div_gwas: Wrapper for bigsnpr for GWAS

In Alice-MacQueen/snpdiver: Explore SNP Effects on Multiple Phenotypes in Diversity Panels

Description

Given a dataframe of phenotypes associated with sample.IDs, this function is a wrapper around bigsnpr functions to conduct linear or logistic regression on wheat. The main advantages of this function over just using the bigsnpr functions is that it automatically removes individual genotypes with missing phenotypic data and that it can run GWAS on multiple phenotypes sequentially.

Usage

div_gwas(df, snp, type, svd, npcs, ncores)

Arguments

df	Dataframe of phenotypes where the first column is sample.ID
snp	Genomic information to include for wheat.
type	Character string. Type of univarate regression to run for GWAS. Options are "linear" or "logistic".
svd	Optional covariance matrix to include in the regression. You can generate these using bigsnpr::snp_autoSVD().
npcs	Integer. Number of PCs to use for population structure correction.
ncores	Integer. Number of cores to use for parallelization.

Value

The gwas results for the last phenotype in the dataframe. That phenotype, as well as the remaining phenotypes, are saved as RDS objects in the working directory.

Alice-MacQueen/snpdiver documentation built on Dec. 17, 2021, 8:41 a.m.