cdbn_gwas: Wrapper for bigsnpr for GWAS on Phaseolus vulgaris (the...

In Alice-MacQueen/CDBNgenomics: Genomics Using the Cooperative Dry Bean Nursery Dataset

Description

Given a dataframe of phenotypes associated with Taxa, this function is a wrapper around bigsnpr functions to conduct linear or logistic regression on Phaseolus vulgaris. 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

cdbn_gwas(
  df,
  type = c("linear", "logistic"),
  snp,
  covar = NA,
  ncores = 1,
  npcs = 10,
  saveoutput = FALSE
)

Arguments

df	Dataframe of phenotypes where the first column is Taxa.
type	Character string. Type of univarate regression to run for GWAS. Options are "linear" or "logistic".
snp	Genomic information to include for Phaseolus vulgaris.
covar	Optional covariance matrix to include in the regression. You can generate these using bigsnpr::snp_autoSVD().
ncores	Number of cores to use. Default is one.
npcs	Number of principle components to use. Default is 10.
saveoutput	Logical. Should output be saved as a rds to the working directory?

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/CDBNgenomics documentation built on Aug. 18, 2020, 4:39 p.m.