plotPCA4plink: Population outlier detection via PCA

In Junfang/Gimpute: Gimpute: An efficient genetic data processing and imputation pipeline

Description

Perform principle component analysis (PCA) on quality controlled genotype data set in order to detect population outliers, and plot the PCs for visualization. Note that, only autosomal genotypes are used for computing principle components.

Usage

plotPCA4plink(gcta, inputPrefix, outputPC4subjFile, outputPCplotFile)

Arguments

gcta	an executable GCTA program in either the current working directory or somewhere in the command path.
inputPrefix	the prefix of the input PLINK format files.
outputPC4subjFile	the pure text file that stores all the subject IDs after QC and their corresponding eigenvalues of the first two principle components.
outputPCplotFile	the plot file for visualizing the first two principle components of all subjects.

Value

The output pure text file and plot file for storing first two principle components of study subjects.

Author(s)

Junfang Chen <[e-mail]>

Junfang/Gimpute documentation built on May 17, 2019, 10:11 p.m.