lit {lit}

Latent Interaction Testing

Description

lit performs a kernel-based testing procedure, Latent Interaction Testing (LIT), using a set of traits and SNPs. LIT tests whether the squared residuals (SQ) and cross products (CP) are statistically independent of the genotypes. In particular, we construct a kernel matrix for the SQ/CP terms to measure the pairwise similarity between individuals, and also construct an analogous one for the genotypes. We then test whether these two matrices are independent. Currently, we implement the linear and projection kernel functions to measure pairwise similarity between individuals. We then combine the p-values of these implementations using a Cauchy combination test to maximize the number of discoveries.

Usage

lit(y, x, adjustment = NULL, pop_struct = NULL)

Arguments

y

matrix of traits (n observations by k traits)

x

matrix of SNPs (n observations by m SNPs)

adjustment

matrix of covariates to adjust traits

pop_struct

matrix of PCs that captures population structure

Value

A data frame of p-values where the columns are

• wlit: LIT using a linear kernel

• ulit: LIT using a projection kernel

• alit: Cauchy combination test of the above two LIT implementations.

See Also

lit_plink

Examples

# set seed
set.seed(123)

# Generate SNPs and traits
X <- matrix(rbinom(10*2, size = 2, prob = 0.25), ncol = 2)
Y <- matrix(rnorm(10*4), ncol = 4)

out <- lit(Y, X)