projectSample2PCA: Project patients onto existing principal component axes (PCA)

In belleau/aicsPaper: Accurate Inference of Genetic Ancestry from Cancer Sequencing

Project patients onto existing principal component axes (PCA)

Description

This function calculates the patient eigenvectors using the specified SNP loadings.

Usage

projectSample2PCA(gds, listPCA, sample.current, np = 1L)

Arguments

gds	an object of class SNPRelate::SNPGDSFileClass, a SNP GDS file.
listPCA	a list containing two objects pca.unrel -> snpgdsPCAClass and a snp.load -> snpgdsPCASNPLoading
sample.current	a character string representing the identifiant of the sample to be projected in the PCA.
np	a single positive integer representing the number of threads. Default: 1L.

Details

More information about the method used to calculate the patient eigenvectors can be found at the Bioconductor SNPRelate website: https://bioconductor.org/packages/SNPRelate/

Value

a snpgdsPCAClass object, a list that contains:

• sample.id the sample ids used in the analysis

• snp.id the SNP ids used in the analysis

• eigenvalues eigenvalues

• eigenvect eigenvactors, “# of samples” x “eigen.cnt”

• TraceXTX the trace of the genetic covariance matrix

• Bayesian whether use bayerisan normalization

Author(s)

Pascal Belleau, Astrid Deschênes and Alexander Krasnitz

Examples

## Path to the demo pedigree file is located in this package
data.dir <- system.file("extdata", "RAIDS")

## TODO

belleau/aicsPaper documentation built on Aug. 4, 2022, 1:12 a.m.