53 lines
1.4 KiB
R
53 lines
1.4 KiB
R
library(immuneSIM)
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library(Biostrings)
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generate_repertoire <- function(number_of_sequences) {
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return(immuneSIM(
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number_of_seqs = number_of_sequences,
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species = "hs",
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receptor = "tr",
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chain = "b"
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))
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}
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amplify_rows <- function(data, column, factor) {
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if (column == "sequence") {
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dna_string <- Biostrings::DNAStringSet(data)
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reverse_complement <- Biostrings::reverseComplement(dna_string)
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return(rep(reverse_complement, factor))
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}
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return(rep(data, factor))
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}
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save_data <- function(data) {
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Biostrings::writeXStringSet(data$sequence, "data/sequence.fasta")
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vdj_sequences <- data[-1]
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write.csv(vdj_sequences, "data/vdj_alignment.csv", row.names = FALSE)
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}
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process_data <- function(repertoire, sequencing_runs) {
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columns <- c(
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"sequence", "v_sequence_alignment",
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"d_sequence_alignment", "j_sequence_alignment"
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)
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data <- repertoire[, columns]
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amplified_data <- mapply(data, names(data),
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sequencing_runs,
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FUN = amplify_rows
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)
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save_data(amplified_data)
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}
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parse_cli_arguments <- function(args) {
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if (length(args) != 2) {
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stop("usage: repertoire.r <number of sequences> <sequencing_runs>")
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}
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return(c(args[1], args[2]))
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}
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args <- commandArgs(trailingOnly = TRUE)
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arguments <- parse_cli_arguments(args)
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number_of_sequences <- as.integer(arguments[1])
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sequencing_runs <- as.integer(arguments[2])
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repertoire <- generate_repertoire(number_of_sequences)
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process_data(repertoire, sequencing_runs) |