ClusterDR: Run all Dimension Reduction methods and find marker genes...

In Morriseylab/scExtras: Single cell data analysis helper functions

Run all Dimension Reduction methods and find marker genes between clusters

Description

Run all Dimension Reduction methods and find marker genes between clusters

Usage

ClusterDR(
  object,
  dims,
  n.neighbors = 30,
  k = 20,
  algorithm = 1,
  DM = F,
  UMAP = T,
  TSNE = T,
  findallmarkers = T,
  resolution = 0.5,
  n.components = 2,
  min.dist = 0.3
)

Arguments

object	Seurat object
n.neighbors	n number of neighbors for umap
k	K prarma for find neifhbors
DM	Run diffusion map
UMAP	Run UMAP
TSNE	Run TSNE
findallmarkers	T/F run findallmarkers
resolution	Resolution param for FindCluster
n.components	How many components to compute for Dim reductions (UMAP,DM,etc)
min.dist	minimum distance parameter for RunUMAP function. Controls how tightly to compress the umap points together
dim	Which dimensions to use as input features

Morriseylab/scExtras documentation built on July 10, 2024, 6:41 a.m.