mirror of
https://github.com/johrpan/geposanui.git
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70 lines
No EOL
2.2 KiB
R
70 lines
No EOL
2.2 KiB
R
library(data.table)
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library(rlog)
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#' Merge genome data from files in `path` into `data.table`s.
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#'
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#' The result will be a list with named elements:
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#' - `genes` will be a table with metadata on human genes.
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#' - `species` will contain metadata on each species.
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#' - `distances` will contain each species' genes' distances to the telomere.
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#'
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#' @seealso [load_data_cached()]
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load_input <- function(path) {
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genes <- fread(paste(path, "genes.tsv", sep = "/"))
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original_species <- fread(paste(path, "species.csv", sep = "/"))
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species <- data.table(
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id = character(),
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group = character(),
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label = character(),
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median_distance = numeric()
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)
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distances <- data.table(
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species = character(),
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gene = integer(),
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distance = integer()
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)
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# Each file will contain data on one species.
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file_names <- list.files(paste(path, "genomes", sep = "/"))
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n_species <- length(file_names)
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for (i in seq_along(file_names)) {
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file_name <- file_names[i]
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species_id <- strsplit(file_name, split = ".", fixed = TRUE)[[1]][1]
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species_path <- paste(path, "genomes", file_name, sep = "/")
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log_info(sprintf(
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"Reading species %i/%i (%s)", i, n_species, species_id
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))
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species_distances <- fread(species_path)
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# Compute the median distance across all genes of this species and
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# add it to the species table along other static data.
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species <- rbindlist(list(species, data.table(
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id = species_id,
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group = original_species[id == species_id, group],
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label = original_species[id == species_id, label],
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median_distance = median(species_distances[, dist])
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)))
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species_distances <- data.table(
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species = species_id,
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gene = species_distances[, geneid],
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distance = species_distances[, dist]
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)
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distances <- rbindlist(list(distances, species_distances))
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}
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# Order species by their median distance.
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setorder(species, median_distance)
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list(
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genes = genes,
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species = species,
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distances = distances
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)
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} |