In neurogenomics/orthogene: Interspecies gene mapping

knitr::opts_chunk$set(echo = TRUE, root.dir=here::here())
knitr::opts_knit$set(root.dir=here::here())

Benchmark the following strategies:

1. uppercase : Simply making the genes uppercase.
2. homologene : method="homologene"
3. gorth : method="gorth"

For each method, benchmark the following metrics:

• % genes mapped within species (all_genes).
• % genes mapped to human (map_orthologs).
• Speed of each metric.

library(orthogene)

library(dplyr)
library(ggplot2) 
library(patchwork)

Define species

Repeat tests across various common model organisms.

species <- c(human="H sapiens",
             chimp="P troglodytes",
             baboon="P anubis", 
             macaque = "M mulatta",
             marmoset = "C jacchus",
             mouse = "M musculus",
             rat = "R norvegicus",
             hamster = "M auratus",
             dog = "C lupus familiaris",
             cat = "F catus",
             cow = "B taurus",
             chicken = "G gallus",
             zebrafish = "D rerio",
             fly = "D melanogaster",
             worm = "C elegans",
             rice = "O sativa"
             )
species_mapped <- map_species(species = species) |> `names<-`(names(species))

Benchmark

Note the orthogene:::function notation is needed to use these benchmarking functions, as they are internal.

Run benchmark

run_benchmark() will run the full benchmarking pipeline.

You can set mc.cores to speed this up with multi-core parallelisation.

WARNING: This step can take a long time. For the purposes of this example, we'll not run the full benchmark and instead provide some pre-computed results.

bench_res <- orthogene:::run_benchmark(species_mapped = species_mapped[c("human","mouse","fly")], 
                                       run_convert_orthologs = TRUE, 
                                       mc.cores = 10) 
# write.csv(bench_res, here::here("inst/benchmark/bench_res_example.csv"), row.names = FALSE)

Print results

Load stored benchmark results.

if(!exists("bench_res")) {
  bench_res <- read.csv(system.file(package = "orthogene","benchmark/bench_res_example.csv"))
}
knitr::kable(bench_res)

Plot results

Bar plot

For each method, plot the run time (a) and the number of genes returned (b).

bench_barplot <- orthogene:::plot_benchmark_bar(bench_res = bench_res)
# ggsave(here::here("inst/benchmark/bench_barplot.pdf"),bench_barplot, height = 8)

Scatter plot

For each method, plot the relationship between number of genes returned and run time.

bench_scatterplot <- orthogene:::plot_benchmark_scatter(bench_res = bench_res)
# ggsave(here::here("inst/benchmark/bench_scatterplot.pdf"),bench_scatterplot)

Session Info

utils::sessionInfo()

neurogenomics/orthogene documentation built on Jan. 30, 2024, 4:44 a.m.