SPA.I.GE: Rare variants association test score to evaulate the effect...

In SPAr: Perform rare variants association analysis based on summation of partition approaches

Description

Compute the nonparametric association information score between a set of rare variants and dichotomous outcomes, incorporating interactions with environmental factors.

Usage

SPA.I.GE(x, y, E, nperm = 100)

Arguments

x	a matrix of numeric genotypes with each row as an individual and each column as a separate rare SNP. Each genotype should be coded as 0,1 and 2.
y	a vector of phenotypes. The length of y should be the same as the number of rows of x.
E	a vector of environmental factors. It must be a categorical variable.
nperm	the number of permutations used to obtain the significance level. See details.

Details

This function evaluates the gene-environmental intearction effects associated with the dichotomous trait. The phenotype y must be dichotomous. The significance is computed using both global permutation and local permutation.

Value

I2star	The numerical value of the information score.
pvalue.global	The p-value from global permutation.
pvalue.local	The p-value from local permutation.
call	The matched call.
type	Type of the method used. It is "env".

Author(s)

Ruixue Fan [e-mail]

References

Fan, R., Lo, S-H (2013). A robust model-free approach for rare variantss association studies incorporating gene-gene and gene-environmental interactions. PLOS ONE 8(12):e83057.

Examples

	data(SPA_example)
	attach(SPA_example)
	SPA.I.GE <- SPA.I.GE(x,y.d,E,nperm=10)
	print(SPA.I.GE)

SPAr documentation built on May 2, 2019, 7:18 a.m.