data: Simplify data structure

This commit also adds the input data to the index.
This commit is contained in:
Elias Projahn 2021-06-24 20:20:46 +02:00
parent 914673c79c
commit 998009b418
205 changed files with 3296891 additions and 272 deletions

41
data.R
View file

@ -27,35 +27,34 @@ load_data_cached <- function(path) {
#' Merge genome data from files in `path` into `tibble`s.
#'
#' The result will be a list with two named elements:
#' - `genes` will be a table with one row per unique `geneid` and multiple
#' columns per species containing the data of interest.
#' - `species` will contain additional information on each species.
#' The result will be a list with named elements:
#' - `genes` will be a table with metadata on human genes.
#' - `species` will contain metadata on each species.
#' - `distances` will contain each species' genes' distances to the telomere.
#'
#' @seealso [load_data_cached()]
load_data <- function(path) {
# The resulting table for information by species.
genes <- read_tsv(paste(path, "genes.tsv", sep = "/"))
species <- read_csv(paste(path, "species.csv", sep = "/"))
# The resulting table for information by gene. For each species, columns
# will be appended.
genes <- tibble(geneid = integer())
distances <- tibble(geneid = integer())
# Each file will contain data on one species.
file_names <- list.files(path, "*_raw.txt")
file_names <- list.files(paste(path, "genomes", sep = "/"))
# Table containing additional columns to be added to the species table.
# Table containing additional columns to be added to the species table
# later.
species_computed <- tibble(
id = character(),
median_distance = numeric()
)
for (file_name in file_names) {
species_id <- strsplit(file_name, split = "_")[[1]][1]
genes_for_species <- read_tsv(paste(path, file_name, sep = "/"))
species_id <- strsplit(file_name, split = ".", fixed = TRUE)[[1]][1]
species_path <- paste(path, "genomes", file_name, sep = "/")
species_distances <- read_tsv(species_path)
# Compute the median distance across all genes of this species.
median_distance <- genes_for_species %>%
median_distance <- species_distances %>%
select(dist) %>%
summarise(median_distance = median(dist)) %>%
pull(median_distance)
@ -67,19 +66,19 @@ load_data <- function(path) {
)
# Column names have to be unique for each species.
genes_for_species <- rename_with(
genes_for_species,
~ paste(species_id, .x, sep = "_"),
c(dist, name, chromosome)
)
# TODO: How to create a dynamic column name using `rename()`?
species_distances <- species_distances %>%
rename_with(function(x) species_id, dist)
genes <- full_join(genes, genes_for_species)
distances <- full_join(distances, species_distances)
}
# Add additional columns to the original species table.
species <- left_join(species, species_computed)
list(
genes = genes,
species = species
species = species,
distances = distances
)
}