run_pca: Run Principle Component Analysis

In NWhitener/benchmarking: Benchmarking Tools For Single Cell RNA Sequencing Datasets

Run Principle Component Analysis

Description

This functions runs the Seurat RunPCA function on a list of data sets. This functions assumes that genes are in rows and cells are in columns. Verbose is set to false, the Features are set to be the Variable Features of the data set, the default number of components is 10, and the PCA is run on only scaled data

Usage

run_pca(dataList, numComponents = 10)

Arguments

dataList	A list of data sets to be reduced by PCA
numComponents	The number of components to be found, with a default of 10

Value

A data list with PCA completed on the features

NWhitener/benchmarking documentation built on Oct. 23, 2023, 12:20 a.m.