GSEA.barplot: Visualize the gene set enrichment analysis

In dongminjung/PPInfer: Inferring functionally related proteins using protein interaction networks

Description

For the functional enrichment analysis, we can visualize the result from the gene set enrichment analysis.

Usage

GSEA.barplot(object, category, score, pvalue, top = 10,
             sort = NULL, decreasing = FALSE, numChar = NULL, 
             title = NULL, transparency = 0.5, plot = TRUE)

Arguments

object	a table with category, enrichment score and p-value of gene sets
category	name of gene sets
score	enrichment score
pvalue	p-value of gene sets
top	the number of top categories (default: 10)
sort	a variable used for sorting data
decreasing	logical indicating whether ascending or descending order (default: FALSE)
numChar	the maximal number of characters of the name of gene sets
title	title for the plot
transparency	transparency (default: 0.5)
plot	return plot when plot is true, otherwise return table (default: TRUE)

Value

GSEA barplot

Author(s)

Dongmin Jung, Xijin Ge

References

Yu G, Wang L, Yan G and He Q (2015). "DOSE: an R/Bioconductor package for Disease Ontology Semantic and Enrichment analysis." Bioinformatics, 31(4), pp. 608-609.

See Also

ggplot2

Examples

data(examplePathways)
data(exampleRanks)
set.seed(1)
result.GSEA <- fgsea(examplePathways, exampleRanks, nperm = 1000)
GSEA.barplot(result.GSEA, category = 'pathway', score = 'NES',
             pvalue = 'pval', sort = 'NES', decreasing = TRUE)

dongminjung/PPInfer documentation built on May 15, 2019, 10:41 a.m.