Align full sequences efficiently

src/alignment.r

@@ -1,14 +1,14 @@
 library(Biostrings)
 library(parallel)
 
-construct_dataframe <- function(data) {
-  vdj_string_set <- lapply(data, FUN = Biostrings::DNAStringSet)
-  vdj_dataframe <- as.data.frame(vdj_string_set)
-  vdj_dataframe$hvr_region <- paste(vdj_dataframe$v_sequence,
+construct_hvr_sequence <- function(data) {
+  vdj_dataframe <- as.data.frame(data)
+  hvr_sequence <- paste(vdj_dataframe$v_sequence,
     vdj_dataframe$d_sequence,
     vdj_dataframe$j_sequence,
     sep = ""
   )
+  vdj_dataframe$hvr <- hvr_sequence
   return(vdj_dataframe)
 }
 
@@ -16,8 +16,33 @@ parse_data <- function(files) {
   reversed_sequences <- Biostrings::readQualityScaledDNAStringSet(files[1])
   sequences <- Biostrings::reverseComplement(reversed_sequences)
   vdj_alignment <- read.csv(files[2])
-  vdj_dataframe <- construct_dataframe(vdj_alignment)
-  return(list(sequences, vdj_dataframe))
+  vdj_dataframe <- construct_hvr_sequence(vdj_alignment)
+  vj_segments <- union(
+    readRDS("data/v_segments.rds"),
+    readRDS("data/j_segments_phe.rds")
+  )
+  return(list(sequences, vj_segments, vdj_dataframe))
+}
+
+# TODO Test if grep can return more than one match
+get_vj_sequence <- function(identifier, names, sequences) {
+  row <- grep(names, pattern = identifier)
+  return(as.character(sequences[row]))
+}
+
+construct_full_sequences <- function(vdj_segments, metadata) {
+  v_sequences <- lapply(metadata$v_call,
+    names(vdj_segments),
+    vdj_segments,
+    FUN = get_vj_sequence
+  )
+  j_sequences <- lapply(metadata$j_call,
+    names(vdj_segments),
+    vdj_segments,
+    FUN = get_vj_sequence
+  )
+  full_sequence <- paste(v_sequences, metadata$hvr, j_sequences, sep = "")
+  return(Biostrings::DNAStringSet(full_sequence))
 }
 
 align_sequence <- function(sequence, vdj_segment) {
@@ -25,20 +50,25 @@ align_sequence <- function(sequence, vdj_segment) {
     pattern = sequence,
     subject = vdj_segment,
     type = "global-local",
-    gapOpening = 1
+    gapOpening = 1,
   ))
 }
 
-perform_alignment <- function(sequences, vdj_segments) {
-  sequence_alignment <- mcmapply(sequences,
-    vdj_segments$hvr_region,
+perform_alignment <- function(sequences, vdj_segments, metadata) {
+  vj_sequences <- construct_full_sequences(vdj_segments, metadata)
+  sequence_alignment <- mcmapply(vj_sequences,
+    vdj_segments,
     FUN = align_sequence,
-    mc.cores = 4
+    mc.cores = detectCores()
   )
   return(sequence_alignment)
 }
 
 input_files <- c("data/curesim_sequence.fastq", "data/vdj_alignment.csv")
 data <- parse_data(input_files)
-alignment <- perform_alignment(sequences = data[[1]], vdj_segments = data[[2]])
+alignment <- perform_alignment(
+  sequences = data[[1]],
+  vdj_segments = data[[2]],
+  metadata = data[[3]]
+)
 print(alignment)

src/repertoire.r

@@ -20,7 +20,8 @@ save_data <- function(data, reads) {
 process_data <- function(repertoire, reads) {
   columns <- c(
     "sequence", "v_sequence_alignment",
-    "d_sequence_alignment", "j_sequence_alignment"
+    "d_sequence_alignment", "j_sequence_alignment",
+    "v_call", "j_call"
   )
   data <- repertoire[, columns]
   dna_sequence <- Biostrings::DNAStringSet(data$sequence)