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Phymm and PhymmBL: metagenomic phylogenetic classification with interpolated Markov models
Arthur Brady1, Steven L Salzberg
1Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, USA. abrady@umiacs.umd.edu
Nature Methods
|August 4, 2009
Summary
Phymm accurately classifies short DNA sequences from metagenomics projects, improving phylogenetic analysis. This new method enhances the study of biological diversity from environmental samples.
Area of Science:
- Bioinformatics
- Genomics
- Microbiology
Background:
- Metagenomics projects analyze DNA from diverse environments, posing challenges for phylogenetic classification.
- Accurate classification of short DNA reads is crucial for genome assembly and biodiversity analysis.
- Short reads from new sequencing technologies have limited classification accuracy.
Purpose of the Study:
- To develop an accurate classifier for short metagenomic sequence reads.
- To improve phylogenetic classification of environmental DNA samples.
- To enable accurate analysis of biological diversity from short sequencing reads.
Main Methods:
- Developed Phymm, a novel classifier trained on 539 curated genomes.
- Evaluated Phymm's performance on classifying short DNA reads (100 base pairs).
- Investigated the combined use of Phymm with sequence alignment algorithms.
Main Results:
- Phymm accurately classifies metagenomic reads as short as 100 base pairs.
- Achieved substantial improvement over existing composition-based classification methods.
- Combining Phymm with alignment algorithms further enhanced classification accuracy.
Conclusions:
- Phymm offers a significant advancement for metagenomic data analysis.
- Enables more reliable phylogenetic classification and biodiversity assessment from short reads.
- Facilitates the use of modern, high-throughput sequencing technologies in metagenomics.
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