PCADS: Principal Component Analysis (PCA) on SNP genotype data

In isglobal-brge/dsOmics: DataSHIELD server site Omic functions

Principal Component Analysis (PCA) on SNP genotype data

Description

PCA for genotype data on the study server

Usage

PCADS(genoData, pca_rs, pca_means, pca_sd_hw)

Arguments

genoData	GenotypeData object
pca_rs	vector of strings SNPs included on the standardization. Obtained with dsBaseClient::standardizeGenoData
pca_means	vector of numerics Means. Obtained with dsBaseClient::standardizeGenoData
pca_sd_hw	vector of numerics Standar deviations. Obtained with dsBaseClient::standardizeGenoData

Details

Pooled method implemented using block method ("Parallel Algorithms for the Singular Value Decomposition." Berry et al. 2005). The snp_subset option uses gene regions that have been linked to ethnic groupings, it is suggested to use this option to optimize the computing time and get noise-less principal components.

Value

data.frame with the results

isglobal-brge/dsOmics documentation built on March 22, 2023, 4:01 a.m.