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26 lines
1.3 KiB
Text
26 lines
1.3 KiB
Text
WEVOTE (WEighted VOting Taxonomic idEntification)
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WEVOTE is a method that classifies metagenome shotgun sequencing DNA
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reads based on an ensemble of existing methods using k-mer based,
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marker-based, and naive-similarity based approaches. The performance
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evaluation based on fourteen simulated microbiome datasets
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consistently demonstrates that WEVOTE achieves a high level of
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sensitivity and precision compared to the individual methods across
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different taxonomic levels. The major advantage of the WEVOTE pipeline
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is that the user can make the choice of which tools to use in order to
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explore the trade-off between sensitivity, precision, time and memory.
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The WEVOTE architecture is flexible so that additional taxonomic tools
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can be easily added, or the current tools can be replaced by improved
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ones. Moreover, the score assigned to the taxon for each read
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indicates the confidence level of the assignment. This information is
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especially useful for the assessment of false positive annotations at
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a particular taxonomic level. The classification score given by WEVOTE
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can be used for any downstream analysis that requires the high
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confidence of the annotated sequences.
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Publication:
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Ahmed A. Metwally, Yang Dai, Patricia W. Finn, and David L. Perkins.
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WEVOTE: Weighted Voting Taxonomic Identification Method of Microbial
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Sequences.
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PloS ONE, 2016.
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