runVDJPCA: Run PCA on clonotype abundance matrix

In kstreet13/VDJdive: Analysis Tools for 10X V(D)J Data

Run PCA on clonotype abundance matrix

Description

Perform Principal Components Analysis (PCA) on the matrix of sample-level clonotype abundances. In the context of clonotype analysis, this is a form of beta diversity.

Usage

runVDJPCA(x, ...)

## S4 method for signature 'clonoStats'
runVDJPCA(x, unit = c("samples", "clonotypes"))

Arguments

x	A matrix of abundance values where rows are features (clonotypes) and columns are samples.
...	additional arguments.
unit	Character value indicating whether the unit of interest is "samples" or "clonotypes".

Value

A list with class "prcomp". The component x stores the reduced-dimensional representation of the data. For a full description, see prcomp.

Examples

data('contigs')
x <- clonoStats(contigs)
runVDJPCA(x)

kstreet13/VDJdive documentation built on May 27, 2023, 8:08 a.m.