prepareDataFromscRNA: Prepare scRNA Data for clusterGvis Analysis

In ClusterGVis: One-Step to Cluster and Visualize Gene Expression Data

Prepare scRNA Data for clusterGvis Analysis

Description

This function prepares single-cell RNA sequencing (scRNA-seq) data for differential gene expression analysis. It extracts the expression data for the specified cells and genes, and organizes them into a dataframe format suitable for downstream analysis.

Usage

prepareDataFromscRNA(
  object = NULL,
  diffData = NULL,
  showAverage = TRUE,
  cells = NULL,
  group.by = "ident",
  assays = "RNA",
  slot = "data",
  scale.data = TRUE,
  cluster.order = NULL,
  keep.uniqGene = TRUE,
  sep = "_"
)

Arguments

object	an object of class Seurat containing the scRNA-seq data.
diffData	a dataframe containing information about the differential expression analysis which can be output from function FindAllMarkers.
showAverage	a logical indicating whether to show the average gene expression across all cells.
cells	a vector of cell names to extract from the Seurat object. If NULL, all cells will be used.
group.by	a string specifying the grouping variable for differential expression analysis. Default is 'ident', which groups cells by their assigned clusters.
assays	a string or vector of strings specifying the assay(s) to extract from the Seurat object. Default is 'RNA'.
slot	a string specifying the slot name where the assay data is stored in the Seurat object. Default is 'data'.
scale.data	whether do Z-score for expression data, default TRUE.
cluster.order	the celltype orders.
keep.uniqGene	a logical indicating whether to keep only unique gene names. Default is TRUE.
sep	a character string to separate gene and cell names in the output dataframe. Default is "_".

Value

a dataframe containing the expression data for the specified genes and cells, organized in a format suitable for differential gene expression analysis.

ClusterGVis documentation built on April 4, 2025, 2:27 a.m.