represents the number of factors in the “best” model choice, as determined by DIC

	Sim 7: N=125, Edges_Sim=350					Sim 8: N=125, Edges_Sim=425
	TPR	FDR	AUC	Edges		TPR	FDR	AUC	Edges
HBFM, F = 18	0.817	0.043	0.927	299	HBFM, F = 18	0.638	0.000	0.942	271
LEAP	0.700	0.377	0.819	393	LEAP	0.466	0.423	0.630	343
PIDC	0.714	0.164	0.875	299^*	PIDC	0.560	0.122	0.817	271^*
SCODE	0.243	0.716	0.491	299^*	SCODE	0.169	0.734	0.540	271^*
BN	0.211	0.026	0.718	76	BN	0.148	0.000	0.689	63
GENIE3	0.349	0.592	0.576	299^*	GENIE3	0.306	0.520	0.558	271^*
PCORR	0.157	0.396	0.559	91	PCORR	0.132	0.434	0.564	99
	Sim 9: N=500, Edges_Sim=350					Sim 10: N=500, Edges_Sim=425
	TPR	FDR	AUC	Edges		TPR	FDR	AUC	Edges
HBFM, F = 22	0.871	0.041	0.993	318	HBFM, F = 20	0.727	0.019	0.947	315
LEAP	0.880	0.548	0.909	681	LEAP	0.744	0.557	0.741	713
PIDC	0.857	0.057	0.941	318^*	PIDC	0.722	0.025	0.933	315^*
SCODE	0.249	0.726	0.571	318^*	SCODE	0.240	0.676	0.520	315^*
BN	0.251	0.064	0.764	94	BN	0.195	0.057	0.669	88
GENIE3	0.366	0.597	0.601	318^*	GENIE3	0.355	0.521	0.569	315^*
PCORR	0.220	0.280	0.609	107	PCORR	0.198	0.408	0.571	142
	Sim 11: N=1000, Edges_Sim=350					Sim 12: N=1000, Edges_Sim=425
	TPR	FDR	AUC	Edges		TPR	FDR	AUC	Edges
HBFM, F = 25	0.966	0.048	0.989	355	HBFM, F = 25	0.831	0.033	0.968	365
LEAP	0.926	0.623	0.870	859	LEAP	0.849	0.529	0.809	767
PIDC	0.957	0.056	0.977	355^*	PIDC	0.807	0.060	0.940	365^*
SCODE	0.303	0.701	0.506	355^*	SCODE	0.191	0.778	0.625	365^*
BN	0.343	0.084	0.756	131	BN	0.233	0.075	0.734	107
GENIE3	0.414	0.592	0.596	355^*	GENIE3	0.374	0.564	0.565	365^*
PCORR	0.297	0.373	0.654	166	PCORR	0.228	0.276	0.612	134

^*Number of edges fixed to match HBFM