Consistency of metagenomic assignment programs in simulated and real data
[Backgroun] Metagenomics is the genomic study of uncultured environmental samples, which has been greatly facilitated by the advent of shotgun-sequencing technologies. One of the main focuses of metagenomics is the discovery of previously uncultured microorganisms, which makes the assignment of sequences to a particular taxon a challenge and a crucial step. Recently, several methods have been developed to perform this task, based on different methodologies such as sequence composition or sequence similarity. The sequence composition methods have the ability to completely assign the whole dataset. However, their use in metagenomics and the study of their performance with real data is limited. In this work, we assess the consistency of three different methods (BLAST + Lowest Common Ancestor, Phymm, and Naïve Bayesian Classifier) in assigning real and simulated sequence reads.
| Main Authors: | , , |
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| Format: | artículo biblioteca |
| Published: |
BioMed Central
2014-03-28
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| Online Access: | http://hdl.handle.net/10261/95685 http://dx.doi.org/10.13039/501100004837 |
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