GSEA.barplot: Visualize the gene set enrichment analysis

Description Usage Arguments Value Author(s) References See Also Examples

Description

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

Usage

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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

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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)

PPInfer documentation built on Nov. 8, 2020, 7:52 p.m.