protfetch 0.1.3

A tool to fetch and process protein FASTA sequences and metadata from NCBI based on a gene list.

protfetch

protfetch is a command-line tool designed to fetch and process protein FASTA sequences and associated metadata from NCBI's Entrez databases. Given a list of gene symbols (or protein names and gene symbols), it retrieves relevant protein sequences, filters them based on various criteria (identity, similarity, fragments), and outputs curated FASTA files and a metadata CSV.

Features

• Flexible Input: Accepts gene lists in two formats:

  • Protein Name | GENE_SYMBOL (e.g., "Mitofusin 1 | MFN1")
  • GENE_SYMBOL (e.g., "MFN1")

• NCBI Entrez Integration: Uses Biopython to query NCBI Entrez for gene UIDs, linked protein UIDs, and FASTA sequences.

• Keyword Filtering: Filters fetched protein sequences based on keywords derived from the input (protein name or gene symbol) found in FASTA headers. This step can be skipped.

• Sequence Processing & Filtering:

  • Parses complex FASTA headers to extract accession and other identifiers
  • Removes duplicate entries by accession (first seen is kept)
  • Filters out identical sequences (keeps one representative, typically by lexicographical accession)
  • Filters near-identical sequences using Levenshtein distance (configurable threshold)
  • Removes fragment sequences (shorter sequences that are substrings of longer ones)

• Concurrent Fetching: Utilizes multiple workers to fetch data for different genes concurrently, speeding up processing for large lists.

• Organized Output:

  • Generates combined FASTA files (short headers and full headers) and a combined metadata CSV file
  • Optionally saves processed files for each gene individually
  • Combined files are deduplicated to ensure unique protein entries

Installation

Prerequisites

• Python 3.8 or higher
• pip (Python package installer)

From PyPI (Recommended)

pip install protfetch

(Note: This command will work once the package is published to PyPI.)

From Source (for development)

1. Clone the repository:

git clone https://github.com/yourusername/protfetch.git  # Update with your repo URL
cd protfetch

2. Install in editable mode:

pip install -e .

Usage

protfetch <input_gene_list_file> [OPTIONS]

Required Arguments:

• input_gene_list_file: Path to the input file containing the list of genes.
  • Each line should be either Protein Name | GENE_SYMBOL or just GENE_SYMBOL
  • Lines starting with # are treated as comments and ignored

NCBI Configuration:

• --entrez-email YOUR_EMAIL: Strongly recommended. Your email address for NCBI Entrez. NCBI requires this for reliable access and to contact you if there are issues with your queries.
• --entrez-api-key YOUR_API_KEY: (Optional) Your NCBI API key for higher request rates.

Key Options:

• -o, --output-dir DIR: Directory to save output files (default: protfetch_results)
• --max-dist INT: Max Levenshtein distance for filtering near-identical sequences (default: 4; 0 to disable)
• --max-workers INT: Maximum number of concurrent workers for fetching data (default: 5)
• --save-individual-files: Save processed FASTA and CSV for each gene individually
• --skip-keyword-filter: Skip filtering FASTA sequences by keyword
• --timeout SECONDS: Timeout for NCBI requests (default: 60)
• --retries INT: Number of retries for NCBI requests (default: 3)
• --debug: Enable detailed debug logging
• -v, --version: Show program's version number and exit
• -h, --help: Show help message and exit

Example:

Create a sample gene list file (e.g., genes.txt):

# Mitofusin 1 | MFN1
# Calreticulin | CALR
# CANX
# PDIA3

Run protfetch:

protfetch genes.txt --entrez-email [e-mail] -o my_protein_data --save-individual-files

This command will:

1. Read genes.txt
2. Fetch data for MFN1, CALR, CANX, and PDIA3 from NCBI
3. Filter and process the sequences
4. Save combined results (e.g., genes_combo_short.fasta, genes_combo_full.fasta, genes_combo_meta.csv) in the my_protein_data directory
5. Save individual files for each gene in my_protein_data/individual_gene_files/

Output Files

In the specified output directory:

• {input_file_stem}_combo_short.fasta: Combined FASTA file with short headers (e.g., >ACCESSION), deduplicated by accession
• {input_file_stem}_combo_full.fasta: Combined FASTA file with full original headers, deduplicated by full header
• {input_file_stem}_combo_meta.csv: Combined metadata CSV file (accession, gene_input, identifier_from_header), deduplicated by accession

If --save-individual-files is used, a subdirectory (default: individual_gene_files) will contain:

• {GENE_SYMBOL}_filtered_short.fasta
• {GENE_SYMBOL}_filtered_full.fasta
• {GENE_SYMBOL}_filtered_meta.csv

License

This project is licensed under the MIT License - see the LICENSE file for details.