Document the alignment script

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coolneng 2021-05-04 19:25:11 +02:00
parent f4b7a41599
commit e8f03189c2
Signed by: coolneng
GPG Key ID: 9893DA236405AF57
1 changed files with 47 additions and 0 deletions

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@ -1,6 +1,10 @@
library(Biostrings) library(Biostrings)
library(parallel) library(parallel)
#' Import and process the TCR and VJ sequences
#'
#' @param file A file path with the sequences after applying a read simulator
#' @return A \code{list} with the TCR sequences and VJ sequences
parse_data <- function(file) { parse_data <- function(file) {
reversed_sequences <- Biostrings::readQualityScaledDNAStringSet(file) reversed_sequences <- Biostrings::readQualityScaledDNAStringSet(file)
sequences <- Biostrings::reverseComplement(reversed_sequences) sequences <- Biostrings::reverseComplement(reversed_sequences)
@ -11,6 +15,10 @@ parse_data <- function(file) {
return(list(sequences, vj_segments)) return(list(sequences, vj_segments))
} }
#' Extracts the VJ metadata from the sequences read identifier
#'
#' @param metadata The read identifier of a sequence
#' @return A \code{list} with the V and J gene identifier
parse_metadata <- function(metadata) { parse_metadata <- function(metadata) {
id_elements <- unlist(strsplit(metadata, split = " ")) id_elements <- unlist(strsplit(metadata, split = " "))
v_identifier <- id_elements[2] v_identifier <- id_elements[2]
@ -18,12 +26,24 @@ parse_metadata <- function(metadata) {
return(list(v_id = v_identifier, j_id = j_identifier)) return(list(v_id = v_identifier, j_id = j_identifier))
} }
#' Fetches the sequence that matches the VJ gene identifier
#'
#' @param names The names of the VJ sequences
#' @param vdj_segments A \code{DNAStringSet} containing the VJ sequences
#' @param id The read identifier of a sequence
#' @return A \code{character} containing the gene sequence
match_id_sequence <- function(names, vdj_segments, id) { match_id_sequence <- function(names, vdj_segments, id) {
matches <- grep(names, pattern = id) matches <- grep(names, pattern = id)
row <- matches[1] row <- matches[1]
return(as.character(vdj_segments[row])) return(as.character(vdj_segments[row]))
} }
#' Gets the V and J sequences for a particular read identifier
#'
#' @param metadata The read identifier of a sequence
#' @param names The names of the VJ sequences
#' @param vdj_segments A \code{DNAStringSet} containing the VJ sequences
#' @return A \code{list} with the V and J sequences
get_vj_sequence <- function(metadata, names, vdj_segments) { get_vj_sequence <- function(metadata, names, vdj_segments) {
identifiers <- parse_metadata(metadata) identifiers <- parse_metadata(metadata)
v_sequence <- match_id_sequence(names, vdj_segments, id = identifiers["v_id"]) v_sequence <- match_id_sequence(names, vdj_segments, id = identifiers["v_id"])
@ -31,6 +51,11 @@ get_vj_sequence <- function(metadata, names, vdj_segments) {
return(list(v_seq = v_sequence, j_seq = j_sequence)) return(list(v_seq = v_sequence, j_seq = j_sequence))
} }
#' Obtains the VJ sequences for all the TCR sequences
#'
#' @param sequences A \code{QualityScaledDNAStringSet} with the TCR sequences
#' @param vdj_segments A \code{DNAStringSet} containing the VJ sequences
#' @return A \code{data.frame} with the V and J sequences
fetch_vj_sequences <- function(sequences, vdj_segments) { fetch_vj_sequences <- function(sequences, vdj_segments) {
vj_sequences <- sapply(names(sequences), vj_sequences <- sapply(names(sequences),
names(vdj_segments), names(vdj_segments),
@ -41,6 +66,11 @@ fetch_vj_sequences <- function(sequences, vdj_segments) {
return(results) return(results)
} }
#' Perform a pairwise alignment of a sequence with the canonical V or J sequence
#'
#' @param sequence A \code{DNAString} containing the TCR sequences
#' @param vdj_segment A \code{DNAString} containing the V or J sequence
#' @return A \code{PairwiseAlignments}
align_sequence <- function(sequence, vdj_segment) { align_sequence <- function(sequence, vdj_segment) {
return(Biostrings::pairwiseAlignment( return(Biostrings::pairwiseAlignment(
subject = sequence, subject = sequence,
@ -50,6 +80,13 @@ align_sequence <- function(sequence, vdj_segment) {
)) ))
} }
#' Computes the coordinate shift of the Cysteine due to indels
#'
#' @param insertion An \code{IRanges} containing the insertions
#' @param deletion An \code{IRanges} containing the deletions
#' @param cys A \code{list} with the Cysteine coordinates
#' @param alignment A \code{PairwiseAlignments}
#' @return A \code{list} with the delta of the Cysteine coordinates
handle_indels <- function(insertion, deletion, cys, alignment) { handle_indels <- function(insertion, deletion, cys, alignment) {
ins_start <- sum(Biostrings::width(deletion[start(deletion) <= cys$start])) ins_start <- sum(Biostrings::width(deletion[start(deletion) <= cys$start]))
ins_end <- sum(Biostrings::width(deletion[end(deletion) <= cys$end])) ins_end <- sum(Biostrings::width(deletion[end(deletion) <= cys$end]))
@ -60,6 +97,10 @@ handle_indels <- function(insertion, deletion, cys, alignment) {
return(list("start" = ins_start - gaps, "end" = ins_end - gaps)) return(list("start" = ins_start - gaps, "end" = ins_end - gaps))
} }
#' Find the coordinates of the first Cysteine of the HVR
#'
#' @param alignment A \code{PairwiseAlignments}
#' @return A \code{list} with the Cysteine coordinates
get_cys_coordinates <- function(alignment) { get_cys_coordinates <- function(alignment) {
cys <- list("start" = 310, "end" = 312) cys <- list("start" = 310, "end" = 312)
insertion <- unlist(Biostrings::insertion(alignment)) insertion <- unlist(Biostrings::insertion(alignment))
@ -70,6 +111,12 @@ get_cys_coordinates <- function(alignment) {
return(list("start" = cys_start, "end" = cys_end)) return(list("start" = cys_start, "end" = cys_end))
} }
#' Delimit the hypervariable region (HVR) for each TCR sequence
#'
#' @param sequences A \code{QualityScaledDNAStringSet} with the TCR sequences
#' @param vdj_segments A \code{DNAStringSet} containing the VJ sequences
#' @param cores Number of cores to apply multiprocessing
#' @return A \code{QualityScaledDNAStringSet} containing the HVR
get_hvr_sequences <- function(sequences, vdj_segments, cores = detectCores()) { get_hvr_sequences <- function(sequences, vdj_segments, cores = detectCores()) {
df <- fetch_vj_sequences(sequences, vdj_segments) df <- fetch_vj_sequences(sequences, vdj_segments)
v_alignment <- parallel::mcmapply(sequences, v_alignment <- parallel::mcmapply(sequences,