enigmadatabase 0.1.1

NCBI DNA Database Builder and Dataset Loader for ML pipelines (Enigma2).

EnigmaDB

Dataset generation pipeline for Enigma2 using NCBI database. Along with additional helper such as Dataset class to retireve & create batches for training ML models.

Prerequisites

Before setting up EnigmaDB, ensure that you have the following prerequisites installed:

1. Python 3.8 or higher
2. pip (Python package installer)

Dependencies

• Biopython
• NumPy
• PyTorch
• Biosaic

Installation

1. From PyPI

pip install enigmadatabase

2. Clone the Repo

git clone https://github.com/delveopers/EnigmaDataset.git
cd EnigmaDB

Documentation & Usage

Data gathering pipeline

from EnigmaDB import Database, EntrezQueries
queries = EntrezQueries()   # get queries

db = Database(topics=queries(), out_dir="./data/raw", email=EMAIL, api_key=API_KEY, retmax=1500, max_rate=10)   # set parameters
db.build(with_index=False)  # startbuilding

Creating Indexes

from EnigmaDB import create_index

create_index("./data/raw")    # add path to data

Converting versions

from EnigmaDB import convert_fasta

convert_fasta(input_dir="./data/raw", output_dir="./data/parquet", mode='parquet')  # for parquet
convert_fasta(input_dir="./data/raw", output_dir="./data/parquet", mode='csv')  # for csv

for more technical information, refer to documentation:

1. Database.md
2. Dataset.md

Project Structure

├── docs/
├── ├── Database.md
├── ├── Dataset.md
├── src/
├── ├── __init__.py
├── ├── _database.py    # ``Database`` class for downloading data from NCBI
├── ├── _dataset.py     # ``Dataset`` a dataloader class for enigma2
├── ├── _queries.py     # contains queries for DB pipeline
├── README.md
├── setup.py
├── pyproject.toml
├── requirements.txt  # List of Python dependencies

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

1. Fork the repository.

2. Create a feature branch:

git checkout -b feature-name

3. Commit your changes:

git commit -m "Add feature"

4. Push to the branch:

 git push origin feature-name

5. Create a pull request.

Please make sure to update tests as appropriate.

License

MIT License. Check out License for more info.