LKMO_Null_Model: Optimal KM for Quantitative Traits in Longitudinal GWAS Data...

In KMgene: Gene-Based Association Analysis for Complex Traits

Description

This function (LKMO) is used to perform optimal KM analysis (Yan et al., 2016) for quantitative traits in GWAS longitudinal data.
# It considers random intercept and random time

Usage

LKMO_Null_Model(phenotype, time, yid, covariates = NULL)

Arguments

phenotype	A vector of quantitative trait in the analysis (class: vector). The order should match the vector yid. No missing.
time	A vector of time points (class: vector). The order should match the vector yid. No missing.
yid	A vector of id (class: vector). Although it doesn't have to be sorted, observations from the same subject have to be connected with each other. The repeated id numbers indicate multiple time points for one subject. Make sure it is not a factor. No missing.
covariates	A matrix of covariates (class: data.frame). The order of rows should match the vector yid. Default NULL. No missing.

Value

output: object as input for LKMO

KMgene documentation built on July 8, 2020, 6:09 p.m.