genbin-package: genbin: R wrappers for binaries in genetics

genbin-packageR Documentation

genbin: R wrappers for binaries in genetics

Description

Conveniently run genetics analysis involving external binary executables from R. Pipelines support simple procedures for creating, reading, and cleaning up files, in some cases complemented by the genio package.

Author(s)

Maintainer: Alejandro Ochoa alejandro.ochoa@duke.edu (ORCID)

See Also

Useful links:

Examples

## Not run: 
library(genbin)
library(genio)

# examples below assume these "plink" files exist:
# name.bed, name.bim, name.fam, name.phen
name <- 'name'
# number of PCs for some examples:
n_pcs <- 10

### GCTA pipeline

# The GCTA examples assume that `gcta64` is a binary in the system's PATH.

# create GRM from plink files
gcta_grm( name )
# optional: read kinship matrix into R
data <- genio::read_grm( name )
kinship <- data$kinship

# perform mixed linear model association, returning table
data <- gcta_mlma( name )
# association p-values
data$p

# optional: calculate PCs (creates eigenvec/eigenval files)
gcta_pca( name, n_pcs = n_pcs )
# read PCs into R
data <- genio::read_eigenvec( name )
# delete eigenvec/eigenval files
delete_files_pca( name )

# cleanup
# delete GRM files
genio::delete_files_grm( name )
# delete association table
delete_files_gcta_mlma( name )
# delete log
delete_files_log( name )

### PLINK PCA pipeline

# The plink examples assume that `plink2` is a binary in the system's PATH.

# calculate PCs (creates eigenvec/eigenval files)
plink_pca( name, n_pcs = n_pcs )
# optional: read PCs into R
data <- genio::read_eigenvec( name )

# perform PCA association, returning table
data <- plink_glm( name, file_covar = paste0( name, '.eigenvec' ) )
# association p-values
data$p

# cleanup
# delete eigenvec/eigenval files
delete_files_pca( name )
# delete association table
delete_files_plink_glm( name )
# delete log
delete_files_log( name )


## End(Not run)


OchoaLab/genbin documentation built on Nov. 14, 2024, 7:33 p.m.