ReduceDimensions: Run PCA / t-SNE / UMAP / PHATE.

In jr-leary7/SCISSORS: Identify cell subpopulations in single cell RNA-seq data

Run PCA / t-SNE / UMAP / PHATE.

Description

This function simplifies the running of various dimension reduction algorithms. It exists mostly to make the body of ReclusterCells easier to read.

Usage

ReduceDimensions(
  obj = NULL,
  n.PC = "auto",
  which.algos = c("umap"),
  random.seed = 312
)

Arguments

obj	The Seurat object to run dimension reduction algorithms on. Defaults to NULL.
n.PC	How many principal components should be used? Can be an integer or "auto". Defaults to "auto".
which.algos	Which nonlinear dimension algorithms can be used? Should be some combination of "tsne", "umap", and "phate". Defaults to "umap".
random.seed	The random seed to use. Defaults to 312.

Value

A Seurat object.

Author(s)

Jack Leary

See Also

RunPHATE

Examples

## Not run: 
ReduceDimensions(pbmc,
                 n.PC = 10,
                 which.algos = c("umap", "phate"))

## End(Not run)

jr-leary7/SCISSORS documentation built on April 20, 2023, 8:21 p.m.