FindClustersAndDimRedux: Find Clusters And Perform DimRedux

In bimberlabinternal/CellMembrane: A package with high-level wrappers and pipelines for single-cell RNA-seq tools

Find Clusters And Perform DimRedux

Description

Find Clusters And Perform DimRedux

Usage

FindClustersAndDimRedux(
  seuratObj,
  dimsToUse = NULL,
  minDimsToUse = NULL,
  umap.method = "uwot",
  umap.metric = NULL,
  umap.n.neighbors = NULL,
  umap.min.dist = NULL,
  umap.spread = NULL,
  seed.use = GetSeed(),
  umap.n.epochs = NULL,
  max.tsne.iter = 10000,
  tsne.perplexity = 30,
  umap.densmap = FALSE,
  clusterResolutions = c(0.2, 0.4, 0.6, 0.8, 1.2),
  runTSNE = FALSE,
  useLeiden = FALSE
)

Arguments

seuratObj	A Seurat object.
dimsToUse	The number of dims to use. If null, this will be inferred using FindSeuratElbow()
minDimsToUse	The minimum numbers of dims to use. If dimsToUse is provided, this will override.
umap.method	The UMAP method, either uwot or umap-learn, passed directly to Seurat::RunUMAP
umap.metric	Passed directly to Seurat::RunUMAP
umap.n.neighbors	Passed directly to Seurat::RunUMAP
umap.min.dist	Passed directly to Seurat::RunUMAP
umap.spread	Passed directly to Seurat::RunUMAP
seed.use	Passed directly to Seurat::RunUMAP, FindClusters, and RunTSNE
umap.n.epochs	Passed directly to Seurat::RunUMAP
max.tsne.iter	The value of max_iter to provide to RunTSNE. Increasing can help large datasets.
tsne.perplexity	tSNE perplexity. Passed directly to Seurat::RunTSNE(), but CellMembrane:::.InferPerplexityFromSeuratObj() corrects it if need be based dataset dims.
umap.densmap	Passed directly to Seurat::RunUMAP
clusterResolutions	A vector of clustering resolutions, default is (0.2, 0.4, 0.6, 0.8, 1.2).
runTSNE	If true, tSNE will be run. The default is UMAP alone.
useLeiden	If true, Leiden clustering (FindClusters algorithm = 4) will be used. Otherwise it will default to algorithm = 1 (Louvain).

Value

A modified Seurat object.

bimberlabinternal/CellMembrane documentation built on Oct. 16, 2024, 6:53 a.m.