lit (version 1.0.0)

lit_plink: Latent Interaction Testing

Description

lit_plink 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. This function is suitable for large datasets (e.g., UK Biobank) in plink format. Note that our code to process plink files builds from the genio R package

Usage

lit_plink(y, file, adjustment = NULL, pop_struct = NULL, verbose = TRUE)

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.

Arguments

y

matrix of traits (n observations by k traits)

file

path to plink files

adjustment

matrix of covariates to adjust traits

pop_struct

matrix of PCs that captures population structure

verbose

If TRUE (default) print progress.

See Also

lit

Examples

# set seed
set.seed(123)

# path to plink files
file <- system.file("extdata", 'sample.bed', package = "genio", mustWork = TRUE)

# Generate trait expression
Y <- matrix(rnorm(10*4), ncol = 4)

out <- lit_plink(Y, file = file)