plotPC: Function to plot the selected number of principal components

In RaceID: Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data

Function to plot the selected number of principal components

Description

This functions plots the percentage variability explained the first one hundred (or pcaComp) pricipal components of the PCA performed in the function pruneKnn if the parameter large was TRUE. The selected number of principal components (if pcaComp was NULL) is determined by an elbow criterion and highlighted by a blue circle.

Usage

plotPC(res, logDiff = FALSE)

Arguments

res	List object with k nearest neighbour information returned by pruneKnn function.
logDiff	logical. If TRUE, then plot log2 of the difference in variability explained by PC i and PC i+1.

RaceID documentation built on Sept. 28, 2023, 5:06 p.m.