#!/usr/bin/env Rscript
## Building an Epilepsy gene dataset from the genes compiled by
# Wang et al., 2017. Data were obtained from the personal communication
# with the author.
renv::load(getrd())
## User parameters:
script <- "009_Wang-2017-Epilepsy-geneSet"
short_name <- "wang2017Epilepsy"
paper_url <- "https://www.ncbi.nlm.nih.gov/pubmed/28007376"
gene_source <- "Wang_et_al_2017"
# Description of the data:
data_description <- c(
"977 epilepsy-associated genes were compiled from",
"the literature and online databases. Genes were",
"classified into 4 phenotypic categories.",
"(1) Syndromic epilepsy genes (84 genes).",
"(2) Neurodevelopment-associated epilepsy",
"genes (73 genes). (3) Epilepsy-related genes",
"associated with both physical or other systemic",
"abnormalities and epilepsy or seizures (536 genes).",
"(4) Putative epilepsy genes (284 genes)."
)
# Load functions.
devtools::load_all()
# Other imports.
suppressPackageStartupMessages({
library(readxl)
library(data.table)
library(dplyr)
library(getPPIs)
})
# Directories.
root <- getrd()
gmtdir <- file.path(root, "gmt")
funcdir <- file.path(root, "R")
datadir <- file.path(root, "data")
rdatdir <- file.path(root, "rdata")
tabsdir <- file.path(root, "tables")
downdir <- file.path(root, "downloads")
# Load the data.
myfile <- file.path(downdir, "Wang_et_al_2017_Epilepsy_Genes.xlsx")
data <- read_excel(myfile)
# Clean up the columns.
colnames(data) <- c("Epilepsy", "Neurodevelopment", "Epilepsy-Related", "Potential", "All")
# Melt.
df <- reshape2::melt(data, measure.vars = colnames(data))
colnames(df) <- c("Category", "Gene")
# Map human genes to entrez.
# Why is mapIds returning a list??
genes <- unique(df$Gene)
entrez <- getIDs(genes, from = "symbol", to = "entrez", species = "human")
df$Entrez <- entrez[df$Gene]
# Remove NA.
df <- df[!is.na(df$Entrez), ]
# Map human genes to mouse genes.
df$msEntrez <- getHomologs(df$Entrez, taxid = 10090)
# Remove NA.
df <- df[!is.na(df$msEntrez), ]
# Save table.
myfile <- file.path(tabsdir, paste0(script, ".csv"))
fwrite(df, myfile)
# Split into categories.
gene_groups <- split(df$msEntrez, df$Category)
# Progress report:
ngenes <- length(unique(df$msEntrez))
message(paste("Compiled", ngenes, "mouse epilepsy genes."))
sizes <- sapply(gene_groups, length)
knitr::kable(t(sizes), row.names = FALSE, format = "markdown")
# Save as gmt.
myfile <- file.path(gmtdir, script)
write_gmt(gene_groups, gmt_source = paper_url, gmt_file = myfile)
# Save as rda and generate documentation.
documentDataset(myfile, short_name, Rdir = file.path(root, "R"), datadir)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.