FSbyPCA: Biological feature (such as gene) dimension reduction and...

In xtsvm/CancerSubtypes: Cancer subtypes identification, validation and visualization based on multiple genomic data sets

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 [e-mail],Thuc Le [e-mail]

Examples

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

xtsvm/CancerSubtypes documentation built on May 4, 2019, 1:26 p.m.