lit {lit} | R Documentation |
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.
lit(y, x, adjustment = NULL, pop_struct = NULL)
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 |
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.
# 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)