Table 1.

Calmodulin Prediction Comparison to Phenotype Prediction Software

	MDPPM	PON-P		CONDEL				predictSNP
Variant	Phenotype Prediction	PON-P	SIFT	PPH2	MA	FATHMM	CONDEL	predictSNP	PhD-SNP	PolyPhen-1	PolyPhen-2	SIFT	SNAP
A21G	AD1b	0.845a	0.420d	0.978b	0.805b	−4.910d	0.561b	75%d	83%d	67%d	61%d	76%d	56%b
A42T	AD1b	0.949b	0.000b	1.000b	1.040b	−4.910d	0.570b	60%d	51%d	67%d	68%d	53%b	81%b
D7N	AD1b	0.950b	1.000d	0.336c	0.345d	−4.090d	0.519d	72%b	55%d	59%b	63%b	79%b	85%b
E22G	AD1b	0.937b	0.010b	0.912b	0.975b	−4.930d	0.568b	51%b	61%b	67%d	41%b	53%d	72%b
D23N	CAAb	0.791a	0.230d	0.984b	0.975b	−5.110d	0.573b	87%b	59%b	74%b	60%b	53%b	81%b
E22K	CAAb	0.895b	0.010b	0.460c	0.625d	−4.910d	0.552b	87%b	61%b	59%b	60%b	45%b	89%b
E22Q	CAAb	0.956b	0.010b	0.936b	0.975b	−4.920d	0.568b	61%b	51%d	67%d	81%b	79%b	89%b
L34V	CAAb	0.885b	0.000b	0.999b	1.040b	−4.990d	0.572b	76%b	51%d	74%b	68%b	79%b	62%b
E3D	WTd	0.861b	0.150d	0.015d	0.975b	−4.870d	0.566b	71%d	72%d	67%d	68%d	79%b	58%d
E22D	WTd	0.938b	0.150d	0.015d	0.975b	−4.870d	0.566b	75%d	66%d	67%d	63%d	67%d	56%b
Pearson	−0.726	0.395	0.268	−0.258	−0.267	0.448	−0.362	0.007	−0.380	−0.123	0.673	0.823	0.067
Accuracy	100.0%	60.0%	70.0%	80.0%	60.0%	0.0%	70.0%	60.0%	30.0%	40.0%	60.0%	60.0%	80.0%

^aUnknown.

^bDeleterious/pathological.

^cPossible damage.

^dNeutral/nonpathological.