perform.GO.enrichment: Gene Ontology enrichment

In connorhknight/IBRAP: Integrated Benchmarking scRNA-seq Analytical Pipeline (IBRAP)

Gene Ontology enrichment

Description

Performs gene ontology enrichment for individual cluster differential expression results.

Usage

perform.GO.enrichment(
  result,
  whichOnto = "BP",
  feasibleGenes = NULL,
  mapping = "org.Hs.eg.db",
  ID = "symbol",
  nodeSize = 5,
  algorithm = "classic",
  statistic = "ks",
  rank.cutoff = 0.001,
  gene.col = "gene",
  pval.col = "p_val",
  cluster.col = "cluster",
  n.top.pathways = 10
)

Arguments

result	A database containing the differential expression results
whichOnto	Character. specifying one of the three GO ontologies, namely: "BP", "MF", "CC". Default = 'BP'
feasibleGenes	Character vector. vector containing a subset of gene identifiers. Only these genes will be used to annotate GO terms. Default value is NULL which means that there are no genes filtered.
mapping	Character. The name of the Bioconductor package containing the gene mappings for a specific organism. For example: mapping = "org.Hs.eg.db".
ID	Character. Specify the gene identifier to use. Currently only the following identifiers can be used: c("entrez", "genbank", "alias", "ensembl", "symbol", "genename", "unigene")
nodeSize	Numerical. Minimum number of genes required to consider a GO term. Default = 5
algorithm	Character. Which algorithm to use when testing for significant GO terms, options: 'classic', 'elim', 'weight', 'weight01', 'lea', 'parentchild'. Default = 'classic'
statistic	Character. Which statistic to use when testing for significant GO terms, options: 'fisher', 'ks', 't', 'globaltest', 'sum', 'ks.ties'. Default = 'ks'
rank.cutoff	Numerical. Which cut off to apply for pathway significance, this value will change according to the statistic applied. Default = 0.001
gene.col	Character. Which column name within differential expression results contains the genes. Default = 'gene.col'
pval.col	Character. Which column name within differential expression results contains the p values. Default = 'p_val'
cluster.col	Character. Which column name within differential expression results contains the cluster assignments. Default = 'cluster'
n.top.pathways	Numerical. How many top pathways per group should be retained. Default = 10

Value

A dataframe containing the top enriched pathways for each cluster

Examples

SCT_DE <- perform.seurat.diffexp.all(object = object, assay = 'SCT', test = 'MAST', identity = object@sample_metadata$celltype, latent.vars = 'original.project')

SCT_DE_GO <- perform.GO.enrichment(result = SCT_DE)

plot.GO.output(result = SCT_DE_GO) + ggplot2::ggtitle(label = 'SCT')

connorhknight/IBRAP documentation built on March 9, 2023, 7:01 p.m.