reactomepa.enrich: Reactome pathway analysis

Description Usage Arguments Value See Also Examples

View source: R/reactomepa.enrich.R

Description

reactome.enrich utilizes the package 'ReactomePA' to test for enrichment of reactome pathways in your gene list

Usage

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reactomepa.enrich(
  CSS,
  genome.db = org.Hs.eg.db,
  pvalue = 0.05,
  combine = FALSE,
  combine.by = NULL,
  metric = "cutoff",
  cutoff = 1,
  save = FALSE,
  save.table = FALSE,
  showCategory = 15,
  font.size = 8,
  cex_label_category = 1,
  cex_label_gene = 1
)

Arguments

CSS

output CRISPR screen score matrix from create.CSS()

genome.db

genome database from which to convert gene symbols to entrez ids

pvalue

specified cutoff for pathway significance (default = 0.05)

combine

logical: do you want to combine the columns in the data? (default=FALSE)

combine.by

vector separating the columns of your data into groups for comparing multiple groups

metric

defines whether to look for enrichment based on a gene list of differentially expressed genes defined by a 'cutoff' (default) or by 'gsea' (one sample or fully combined samples only)

cutoff

numeric cutoff to define differential expression (default = 1)

save

logical: saves plots to pdf

save.table

logical: saves tables of enriched pathways

showCategory

number of categories to display

font.size

font size of labels in dotplot and barplot

Value

list of (1) output from ReactomePA enrichment tests and (2) readable output

See Also

ReactomePA, clusterProfiler

Examples

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reactome.enrich <- reactomepa.enrich(CSS.data[,1, drop=FALSE])
reactome.enrich <- reactomepa.enrich(CSS.data[,c(1:5)])
reactome.enrich <- reactomepa.enrich(CSS.data[,c(1:5)], combine = T)
reactome.enrich <- reactomepa.enrich(CSS.data[,1, drop = FALSE], metric = 'gsea')
...

christensensm/COMPOSE documentation built on Dec. 22, 2020, 3:43 a.m.