Prediction of heterogeneous differential genes by detecting outliers to a Gaussian tight cluster

BMC Bioinformatics

Table 3 Distance effect

δ	COPA	OS	ORT	MOST	LSOSS	DOG	M
0.5	0.6687	0.0283	0.0410	0.3634	0.1086	0.0497	0
0.6	0.6687	0.0258	0.0387	0.3278	0.1076	0.0495	0.03
0.7	0.6687	0.0236	0.0366	0.2918	0.1353	0.0472	0.38
0.8	0.6687	0.0220	0.0351	0.3566	0.1213	0.0421	0.92
0.9	0.6687	0.0204	0.0335	0.3418	0.1421	0.0340	1.37
1.0	0.6687	0.0187	0.0315	0.3171	0.1409	0.0271	1.75
1.1	0.6687	0.0170	0.0295	0.3005	0.1655	0.0198	1.85
1.2	0.6687	0.0157	0.0280	0.2863	0.1691	0.0157	1.92
1.3	0.6687	0.0140	0.0260	0.2807	0.1668	0.0117	1.98
1.4	0.6687	0.0125	0.0243	0.2964	0.1656	0.0083	1.99
1.5	0.6687	0.0117	0.0233	0.2875	0.2004	0.0066	2
1.6	0.6687	0.0103	0.0216	0.2820	0.1828	0.0045	2
1.7	0.6687	0.0094	0.0202	0.2656	0.1988	0.0032	1.99
1.8	0.6687	0.0089	0.0196	0.2658	0.1936	0.0028	2
1.9	0.6687	0.0078	0.0178	0.2699	0.2380	0.0018	2
2.0	0.6687	0.0072	0.0169	0.2563	0.2465	0.0012	2

Average p-values for single-hDEG simulations with two outliers and a varying distance, δ, between non-outliers and outliers. M is the average number of outliers detected using DOG.

ISSN: 1471-2105