This project explores lossless data compression techniques applied to DNA sequence data using two well-known algorithms: Lempel-Ziv-Welch (LZW) and Huffman Coding. The goal is to compare their performance in terms of compression efficiency for biological sequence data.
DNA sequencing generates massive amounts of data, posing challenges in storage and management. Efficient compression methods are essential to reduce storage costs and improve data handling.
- LZW is widely used in GIFs, PDFs, and UNIX compression utilities.
- Huffman Coding is commonly applied in text compression by assigning shorter codes to frequently used characters.
This project implements and compares both algorithms on DNA sequences.
- Implement LZW and Huffman Coding algorithms in MATLAB.
- Compare their performance in compressing DNA sequence data.
- Analyze which algorithm provides better efficiency for genomic information.
- Platform: MATLAB IDE
- Input: DNA sequence of 100 nucleotides (A, G, C, T)
- Approach:
- Manual computation of both algorithms.
- MATLAB simulation of compression.
- Comparison of compression ratios and code efficiency.
- LZW achieved a compression ratio of ~1.96.
- Huffman Coding achieved a code efficiency of ~99.04% with fewer bits required.
- Conclusion: Huffman Coding is more efficient for DNA sequence compression in this test case.
- Miro Manuel L. Hernandez – miro_hernandez@dlsu.edu.ph
- Matthew R. Orga
- Dominic P. Yu
De La Salle University – Manila, Department of Electronics and Computer Engineering
This project is based on research regarding data compression techniques for DNA sequences. See full references in the Final Project Report.