Indiv_Score_Test_Region_cond: Conditional score test for individual variants in a given...

In xihaoli/STAAR: STAAR Procedure for Dynamic Incorporation of Multiple Functional Annotations in Whole-Genome Sequencing Studies

Conditional score test for individual variants in a given variant-set

Description

The Indiv_Score_Test_Region_cond function takes in genotype, the genotype of variants to be adjusted for in conditional analysis, and the object from fitting the null model to analyze the conditional associations between a quantitative/dichotomous phenotype and all individual variants in a given variant-set by using score test, adjusting for a given list of variants.

Usage

Indiv_Score_Test_Region_cond(
  genotype,
  genotype_adj,
  obj_nullmodel,
  rare_maf_cutoff = 0.01,
  rv_num_cutoff = 2,
  method_cond = c("optimal", "naive")
)

Arguments

genotype	an n*p genotype matrix (dosage matrix) of the target sequence, where n is the sample size and p is the number of genetic variants.
genotype_adj	an n*p_adj genotype matrix (dosage matrix) of the target sequence, where n is the sample size and p_adj is the number of genetic variants to be adjusted for in conditional analysis (or a vector of a single variant with length n if p_adj is 1).
obj_nullmodel	an object from fitting the null model, which is the output from either fit_null_glm function for unrelated samples or fit_null_glmmkin function for related samples. Note that fit_null_glmmkin is a wrapper of the glmmkin function from the GMMAT package.
rare_maf_cutoff	the cutoff of maximum minor allele frequency in defining rare variants (default = 0.01).
rv_num_cutoff	the cutoff of minimum number of variants of analyzing a given variant-set (default = 2).
method_cond	a character value indicating the method for conditional analysis. optimal refers to regressing residuals from the null model on genotype_adj as well as all covariates used in fitting the null model (fully adjusted) and taking the residuals; naive refers to regressing residuals from the null model on genotype_adj and taking the residuals (default = optimal).

Value

A data frame with p rows corresponding to the p genetic variants in the given variant-set and three columns: Score_cond (the conditional score test statistic adjusting for variants in genotype_adj), SE_cond (the standard error associated with the conditional score test statistic), and pvalue_cond (the conditional score test p-value). If a variant in the given variant-set has minor allele frequency = 0 or greater than rare_maf_cutoff, the corresponding row will be NA. If a variant in the given variant-set has standard error equal to 0, the p-value will be set as 1.

References

Chen, H., et al. (2016). Control for population structure and relatedness for binary traits in genetic association studies via logistic mixed models. The American Journal of Human Genetics, 98(4), 653-666. (pub)

Sofer, T., et al. (2019). A fully adjusted two-stage procedure for rank-normalization in genetic association studies. Genetic Epidemiology, 43(3), 263-275. (pub)

xihaoli/STAAR documentation built on Nov. 3, 2024, 9:34 p.m.