RunPHATE: Perform nonlinear dimension reduction using PHATE.

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

Perform nonlinear dimension reduction using PHATE.

Description

This function wraps the PHATE dimension reduction algorithm in the typical Seurat syntax.

Usage

RunPHATE(
  object = NULL,
  n.components = 2,
  n.PC = NULL,
  mds.method = "smacof",
  dist.metric = "cosine",
  random.seed = 312
)

Arguments

object	The Seurat object you'd like to run PHATE on. Defaults to NULL.
n.components	How dimensions should the data be reduced to? Defaults to p = 2.
n.PC	How many PCs should be used as input to the algorithm? Defaults to NULL.
mds.method	The solver used for MDS. Defaults to SMACOF, but SGD can be used to speed up the algorithm.
dist.metric	The distance metric to use for KNN and MDS. Defaults to the cosine distance.
random.seed	The random seed used to control stochasticity. Defaults to 312.

Value

A Seurat object with an added dimension reduction object for the p-dimensional PHATE embedding.

Author(s)

Jack Leary

See Also

phate

Examples

## Not run: 
RunPhate(object = pbmc,
         n.components = 2,
         n.PC = 10)
RunPhate(object = pbmc,
         n.components = 5,
         n.PC = 30,
         dist.metric = "euclidean")

## End(Not run)

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