.gitignore

@@ -1,2 +0,0 @@
-*.html
-data/multiqc_data

README.org

@@ -1,59 +0,0 @@
-* Adapter parser
-
-This tool parses fastqc reports to extract the adapter sequences, from the *Overrepresented sequences*, and then outputs them to a text file. It also outputs the mean and standard deviation of the sequences length.
-
-** Technologies
-
-- Pandas
-
-** Installation
-
-This project uses [[https://nixos.org][Nix]] to ensure reproducible
-builds.
-
-1.  Install Nix (compatible with MacOS, Linux and
-    [[https://docs.microsoft.com/en-us/windows/wsl/about][WSL]]):
-
-#+begin_src bash
-curl -L https://nixos.org/nix/install | sh
-#+end_src
-
-2.  Clone the repository:
-
-#+begin_src bash
-git clone https://git.coolneng.duckdns.org/coolneng/adapter-parser
-#+end_src
-
-3.  Change the working directory to the project:
-
-#+begin_src bash
-cd adapter-parser
-#+end_src
-
-4.  Enter the nix-shell:
-
-#+begin_src bash
-nix-shell
-#+end_src
-
-After running these commands, you will find yourself in a shell that
-contains all the needed dependencies.
-
-** Usage
-
-The program expects a folder containing the fastqc reports as an input and an output file where to store the sequences in the FASTA format.
-
-#+begin_src bash
-python src/parser.py <input> <output>
-#+end_src
-
-#+RESULTS:
-:
-: usage: parser.py [-h] input output
-:
-: positional arguments:
-:   input       directory containing the fastqc reports
-:   output      file where to export the sequences
-:
-: optional arguments:
-:   -h, --help  show this help message and exit

parser.py

@@ -1,80 +0,0 @@
-from argparse import ArgumentParser
-from glob import glob
-from typing import List, Tuple
-from re import sub
-
-from pandas import DataFrame, read_html, Series
-
-
-def remove_parenthesis(identifier):
-    """
-    Remove parenthesis from the sequence identifier
-    """
-    sequence_str = "".join(map(str, identifier))
-    return sub(r"[()]", "", sequence_str)
-
-
-def extract_adapters(files) -> Tuple[Series, List]:
-    """
-    Extract the adapters sequences and statistics from the files
-    """
-    all_adapters = DataFrame()
-    for entry in files:
-        tables = read_html(entry)
-        if len(tables) > 1:
-            adapter_sequences = tables[1].Sequence
-            all_adapters = all_adapters.append(adapter_sequences)
-    processed_adapters = preprocess_dataframe(all_adapters)
-    stats = [
-        processed_adapters.str.len().mean(),
-        processed_adapters.str.len().std(),
-    ]
-    return processed_adapters, stats
-
-
-def preprocess_dataframe(adapters) -> Series:
-    """
-    Remove empty sequences and duplicates
-    """
-    na_free_adapters = adapters.dropna(axis=1)
-    stacked_adapters = na_free_adapters.stack()
-    duplicate_free_adapters = stacked_adapters.drop_duplicates()
-    return duplicate_free_adapters
-
-
-def save_to_file(filename, adapters) -> None:
-    """
-    Save the adapter sequences as a FASTA file
-    """
-    with open(filename, "w") as f:
-        for index, value in adapters.iteritems():
-            sequence_id = remove_parenthesis(index)
-            fasta_entry = f">{sequence_id}\n{value}\n"
-            f.write(fasta_entry)
-
-
-def parse_arguments():
-    """
-    Parse the command-line arguments
-    """
-    parser = ArgumentParser()
-    parser.add_argument("input", help="directory containing the fastqc reports")
-    parser.add_argument("output", help="file where to export the sequences")
-    return parser.parse_args()
-
-
-def main():
-    """
-    Extract the adapters from FASTQC reports to a FASTA file and show sequence length statistics
-    """
-    args = parse_arguments()
-    file_list = glob(args.input + "/*fastqc.html")
-    adapters, stats = extract_adapters(file_list)
-    save_to_file(args.output, adapters)
-    print(
-        f"Mean of sequence length: {stats[0]}, standard deviation of sequence length {stats[1]}"
-    )
-
-
-if __name__ == "__main__":
-    main()

shell.nix

@@ -2,4 +2,4 @@
 
 with pkgs;
 
-mkShell { buildInputs = [ python39 python39Packages.pandas ]; }
+mkShell { buildInputs = [ python39 python39Packages.beautifulsoup4 ]; }