FSbyPCA {CancerSubtypes}R Documentation

Biological feature (such as gene) dimension reduction and extraction based on Principal Component Analysis.

Description

This function is based on the prcomp(), we write a shell for it and make it easy to use on genomic data.

Usage

FSbyPCA(Data, PC_percent = 1, scale = TRUE)

Arguments

Data

A data matrix representing the genomic data measured in a set of samples. For the matrix, the rows represent the genomic features, and the columns represents the samples.

PC_percent

A numeric values in [0,1] representing the ratio of principal component is seclected.

scale

A bool variable, If true, the Data is normalized before PCA.

Value

A new matrix with full or part Principal Component in new projection space.

Author(s)

Xu,Taosheng taosheng.x@gmail.com,Thuc Le Thuc.Le@unisa.edu.au

Examples

data(GeneExp)
data1=FSbyPCA(GeneExp, PC_percent=0.9,scale = TRUE)
 

[Package CancerSubtypes version 1.18.0 Index]