Using Chaos Game Representation to Compare Genomes
Author Information
Author(s): Joseph Jijoy, Sasikumar Roschen
Primary Institution: Computational Modelling and Simulation, Regional Research Laboratory (CSIR), Thiruvananthapuram, India
Hypothesis
Can chaos game representation (CGR) be effectively used for alignment-based comparisons of whole genome sequences?
Conclusion
The study introduces a fast algorithm that enhances CGR's capability for large-scale sequence alignment, making it a powerful tool for genome analysis.
Supporting Evidence
- The algorithm identifies local alignments based on the distance between CGR points.
- It allows for mismatches by chaining together close local alignments.
- The method can detect homologous segments and internal sequence duplications.
Takeaway
This study shows a new way to compare DNA sequences quickly using a special method called chaos game representation, which helps scientists see how similar or different two genomes are.
Methodology
The study developed an algorithm that uses CGR points to identify local alignments between long DNA sequences, speeding up the comparison process.
Limitations
The current implementation does not significantly improve speed over existing tools like MUMmer, and further optimization is needed.
Digital Object Identifier (DOI)
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