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4dec2061fc
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coolneng | 4dec2061fc |
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@ -1,2 +1 @@
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*.fasta
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*.fastq
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*.fastq
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@ -11,14 +11,11 @@ fi
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sequences=$1
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sequences=$1
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number_of_reads=$2
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number_of_reads=$2
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read_mean_size=350
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read_variance_size=0.0
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data_directory="data/"
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data_directory="data/"
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fasta=".fasta"
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fastq=".fastq"
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fastq=".fastq"
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filename="sequence"
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filename="sequence"
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prefix="curesim_"
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prefix="curesim_"
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Rscript src/repertoire.r "$sequences" &&
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Rscript src/repertoire.r "$sequences" "$number_of_reads" &&
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java -jar tools/CuReSim.jar -n $((number_of_reads * sequences)) -m "$read_mean_size" -sd "$read_variance_size" -f "$data_directory$filename$fasta" -o "$data_directory$prefix$filename$fastq"
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java -jar tools/CuReSim.jar -f "$data_directory$filename$fastq" -o "$data_directory$prefix$filename$fastq"
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rm "$data_directory/log.txt"
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rm "$data_directory/log.txt"
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@ -55,7 +55,6 @@ get_hvr_sequences <- function(sequences, vdj_segments) {
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df <- fetch_vj_sequences(sequences, vdj_segments)
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df <- fetch_vj_sequences(sequences, vdj_segments)
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v_alignment <- parallel::mcmapply(sequences, df$v_seq, FUN = align_sequence)
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v_alignment <- parallel::mcmapply(sequences, df$v_seq, FUN = align_sequence)
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j_alignment <- parallel::mcmapply(sequences, df$j_seq, FUN = align_sequence)
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j_alignment <- parallel::mcmapply(sequences, df$j_seq, FUN = align_sequence)
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print(v_alignment)
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}
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}
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data <- parse_data(file = "data/curesim_sequence.fastq")
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data <- parse_data(file = "data/curesim_sequence.fastq")
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@ -11,26 +11,32 @@ generate_repertoire <- function(number_of_sequences) {
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}
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}
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save_data <- function(data) {
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save_data <- function(data) {
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Biostrings::writeXStringSet(data$sequence, "data/sequence.fasta")
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Biostrings::writeXStringSet(data$sequence,
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Biostrings::writeXStringSet(data$junction, "data/HVR.fasta")
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"data/sequence.fastq",
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format = "fastq"
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)
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Biostrings::writeXStringSet(data$junction, "data/HVR.fastq", format = "fastq")
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}
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}
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process_data <- function(data) {
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process_data <- function(data, reads) {
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dna_sequence <- Biostrings::DNAStringSet(data$sequence)
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dna_sequence <- Biostrings::DNAStringSet(data$sequence)
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data$sequence <- Biostrings::reverseComplement(dna_sequence)
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data$sequence <- Biostrings::reverseComplement(dna_sequence)
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names(data$sequence) <- paste(rownames(data), data$v_call, data$j_call, " ")
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names(data$sequence) <- paste(rownames(data), data$v_call, data$j_call, " ")
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return(data)
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data$junction <- Biostrings::DNAStringSet(data$junction)
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names(data$junction) <- rownames(data)
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amplified_data <- data[rep(seq_len(nrow(data)), reads), ]
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return(amplified_data)
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}
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}
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parse_cli_arguments <- function() {
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parse_cli_arguments <- function() {
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args <- commandArgs(trailingOnly = TRUE)
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args <- commandArgs(trailingOnly = TRUE)
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if (length(args) != 1) {
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if (length(args) != 2) {
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stop("usage: repertoire.r <number of sequences>")
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stop("usage: repertoire.r <number of sequences> <number of reads>")
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}
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}
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return(args[1])
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return(args)
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}
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}
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argument <- parse_cli_arguments()
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args <- parse_cli_arguments()
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repertoire <- generate_repertoire(number_of_sequences = as.integer(argument))
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repertoire <- generate_repertoire(number_of_sequences = as.integer(args[1]))
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data <- process_data(data = repertoire)
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data <- process_data(data = repertoire, reads = args[2])
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save_data(data)
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save_data(data)
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