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CINOEDV (version 2.0)

ExhaustiveSearch: Exhaustive Search

Description

This function exhaustively compute main effects of all SNPs and interaction effects of all SNP-combinations within the maximum order.

Usage

ExhaustiveSearch(pts, class, MaxOrder = 3, measure = 1, alpha = 0)

Arguments

pts
matrix. SNP data. Each row represents a sample. Each column represents a SNP. For the element, 1 -> AA, 2 -> Aa, 3 -> aa.
class
matrix. Class labels of samples. It only has one row. Each column represents a class label. For the element, 1 -> case, 2-> control.
MaxOrder
numeric. The considered maximum order of epistatic interactions. It must be setted as 1, 2, 3, 4, or 5.
measure
numeric. The used evaluation measure. 1 -> the classic co-information measure; 2 -> the normalized co-information measure; 3 -> TingHu's co-informationn measure.
alpha
numeric. The lower threshold of effects, either main effects or interaction effects, which must be higher or equal to 0, By default, alpha <- 0.

Value

SingleEffect
matrix. main Effects of SNPs. There are 2 columns. The first column saves all SNPs, and the second column saves their corresponding effects. Ddescending save according to their effects.
TwoEffect
matrix. interaction Effects of two-SNP combinations. There are three columns. The first two columns save all two-SNP combinations, and the last column saves their corresponding effects. Descending save according to their interaction effects.
ThreeEffect
matrix. interaction Effects of three-SNP combinations. There are four columns. The first three columns save all three-SNP combinations, and the last column saves their corresponding effects. Descending save according to their interaction effects.
FourEffect
matrix. interaction Effects of four-SNP combinations. There are five columns. The first four columns save all four-SNP combinations, and the last column saves their corresponding effects. Descending save according to their interaction effects.
FiveEffect
matrix. interaction Effects of five-SNP combinations. There are six columns. The first five columns save all five-SNP combinations, and the last column saves their corresponding effects. Descending save according to their interaction effects.

References

None

Examples

Run this code
data(pts)
data(class)
Effect <- ExhaustiveSearch(pts, class, MaxOrder = 2, measure = 1, alpha = 0)
SingleEffect <- Effect$SingleEffect
TwoEffect <- Effect$TwoEffect
ThreeEffect <- Effect$ThreeEffect
FourEffect <- Effect$FourEffect
FiveEffect <- Effect$FiveEffect

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