gene_expr_pca: Custom PCA function for analyzing gene expression data.

In jinhyunju/icreport: Tools for creating a visual summary of matrix decomposition results.

Description

Performing PCA on a dataset and create a list object with results.

Usage

gene_expr_pca(phenotype.mx = NULL, info.df = NULL, check.covars = NULL,
  scale.pheno = FALSE, cor.threshold = 0.05)

Arguments

phenotype.mx	Phenotype matrix with diemnsions g x N
info.df	Dataframe that holds sample covariates (ex. population, gender, age, etc...)
check.covars	Column names of info.df which hold the covariates that should be used for association testing with IC coefficients.
scale.pheno	Logical value specifying the scaling of row of the phenotype.mx. Default is set to FALSE.
cor.threshold	Threshold for significant correlation calling. Default is set to 0.05.

Value

List with the following entries.

jinhyunju/icreport documentation built on May 19, 2019, 10:35 a.m.