Learning genetic epistasis using Bayesian network scoring criteria

BMC Bioinformatics

Table 4 Accuracies of scoring criteria on most difficult models

	Scoring Criterion	200	400	800	1600	Total
1	score _{α = 54}	14	48	167	352	581
2	score _{α = 162}	1	21	146	355	563
3	score _{α = 36}	13	46	155	318	532
4	score _{α = 21}	12	43	106	289	450
5	score _{α = 18}	11	37	91	274	413
6	score _MDR	3	25	79	245	352
7	score _{α = 12}	7	25	65	215	312
8	score _AIC ₂	16	33	80	138	267
9	score _{α = 9}	5	20	48	186	259
10	Score _Epi ₁	4	16	47	179	246
11	score _MML ₁	2	7	23	140	172
12	score _{α = 3}	3	6	13	86	108
13	score _Epi ₂	0	1	4	72	77
14	score _Suz ₁	0	1	2	41	44

The number of times out of 500 that each scoring criterion correctly learned the correct model in the case of the most difficult models (55-59) for sample sizes of 200, 400, 800, and 1600. The last column gives the total accuracy over all sample sizes. The scoring criteria are listed in descending order of accuracy.

ISSN: 1471-2105