process_SCTbase: process Seurat Spatial object via SCT

In eisascience/scCustFx: single-cell custom fxs Package

process Seurat Spatial object via SCT

Description

process Seurat Spatial object via SCT

This function takes in a seurat object and applies various transformations and clustering algorithms. The end goal is to identify cell types and subpopulations within the data.

Usage

process_SCTbase(
  SerObj = NULL,
  ncells = 3000,
  assay = "Spatial",
  dims = 1:30,
  verbose = T,
  clusterResolutions = c(0.2, 0.4, 0.6, 0.8, 1.2)
)

process_SCTbase(
  SerObj = NULL,
  ncells = 3000,
  assay = "Spatial",
  dims = 1:30,
  verbose = T,
  clusterResolutions = c(0.2, 0.4, 0.6, 0.8, 1.2)
)

Arguments

SerObj	A seurat object containing single cell transcriptomics data
ncells	The number of cells used to build NB regression, default is 3000
assay	The assay used to run the SCT transformation, default is "Spatial"
dims	The dimensions to use for running PCA, t-SNE, UMAP, default is 1:30
verbose	Logical, whether to print progress messages, default is TRUE
clusterResolutions	A numeric vector of resolutions to use for finding clusters, default is c(0.2, 0.4, 0.6, 0.8, 1.2)

Value

A Processed Seurat Obj

A seurat object with added dimensionality reductions, clustering, and cell type annotations.

eisascience/scCustFx documentation built on June 2, 2025, 3:59 a.m.