run_tsne: Run tSNE

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

Run tSNE

Description

This functions runs the Seurat RunTSNE function on a list of data sets. This functions assumes that genes are in rows and cells are in columns. The default reduction is set to "pca" with the first 10 dimensions being accepted. The perplexity is set to the square root of the number of cells, to accommodate for small datasets, and check_duplicated is set to be false

Usage

run_tsne(dataList, reductionType = "pca", numDimensions = 10)

Arguments

dataList	A list of data sets to be reduced by tSNE
reductionType	The type of reduction that the tSNE calculation should be based on, defaulted to PCA
numDimensions	The number of dimensions to be used in the tSNE calculation, default is 10

Value

A data list with tSNE completed on the features

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