Polymorphism Interaction Analysis (PIA): a method for investigating complex gene-gene interactions

BMC Bioinformatics

Table 1 Definition of the seven scoring functions used in PIA v. 2.0.

Metric	Description	Formula^a
1	%Correct	(NTP + NTN)/(NTP + NFN + NFP + NTN)
2	Sensitivity + Specificity	[NTP/(NTP+NFN)] + [NTN/(NFP+NTN)]
3	Positive Predictive Value (PPV)+ Negative Predictive Value (NPV)	[NTP/(NTP+NFP)] + [NTN/(NFN+NTN)]
4	Risk Ratio	[(NTP)(NFP+NTN)]/[(NFP)(NTP+NFN)]
5	Odds Ratio	[(NTP)(NTN)]/[(NFP)(NFN)]
6	Gini Index^b	GINI_parent - GINI_split
		GINI(k) = 1.0 - ∑_{j = 1, J} [p(j\|k)]
		GINI_split = ∑_{k = 1, K} [(n_k/n) GINI(k)]
7	Absolute Probability Difference^c	Σ_{k = 1, K} \|P₁(k) - P₂(k)\|

^a NTP, Number of true positives; NTN, number of true negatives; NFN, number of false negatives; NFP, number of false positives.
^b Gini Index is used in CART decision trees [25]. The scoring for Gini index is described under "Algorithm."
^c Scoring is the probability of finding a case (P₁) in cell, k, minus the probability of observing a control (P₂) in cell, k, summed over all the K cells in the genotype-phenotype table.

ISSN: 1471-2105