enrich_genesets: enrich_genesets

In clatworthylab/bowerbird: A single-cell package for Functional Annotation + Gene Module Summarization.

Description

Runs geneset tests and store in BOWER class.

Usage

## S3 method for class 'list'
enrich_genesets(
  list,
  bower,
  core = FALSE,
  gene_symbol = "X1",
  logfoldchanges = "logfoldchanges",
  pvals = "pvals",
  remove_mito_ribo = TRUE,
  minSize = 0,
  maxSize = 1000,
  ...
)

## S3 method for class 'Seurat'
enrich_genesets(
  sce,
  bower,
  groupby = NULL,
  core = FALSE,
  standardize = TRUE,
  mode = c("AUCell", "Seurat", "scanpy"),
  sce_assay = "logcounts",
  seurat_assay = "RNA",
  ncpus = NULL,
  aucMaxRank_pct = 5,
  ...
)

## S3 method for class 'SingleCellExperiment'
enrich_genesets(
  sce,
  bower,
  groupby = NULL,
  core = FALSE,
  standardize = TRUE,
  mode = c("AUCell", "Seurat", "scanpy"),
  sce_assay = "logcounts",
  seurat_assay = "RNA",
  ncpus = NULL,
  aucMaxRank_pct = 5,
  ...
)

Arguments

list	list containing differentially expressed gene testing results in a data frame.
bower	Processed BOWER object.
core	boolean. Whether or not to use the coregenes of genesets slot. Default is FALSE (use genesets).
gene_symbol	column name for gene_symbol for gsea.
logfoldchanges	column name for logfoldchanges for gsea.
pvals	column name for pvals for gsea.
remove_mito_ribo	boolean. whether or not to remove mitochondial and ribosomal genes from consideration for gsea. Default is TRUE.
minSize	minimum geneset size for gsea. Default is 0.
maxSize	maximum geneset size for gsea. Default is 1000.
...	passed to fgsea::fgsea, AUCell::AUCell_buildRankings or Seurat::AddModuleScore
sce	a single cell object in the format of a Seurat object or SingleCellExperiment object.
groupby	Column name in the meta.data/colData of the single cell objects specifying the group to average the enrichment score. If not specified, not cluster average will be calculated.
standardize	whether or not to standardize mean enrichment values to 0 to 1. Only used if groupby is not NULL.
mode	choice of enrichment test to perform.
sce_assay	name of assay in SingleCellExperiment object.
seurat_assay	name of assay in Seurat object.
ncpus	number of cores used for parallelizing geneset testing.
aucMaxRank_pct	percentage to use for aucMaxRank in AUCell::AUCell_calcAUC.
nperm	number of permuation iterations for gsea. Default is 10000.

Value

Returns a dataframe of average gene set scores.

Examples

library(ktplots)
data(kidneyimmune)
gmt_file <- system.file("extdata", "h.all.v7.4.symbols.gmt", package = "bowerbird")
bwr <- bower(gmt_file)
bwr <- snn_graph(bwr)
bwr <- find_clusters(bwr)
bwr <- summarize_clusters(bwr, ncpus = 1)
bwr <- enrich_genesets(kidneyimmune, bwr, groupby = 'celltype', ncpus = 1)
bwr

clatworthylab/bowerbird documentation built on Dec. 19, 2021, 5:15 p.m.