cellmarker_enrich {scMappR}

Fisher's Exact Cell-Type Identification.

Description

This function uses the CellMarker and Panglao datasets to identify cell-type differentially expressed genes.

Usage

cellmarker_enrich(
  gene_list,
  p_thresh,
  gmt = "cellmarker_list.Rdata",
  fixed_length = 13000,
  min_genes = 5,
  max_genes = 3000,
  isect_size = 3
)

Arguments

gene_list

A character vector of gene symbols with the same designation (e.g. mouse symbol - mouse, human symbol - human) as the gene set database.

p_thresh

The Fisher's test cutoff for a cell-marker to be enriched.

gmt

Either a path to an rda file containing an object called "gmt", which is a named list where each element of the list is a vector of gene symbols website for more detail on the file type (https://software.broadinstitute.org/cancer/software/gsea/wiki/index.php/Data_formats). The gmt list may also be inputted.

fixed_length

Estimated number of genes in your background.

min_genes

Minimum number of genes in the cell-type markers.

max_genes

Maximum number of genes in the cell-type markers.

isect_size

Number of genes in your list and the cell-type.

Details

Complete a Fisher's exact test of an input list of genes against a gene set saved in an *.RData object. The RData object is storing a named list of genes called "gmt".

Value

cellmarker_enrich Gene set enrichment of cell-types on your inputted gene list.

Examples

data(POA_example)
POA_generes <- POA_example$POA_generes
POA_OR_signature <- POA_example$POA_OR_signature
POA_Rank_signature <- POA_example$POA_Rank_signature
Signature <- POA_Rank_signature
rowname <- get_gene_symbol(Signature)
rownames(Signature) <- rowname$rowname
genes <- rownames(Signature)[1:100]
data(gmt)
enriched <- cellmarker_enrich(gene_list = genes, 
                              p_thresh = 0.05, gmt = gmt)