Table 1.

Simulation results for Models 1–4. (n, p, s) = (200, 1100, 44). Sensitivity, specificity, MCC, number of selected genes, number of false positives (FPs), and mean squared error (MSE) were averaged over 50 replicates. Lnet: Laplcian net; AdaLnet: adaptive Laplacian net; Lasso: ℓ₁-penalty; Enet: elastic net; GL: group ℓ_γ-penalty. Standard errors are given in the Supplementary Material.

Method	Sensitivity	Specificity	MCC	# of genes	# of FPs	MSE
Model 1
Lnet	0.346	0.997	0.524	18.84	3.60	0.016
AdaLnet	0.395	0.996	0.559	21.47	4.09	0.016
Lasso	0.435	0.950	0.310	72.25	53.13	0.012
Enet	0.407	0.995	0.561	22.77	4.88	0.016
GLγ	0.233	0.998	0.431	12.66	2.42	0.015
Model 2
Lnet	0.442	0.996	0.600	23.54	4.09	0.015
AdaLnet	0.557	0.996	0.682	28.79	4.23	0.015
Lasso	0.465	0.958	0.362	64.32	43.88	0.011
Enet	0.616	0.991	0.675	36.68	9.58	0.015
GLγ	0.434	0.996	0.594	22.99	3.91	0.014
Model 3
Lnet	0.526	0.987	0.591	37.06	13.91	0.070
AdaLnet	0.624	0.995	0.715	33.24	5.77	0.071
Lasso	0.363	0.975	0.346	42.67	26.71	0.067
Enet	0.684	0.986	0.682	44.90	14.79	0.072
GLγ	0.437	0.999	0.633	20.26	1.05	0.070
Model 4
Lnet	0.446	0.996	0.601	24.34	4.71	0.070
AdaLnet	0.633	0.995	0.728	32.62	4.76	0.070
Lasso	0.407	0.974	0.376	45.66	27.76	0.063
Enet	0.661	0.988	0.684	41.96	12.88	0.072
GLγ	0.541	0.999	0.703	25.22	1.40	0.070