plotVennPathway | R Documentation |
Plot a Venn diagram from multiple pathway analysis results.
plotVennPathway(PAResults, pThreshold = 0.05, useFDR = TRUE, topToList = 10)
PAResults |
A list of data frames with the results of pathway analysis. |
pThreshold |
The p-value threshold to determine if a pathway is enriched. |
useFDR |
Use the FDR adjusted p-value instead of the raw p-value. |
topToList |
The number of common signifcant pathways that are used to annotate the plot. |
A ggplot2 object.
library(RCPA)
affyFgseaResult <- loadData("affyFgseaResult")
agilFgseaResult <- loadData("agilFgseaResult")
RNASeqFgseaResult <- loadData("RNASeqFgseaResult")
metaPAResult <- loadData("metaPAResult")
PAResults <- list(
"Affymetrix - GSE5281" = affyFgseaResult,
"Agilent - GSE61196" = agilFgseaResult,
"RNASeq - GSE153873" = RNASeqFgseaResult,
"Meta-analysis" = metaPAResult
)
PAREsultUps <- lapply(PAResults, function(df) df[df$normalizedScore > 0,])
PAREsultDowns <- lapply(PAResults, function(df) df[df$normalizedScore < 0,])
if (require("ggvenn", quietly = TRUE)){
p1 <- RCPA::plotVennPathway(PAResults, pThreshold = 0.05) +
ggplot2::ggtitle("All Significant Pathways")
p2 <- RCPA::plotVennPathway(PAREsultUps, pThreshold = 0.05) +
ggplot2::ggtitle("Significantly Up-regulated Pathways")
p3 <- RCPA::plotVennPathway(PAREsultDowns, pThreshold = 0.05) +
ggplot2::ggtitle("Significantly Down-regulated Pathways")
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.