Gene Feature Extraction and Keyword Analysis

This repository contains Python functions for extracting gene features from a GFF3 file and performing keyword analysis using TF-IDF (Term Frequency-Inverse Document Frequency).

Functions

Extraction.py:

This file contains methods required to extract information from the genome and descriptions of organisms.

extract_keywords(text: str) -> set

Returns important keywords from a given text using TF-IDF. The function tokenizes the text, removes stopwords, and computes the TF-IDF scores. It then selects the top N words as keywords.

Args:

• text (str): The input text from which keywords are drawn.

Returns:

• extraction (set): A set of important keywords.

extract_gene_features(gff_file: str, output_filename: str) -> None

Extracts gene features from a GFF3 file and writes them to a new file.

Args:

• gff_file (str): Path to the GFF3 file.
• output_filename (str): Path to the output file.

extract_gene_info(gff_file: str, output_filename: str) -> None

Extracts gene IDs and descriptions from a GFF3 file and writes them to a new file.

Args:

• gff_file (str): Path to the GFF3 file.
• output_filename (str): Path to the output file.

Read.py

This file contains a method to read descriptions of genes and return ones that match to generated keywords.

read_descriptions(fp: str, kwords: set) -> set

Finds matching gene IDs and descriptions based on provided keywords.

Args:

• fp (str): The filepath to the gene descriptions text file.
• kwords (set): A set of keywords to search for.

Returns:

• matching_descriptions (set): A set of tuples containing matching gene IDs, descriptions, and keywords.