Convert org mode README to markdown

README.md

@@ -22,25 +22,25 @@ builds.
 1.  Install Nix (compatible with MacOS, Linux and
     [WSL](https://docs.microsoft.com/en-us/windows/wsl/about)):
 
-```bash
+``` {.shell}
 curl -L https://nixos.org/nix/install | sh
 ```
 
 2.  Clone the repository:
 
-```bash
+``` {.shell}
 git clone https://git.coolneng.duckdns.org/coolneng/locigenesis
 ```
 
 3.  Change the working directory to the project:
 
-```bash
+``` {.shell}
 cd locigenesis
 ```
 
 4.  Enter the nix-shell:
 
-```bash
+``` {.shell}
 nix-shell
 ```
 
@@ -52,7 +52,7 @@ contains all the needed dependencies.
 An execution script that accepts 2 parameters is provided, the following
 command invokes it:
 
-```bash
+``` {.shell}
 ./generation.sh <number of sequences> <number of reads>
 ```
 
@@ -63,6 +63,7 @@ command invokes it:
 
 The script will generate 2 files under the data directory:
 
-|HVR.fastq  | curesim-HVR.fastq |
-|:----:|:-----:|
-|Contains the original CDR3 sequence|Contains CDR3 after the read simulation, with sequencing errors |
+  ------------------- -----------------------------------------------------------------
+  HVR.fastq           Contains the original CDR3 sequence
+  CuReSim-HVR.fastq   Contains CDR3 after the read simulation, with sequencing errors
+  ------------------- -----------------------------------------------------------------

src/alignment.r

@@ -34,11 +34,7 @@ parse_metadata <- function(metadata) {
 #' @return A \code{character} containing the gene sequence
 match_id_sequence <- function(names, vdj_segments, id) {
   matches <- grep(names, pattern = id)
-  if(id == "TRBJ2-2"){
-    row <- matches[2]
-  } else {
-    row <- matches[1]
-  }
+  row <- matches[1]
   return(as.character(vdj_segments[row]))
 }
 
@@ -110,9 +106,8 @@ get_cys_coordinates <- function(alignment) {
   insertion <- unlist(Biostrings::insertion(alignment))
   deletion <- unlist(Biostrings::deletion(alignment))
   delta_coordinates <- handle_indels(insertion, deletion, cys, alignment)
-  read_start <- unlist(start(Biostrings::Views(alignment)))
-  cys_start <- cys$start + delta_coordinates$start + read_start - 1
-  cys_end <- cys$end + delta_coordinates$end + read_start
+  cys_start <- cys$start + delta_coordinates$start
+  cys_end <- cys$end + delta_coordinates$end
   return(list("start" = cys_start, "end" = cys_end))
 }
 
@@ -131,7 +126,7 @@ get_hvr_sequences <- function(sequences, vdj_segments, cores = detectCores()) {
   )
   cys_coordinates <- parallel::mclapply(v_alignment, FUN = get_cys_coordinates)
   cys_df <- as.data.frame(do.call(rbind, cys_coordinates))
-  remaining <- Biostrings::subseq(sequences, start = unlist(cys_df$end) + 1)
+  remaining <- Biostrings::subseq(sequences, start = unlist(cys_df$end))
   j_alignment <- parallel::mcmapply(remaining,
     df$j_seq,
     FUN = align_sequence,
@@ -150,4 +145,4 @@ get_hvr_sequences <- function(sequences, vdj_segments, cores = detectCores()) {
 
 data <- parse_data(file = "data/curesim_sequence.fastq")
 hvr <- get_hvr_sequences(sequences = data[[1]], vdj_segments = data[[2]])
-Biostrings::writeXStringSet(hvr, "data/curesim-HVR.fastq", format = "fastq")
+Biostrings::writeXStringSet(hvr, "data/CuReSim-HVR.fastq", format = "fastq")