BMC Bioinformatics

Table 1 Results from simulation studies using data generated from the proposed methodology. The value of F for HBFM represents the number of factors in the “best” model choice, as determined by DIC

From: A sparse Bayesian factor model for the construction of gene co-expression networks from single-cell RNA sequencing count data

	Sim 1: N=125,F_sim=10					Sim 2: N=125,F_sim=15
	TPR	FDR	AUC	Edges		TPR	FDR	AUC	Edges
HBFM, F = 15	0.760	0.153	0.927	314	HBFM, F = 15	0.640	0.111	0.820	306
LEAP	0.386	0.378	0.705	217	LEAP	0.341	0.275	0.665	200
PIDC	0.634	0.293	0.821	314^*	PIDC	0.506	0.297	0.742	306^*
SCODE	0.229	0.745	0.550	314^*	SCODE	0.249	0.654	0.504	306^*
BN	0.206	0.077	0.682	78	BN	0.186	0.037	0.672	82
GENIE3	0.540	0.398	0.746	314^*	GENIE3	0.468	0.350	0.711	306^*
PCORR	0.123	0.566	0.599	99	PCORR	0.148	0.442	0.602	113
	Sim 3: N=500,F_sim=10					Sim 4: N=500,F_sim=15
	TPR	FDR	AUC	Edges		TPR	FDR	AUC	Edges
HBFM, F = 25	0.889	0.034	0.984	322	HBFM, F = 25	0.704	0.029	0.929	308
LEAP	0.743	0.608	0.741	664	LEAP	0.402	0.305	0.696	246
PIDC	0.794	0.137	0.915	322^*	PIDC	0.621	0.143	0.866	308^*
SCODE	0.249	0.730	0.501	322^*	SCODE	0.216	0.701	0.578	308^*
BN	0.277	0.040	0.751	101	BN	0.212	0.032	0.716	93
GENIE3	0.554	0.398	0.754	322^*	GENIE3	0.466	0.357	0.729	308^*
PCORR	0.300	0.266	0.683	143	PCORR	0.261	0.327	0.624	165
	Sim 5: N=1000,F_sim=10					Sim 6: N=1000,F_sim=15
	TPR	FDR	AUC	Edges		TPR	FDR	AUC	Edges
HBFM, F = 20	0.909	0.076	0.973	344	HBFM, F = 25	0.624	0.070	0.904	285
LEAP	0.780	0.550	0.804	606	LEAP	0.591	0.541	0.680	547
PIDC	0.857	0.128	0.954	344^*	PIDC	0.633	0.056	0.889	285^*
SCODE	0.269	0.727	0.496	344^*	SCODE	0.221	0.670	0.510	285^*
BN	0.323	0.050	0.793	119	BN	0.247	0.037	0.710	109
GENIE3	0.603	0.387	0.764	344^*	GENIE3	0.440	0.344	0.700	285^*
PCORR	0.403	0.291	0.720	199	PCORR	0.294	0.251	0.669	167

^*Number of edges fixed to match HBFM

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ISSN: 1471-2105

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