FastA_algorithm

This project is a simplified implementation of the FastA algorithm, designed to compare a query DNA sequence against the complete set of coding (gene) sequences of Saccharomyces cerevisiae (baker's yeast). The purpose is to identify significant matches based on word-level similarity using a lightweight scoring system and filtering criteria.

Objective

To simulate a basic version of the FastA sequence alignment algorithm with the following parameters:

• Scoring Scheme: +1 for each exact word match (5-mer), 0 for mismatches

• Word size/ k-mer size (k): 5

• Minimum matched diagonal size (m): 20

• Maximum gap allowed when joining regions (g): 3

• Threshold for total score: 50% of the query sequence length

• Outputs:

  • Identification of the best matching sequence based on the matching highest score

  • Identification of the best matching gene based on the highest score

  • Highest matching score

Data format

• Query sequence: single-sequence FASTA file

• Gene sequences (S. cerevisiae): multi- FASTA file