div_lambda_GC: Return lambda_GC for different numbers of PCs for GWAS on...

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

Description

Given a dataframe of phenotypes associated with sample.IDs and output from a PCA to control for population structure, this function will return a .csv file of the lambda_GC values for the GWAS upon inclusion of different numbers of PCs. This allows the user to choose a number of PCs that returns a lambda_GC close to 1, and thus ensure that they have done adequate correction for population structure.

Usage

div_lambda_GC(
  df,
  type = c("linear", "logistic"),
  snp,
  svd = NA,
  ncores = 1,
  npcs = c(0:10),
  saveoutput = FALSE
)

Arguments

df	Dataframe of phenotypes where the first column is sample.ID and each sample.ID occurs only once in the dataframe.
type	Character string. Type of univarate regression to run for GWAS. Options are "linear" or "logistic".
snp	A bigSNP object with sample.IDs that match the df.
svd	big_SVD object; Covariance matrix to include in the regression. Generate these using bigsnpr::snp_autoSVD().
ncores	Number of cores to use. Default is one.
npcs	Integer vector of principle components to use. Defaults to c(0:10).
saveoutput	Logical. Should output be saved as a csv to the working directory?

Value

A dataframe containing the lambda_GC values for each number of PCs specified. This is also saved as a .csv file in the working directory.

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