annotate_clusters: annotate_clusters functionally annotates the identified...

In IMB-Computational-Genomics-Lab/scGPS: A complete analysis of single cell subpopulations, from identifying subpopulations to analysing their relationship (scGPS = single cell Global Predictions of Subpopulation)

Description

often we need to label clusters with unique biological characters. One of the common approach to annotate a cluster is to perform functional enrichment analysis. The annotate implements ReactomePA and clusterProfiler for this analysis type in R. The function require installation of several databases as described below.

Usage

annotate_clusters(
  DEgeneList,
  pvalueCutoff = 0.05,
  gene_symbol = TRUE,
  species = "human"
)

Arguments

DEgeneList	is a vector of gene symbols, convertable to ENTREZID
pvalueCutoff	is a numeric of the cutoff p value
gene_symbol	logical of whether the geneList is a gene symbol
species	is the selection of 'human' or 'mouse', default to 'human' genes

Value

write enrichment test output to a file and an enrichment test object for plotting

Examples

genes <-training_gene_sample
genes <-genes$Merged_unique[seq_len(50)]
enrichment_test <- annotate_clusters(genes, pvalueCutoff=0.05, 
    gene_symbol=TRUE, species = 'human')
clusterProfiler::dotplot(enrichment_test, showCategory=15)

IMB-Computational-Genomics-Lab/scGPS documentation built on Dec. 6, 2020, 3:20 p.m.