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Alignment-free analysis of barcode sequences by means of compression-based methods
Massimo La Rosa1, Antonino Fiannaca, Riccardo Rizzo
1ICAR-CNR, National Research Council of Italy, Viale delle Scienze Ed. 11, 90128, Palermo, Italy. larosa@pa.icar.cnr.it
BMC Bioinformatics
|July 3, 2013
Summary
This study introduces an alignment-free method using compression-based Universal Similarity Metric (USM) for DNA barcode analysis. The new approach reliably extracts taxonomic information from short animal DNA barcode sequences.
Area of Science:
- Bioinformatics
- Genomics
- Taxonomy
Background:
- DNA barcoding uses short DNA sequences for species identification.
- The mitochondrial gene cytochrome c oxidase I (COI) is a common animal barcode.
- Integrating barcode data with other information enhances taxonomic consistency.
Purpose of the Study:
- To introduce an alignment-free approach for DNA barcode taxonomic analysis.
- To demonstrate the utility of compression-based Universal Similarity Metric (USM) for short barcode sequences.
- To show USM's capability in extracting taxonomic information from DNA barcodes.
Main Methods:
- Utilized two compression-based versions of the Universal Similarity Metric (USM).
- Analyzed 30 animal barcode sequence datasets from the Barcode of Life Data System (BOLD).
- Compared topology preservation between compression-based and classic evolutionary phylogenetic tree methods.
Main Results:
- Achieved 80%-100% similarity scores between evolutionary and compression-based trees for most datasets (94%).
- Experimental tests on simulated barcode datasets yielded mean similarity scores of 83%-99%.
- Demonstrated high similarity between tree types across various dataset sizes.
Conclusions:
- Compression-based methods are reliable for analyzing short DNA barcode sequences.
- Universal Similarity Metric (USM) effectively extracts taxonomic information.
- Compression-based methods offer a valid alignment-free and parameter-free approach for barcode studies.
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