In cbg-ethz/dce: Pathway Enrichment Based on Differential Causal Effects

Introduction

Load required packages

Load the package with the library function.

library(tidyverse)
library(ggplot2)

library(dce)

set.seed(42)

Pathway database overview

We provide access to the following topological pathway databases using graphite [@sales2012graphite] in a processed format. This format looks as follows:

dce::df_pathway_statistics %>%
  arrange(desc(node_num)) %>%
  head(10) %>%
  knitr::kable()

Let's see how many pathways each database provides:

dce::df_pathway_statistics %>%
  count(database, sort = TRUE, name = "pathway_number") %>%
  knitr::kable()

Next, we can see how the pathway sizes are distributed for each database:

dce::df_pathway_statistics %>%
  ggplot(aes(x = node_num)) +
    geom_histogram(bins = 30) +
    facet_wrap(~ database, scales = "free") +
    theme_minimal()

Plotting pathways

It is easily possible to plot pathways:

pathways <- get_pathways(
  pathway_list = list(
    pathbank = c("Lactose Synthesis"),
    kegg = c("Fatty acid biosynthesis")
  )
)

lapply(pathways, function(x) {
  plot_network(
    as(x$graph, "matrix"),
    visualize_edge_weights = FALSE,
    arrow_size = 0.02,
    shadowtext = TRUE
  ) +
    ggtitle(x$pathway_name)
})