pca123: PCA step 1, 2, 3.

In markgene/yamatClassifier: Yet Another Methylation Array Toolkit: Classifier

PCA step 1, 2, 3.

Description

PCA step 1, 2, 3.

Usage

pca123(x, k = 50)

Arguments

x	A matrix which has columns as features and rows as samples.
k	Number of eigenvalues requested.

Details

PCA steps 1, 2, 3 are:

1. Center and scale.

2. Compute the correlation/covariance matrix.

3. Calculate the eigenvectors and eigenvalues.

I use eigs function in Rspectra package instead of eigen function in base to deal with large matrix.

Value

A list of four elements:

• scaled A matrix of scaled input matrix.

• cor_mat Correlation/covariance matrix of the scaled matrix.

• eigs A list returned by eigs.

• plot A ggplot object of density plot of eigenvalues.

markgene/yamatClassifier documentation built on Oct. 14, 2024, 2:36 a.m.