. Author manuscript; available in PMC: 2019 May 1.

Published in final edited form as: IEEE/ACM Trans Comput Biol Bioinform. 2017 Feb 7;15(3):760–773. doi: 10.1109/TCBB.2017.2665495

TABLE I.

The sensitivities, specificities and F1-scores for cPLS (with false discovery rate set to 0.10) and its comparative methods, glasso and WGCNA.

Simulation model	n	p	Sensitivity			Specificity			F1-score
Simulation model	n	p	cPLS	glasso	WGCNA	cPLS	glasso	WGCNA	cPLS	glasso	WGCNA
Overdispersed Poisson	20	100	0.722	0.000	0.978	0.998	1.000	0.717	0.838	0.000	0.827
	20	1000	0.690	0.000	0.971	1.000	1.000	0.687	0.817	0.000	0.805
	100	100	0.588	0.000	1.000	1.000	1.000	0.773	0.741	0.000	0.872
	100	1000	0.687	0.000	0.998	1.000	1.000	0.927	0.814	0.000	0.961
Multinomial	20	100	0.142	0.000	1.000	1.000	1.000	0.773	0.249	0.000	0.872
	20	1000	0.092	0.000	1.000	1.000	1.000	0.774	0.168	0.000	0.873
	100	100	0.979	0.000	1.000	1.000	1.000	0.995	0.989	0.000	0.997
	100	1000	0.929	0.000	1.000	1.000	1.000	0.995	0.963	0.000	0.997
SimSeq	20	100	0.785	0.000	0.926	0.997	1.000	0.624	0.878	0.000	0.747
	20	1000	0.900	0.000	0.954	0.992	1.000	0.544	0.944	0.000	0.693
	100	100	0.826	0.000	0.921	0.996	1.000	0.783	0.903	0.000	0.846
	100	1000	0.982	0.000	0.956	0.995	1.000	0.652	0.988	0.000	0.775