Run_fGSEA_analysis: Run GSEA analysis

In supatt-lab/SingCellaR: SingCellaR: an integrative analysis tool for single-cell RNA sequencing (scRNA-seq) data

Run GSEA analysis

Description

Run GSEA analysis

Usage

Run_fGSEA_analysis(
  objectA = objectA,
  objectB = objectB,
  cellsA = c(),
  cellsB = c(),
  GSEAPrerankedGenes_info = "",
  gmt.file = "",
  plotGSEA = T,
  nTopGenesets = 10,
  minSize = 5,
  maxSize = 1000,
  eps = 0,
  nPermSimple = 1000
)

Arguments

objectA	The SingCellaR object A
objectB	The SingCellaR object B
cellsA	The vector of cell names from object A
cellsB	The vector of cell names from object B
GSEAPrerankedGenes_info	The dataframe object of preranked genes.
gmt.file	The GMT file name
plotGSEA	is logical. If TRUE, this function will plot GSEA enrichment.
nTopGenesets	The number of showing top gene sets.
minSize	The cutoff minimum number of genes in each gene set. Gene set that contains the number of genes lower than this number will be excluded. Default 5
maxSize	The cutoff maxiumum number of genes in each gene set. Gene set that contains the number of genes higher than this number will be excluded. Default 1000
eps	The eps paramenter for fgsea, this parameter sets the boundary for calculating the p value. Default 0
nPermSimple	The number of permutations in the simple fgsea implementation for preliminary estimation of P-values.

supatt-lab/SingCellaR documentation built on Aug. 24, 2023, 5:49 p.m.