perform_pca: Performing PCA analysis

In schyen/somefxns: Generic Tools to Help with Analysis

Description

Performing PCA analysis

Usage

perform_pca(data, sampleID = "sample_name", variable, value = "value",
  scale = "UV", center = TRUE, convert.NA = FALSE, print = TRUE)

Arguments

data	dataframe; data to be used for PCA. Sample metadata is in columns and the variables involved (i.e. compound or species)
sampleID	string. column name for sampleID. Default 'sample_name'
variable	string; the column name in which variables are stored
value	string; default 'value'; the column name in which data values are stored (i.e. 'concentration' or 'abundance')
scale	'UV' for unit variance, 'UVN' for no unit variance, 'pareto'; default UV
center	logical; mean centering; default to TRUE
convert.NA	logical; where value is NA, convert value to 0; desirable when want to explicitly say missing values are true zeros (i.e. below limit of detection) and not missing from analysis
print	logic. Default TRUE. print preview of pca results

Value

prcomp object; PCA-processed data

schyen/somefxns documentation built on Aug. 6, 2019, 2:26 p.m.