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cBar: a computer program to distinguish plasmid-derived from chromosome-derived sequence fragments in metagenomics
1Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602, USA.
Bioinformatics (Oxford, England)
|June 12, 2010
Summary
Metagenomic data contains both chromosomal and plasmid DNA. A new program, cBar, effectively distinguishes these sequences using pentamer frequencies, improving genomic analysis accuracy.
Area of Science:
- Microbiology
- Bioinformatics
- Genomics
Background:
- Metagenomic studies generate vast amounts of sequence data from microbial communities.
- Sequenced metagenomes are complex mixtures of chromosomal and plasmid DNA from various organisms.
- Distinguishing between chromosomal and plasmid sequences is crucial for accurate gene prediction.
Purpose of the Study:
- To develop a computational method for classifying metagenomic sequences into chromosomal and plasmid origins.
- To address the challenge of analyzing mixed sequence data in metagenomics.
Main Methods:
- Developed a program named cBar for sequence classification.
- Utilized distinguishing pentamer frequencies as the basis for classification.
- Trained the program on a large dataset of sequenced prokaryotic chromosomes and plasmids.
Main Results:
- Achieved approximately 92% classification accuracy on a large training set.
- Demonstrated classification accuracy ranging from 64.45% to 88.75% on simulated metagenomes.
- Attained 88.29% classification accuracy on a large independent test set.
Conclusions:
- The cBar program effectively classifies metagenomic sequences into chromosomal and plasmid origins.
- Pentamer frequency analysis provides a robust method for distinguishing sequence types.
- This classification is essential for improving downstream computational analyses of metagenomic data.
