preprocess: Preprocess input data with Principal Component Analysis...

Description Usage Arguments Value

View source: R/preprocess.R

Description

Preprocess input data with Principal Component Analysis method (PCA)

Usage

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preprocess(data, pheno = NULL, method = "pca", reg.family = "binomial",
  scaleData = FALSE, cumvar.threshold = 75, out.type = "D",
  penalty = 0.001, verbose = FALSE)

Arguments

data

An input matrix with values of independent variables (predictors).

pheno

A phenotype - column-vector, needed for LASSO/ridge and NULL by default.

method

A dimensionality reduction method. Default: pca.

reg.family

A regression family. Default: "binomial".

scaleData

A logical variable, indicates wheither or not scaling should be performed. Default: FALSE.

cumvar.threshold

A threshold value for explained variance. Default: 75

out.type

An output (phenotype) type. Default: "D"

penalty

Value of penalty parameter for LASSO/ridge regression. Default: 0.001

verbose

Indicates verbosing output. Default: FALSE.

Value

A list of one: "S" - a data frame of predictor values.


izhbannikov/rqt documentation built on May 18, 2019, 7:14 a.m.