This function supports any combination of numeric x-y variables to plot from fedup results. The list outputted by runFedup must first be converted to a data.frame before plotting (see examples for sample use).

plotDotPlot(
    df,
    xVar,
    yVar,
    xLab = xVar,
    yLab = NULL,
    pTitle = NULL,
    fillVar = NULL,
    fillCol = NULL,
    fillLab = fillVar,
    sizeVar = NULL,
    sizeLab = sizeVar
)

Arguments

df

(data.frame) table with fedup results generated via runFedup

xVar

(char) x-axis variable (must be a column value in df)

yVar

(char) y-axis variable (must be a column value in df)

xLab

(char) x-axis label (default xVar value)

yLab

(char) y-axis label (default NULL)

pTitle

(char) plot title (default NULL)

fillVar

(char) point fill variable (default NULL)

fillCol

(char) point fill colours (default NULL)

fillLab

(char) point fill label (default fillVar value)

sizeVar

(char) point size variable (default NULL)

sizeLab

(char) point size label (default sizeVar value)

Value

Object returned from ggplot with the enrichment dot plot.

Examples

# Load example data data(geneDouble) data(pathwaysGMT) # Load external libraries suppressMessages(library(dplyr)) suppressMessages(library(tidyr)) # Run fedup fedupRes <- runFedup(geneDouble, pathwaysGMT)
#> Running fedup with: #> => 2 test set(s) #> + FASN_negative: 379 genes #> + FASN_positive: 298 genes #> => 17804 background genes #> => 1437 pathway annotations
#> All done!
# Prepare dataframe from fedup results fedupPlot <- fedupRes %>% bind_rows(.id = "set") %>% separate(col = "set", into = c("set", "sign"), sep = "_") %>% subset(qvalue < 0.01) %>% mutate(log10qvalue = -log10(qvalue)) %>% mutate(pathway = gsub("\\%.*", "", pathway)) %>% as.data.frame() # Plot p <- plotDotPlot( df = fedupPlot, xVar = "log10qvalue", yVar = "pathway", xLab = "-log10(qvalue)", fillVar = "sign", fillLab = "Genetic interaction", fillCol = c("#0077f1", "#fcde24"), sizeVar = "fold_enrichment", sizeLab = "Fold enrichment" )