PathwayEmbed is an R package for quantifying and visualizing intracellular signaling pathway activation from transcriptomic data, integrating pathway topology and gene expression data.
You can install the released version of PathwayEmbed from GitHub using:
# Install remotes if you haven't already
if (!requireNamespace("remotes", quietly = TRUE)) {
install.packages("remotes")
}
remotes::install_github("RaredonLab/PathwayEmbed")
library(PathwayEmbed)
# Load example data included with the package
data("synthetic_test_object_100")
data("synthetic_test_metadata")
# Check what pathways are availabel in the pre-constructed table
ListPathway() # summary page
ListPathway("Pathway") # what pathways are available
ListPathway("WNT") # what coefficient tables are available
# Load pre-constructed pathway coefficient tables
Wnt_12h <- LoadPathway("WNT3A_12H_ACTIVATION", "mouse")
# Input data preprocess
matrix_12h <- DataPreProcess(synthetic_test_object_100, Wnt_12h, Seurat.object = TRUE)
# Determine the global reference (ON and OFF)
pathwaystat_12h <- PathwayMaxMin(matrix_12h, Wnt_12h)
# Compute pathway data
score_12h <- ComputeCellData(matrix_12h, pathwaystat_12h)
# Prepare data for plotting
plot_data_12h <- PreparePlotData(synthetic_test_metadata, score_12h, group = "genotype")
# Plot pathway activation
PlotPathway(plot_data_12h, "12hr Wnt", "genotype", c("#ae282c", "#2066a8"))
# Calculate percentage and do comparison between two groups (optional)
CalculatePercentage(to.plot = plot_data_12h, group_var = "genotype")