Predicting the effect of missense mutations on protein function: analysis with Bayesian networks

Needham, Chris J; Bradford, James R; Bulpitt, Andrew J; Care, Matthew A; Westhead, David R

doi:10.1186/1471-2105-7-405

BMC Bioinformatics

Table 2 Results with a naïve Bayes classifier.

From: Predicting the effect of missense mutations on protein function: analysis with Bayesian networks

Cross-validation	Trained on:	All	All	NoS	All	NoE	All	key
	Tested on:	All	NoS	NoS	NoE	NoE	key	key
mixed	AUC	0.83 ± 0.01	0.70 ± 0.02	0.70 ± 0.02	0.81 ± 0.02	0.81 ± 0.02	0.80 ± 0.02	0.79 ± 0.01
	MCC	0.44 ± 0.04	0.27 ± 0.03	0.27 ± 0.03	0.43 ± 0.03	0.43 ± 0.03	0.41 ± 0.02	0.35 ± 0.06
	Overall error rate	0.19 ± 0.01	0.24 ± 0.01	0.24 ± 0.01	0.18 ± 0.01	0.18 ± 0.01	0.18 ± 0.01	0.21 ± 0.00
	Effect error rate	0.35 ± 0.05	0.52 ± 0.03	0.52 ± 0.03	0.26 ± 0.07	0.26 ± 0.07	0.24 ± 0.07	0.41 ± 0.04
	No effect error rate	0.15 ± 0.02	0.18 ± 0.01	0.18 ± 0.01	0.17 ± 0.01	0.17 ± 0.01	0.17 ± 0.02	0.17 ± 0.03
	sensitivity	0.47 ± 0.12	0.37 ± 0.06	0.37 ± 0.06	0.37 ± 0.06	0.37 ± 0.06	0.36 ± 0.09	0.38 ± 0.16
	specificity	0.92 ± 0.03	0.88 ± 0.02	0.88 ± 0.02	0.96 ± 0.02	0.96 ± 0.02	0.96 ± 0.03	0.92 ± 0.05
lac rep	AUC	0.84 ± 0.02	0.74 ± 0.02	0.74 ± 0.02	0.82 ± 0.02	0.82 ± 0.02	0.80 ± 0.02	0.80 ± 0.02
	MCC	0.47 ± 0.03	0.33 ± 0.06	0.33 ± 0.06	0.46 ± 0.04	0.46 ± 0.04	0.44 ± 0.03	0.39 ± 0.05
	Overall error rate	0.18 ± 0.01	0.23 ± 0.01	0.23 ± 0.01	0.18 ± 0.01	0.18 ± 0.01	0.19 ± 0.01	0.21 ± 0.00
	Effect error rate	0.27 ± 0.05	0.40 ± 0.04	0.40 ± 0.04	0.20 ± 0.06	0.20 ± 0.06	0.18 ± 0.09	0.36 ± 0.05
	No effect error rate	0.16 ± 0.02	0.19 ± 0.02	0.19 ± 0.02	0.18 ± 0.02	0.18 ± 0.02	0.19 ± 0.03	0.18 ± 0.03
	sensitivity	0.47 ± 0.10	0.36 ± 0.12	0.36 ± 0.12	0.37 ± 0.08	0.38 ± 0.08	0.34 ± 0.12	0.41 ± 0.13
	specificity	0.93 ± 0.03	0.92 ± 0.04	0.92 ± 0.04	0.96 ± 0.02	0.96 ± 0.02	0.97 ± 0.04	0.92 ± 0.04
lysozyme	AUC	0.83 ± 0.02	0.68 ± 0.04	0.68 ± 0.05	0.81 ± 0.04	0.81 ± 0.04	0.78 ± 0.04	0.77 ± 0.04
	MCC	0.40 ± 0.05	0.23 ± 0.06	0.23 ± 0.06	0.38 ± 0.08	0.38 ± 0.08	0.36 ± 0.11	0.28 ± 0.09
	Overall error rate	0.17 ± 0.02	0.24 ± 0.01	0.24 ± 0.02	0.17 ± 0.03	0.17 ± 0.03	0.16 ± 0.02	0.21 ± 0.03
	Effect error rate	0.40 ± 0.05	0.63 ± 0.05	0.63 ± 0.05	0.39 ± 0.12	0.39 ± 0.12	0.33 ± 0.13	0.54 ± 0.09
	No effect error rate	0.13 ± 0.02	0.15 ± 0.01	0.15 ± 0.01	0.13 ± 0.03	0.13 ± 0.03	0.15 ± 0.02	0.14 ± 0.02
	Sensitivity	0.43 ± 0.11	0.39 ± 0.07	0.39 ± 0.07	0.38 ± 0.17	0.38 ± 0.17	0.28 ± 0.09	0.36 ± 0.11
	Specificity	0.93 ± 0.03	0.84 ± 0.02	0.84 ± 0.02	0.93 ± 0.07	0.93 ± 0.07	0.97 ± 0.01	0.89 ± 0.04
Train: lac rep	AUC	0.80	0.66	0.67	0.78	0.78	0.77	0.77
	MCC	0.40	0.23	0.23	0.35	0.35	0.35	0.35
	Overall error rate	0.20	0.27	0.24	0.17	0.17	0.16	0.16
Test: lysozyme	Effect error rate	0.52	0.65	0.63	0.41	0.41	0.32	0.32
	No effect error rate	0.10	0.14	0.15	0.14	0.14	0.15	0.16
	Sensitivity	0.58	0.46	0.39	0.33	0.33	0.26	0.26
	Specificity	0.85	0.80	0.84	0.95	0.95	0.97	0.97
Train: lysozyme	AUC	0.81	0.71	0.71	0.80	0.80	0.79	0.79
	MCC	0.43	0.37	0.37	0.41	0.41	0.42	0.42
	Overall error rate	0.20	0.22	0.22	0.20	0.20	0.19	0.19
Test: lac rep	Effect error rate	0.34	0.43	0.43	0.25	0.25	0.18	0.18
	No effect error rate	0.17	0.17	0.17	0.19	0.19	0.20	0.20
	Sensitivity	0.45	0.46	0.46	0.33	0.33	0.30	0.30
	Specificity	0.92	0.88	0.88	0.96	0.96	0.98	0.98

Column: (1) trained on all variables, tested with all variables observed; (2) trained on all variables, tested without any structural information (NoS) – only evolutionary variables observed; (3) trained and tested using only five evolutionary nodes; (4) trained on all variables, tested without any evolutionary information (NoE) – only structural variables observed; (5) trained and tested using only eight structural nodes; (6) trained on all variables, tested with only key variables observed (see later section); (7) trained and tested using only the three key variables.

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ISSN: 1471-2105

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