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Rapid denoising of pyrosequencing amplicon data: exploiting the rank-abundance distribution
We developed a fast method for denoising pyrosequencing for community 16S rRNA analysis. We observe a 2–4 fold reduction in the number of observed OTUs (operational taxonomic units) comparing denoised with non-denoised data. ~50,000 sequences can be denoised on a laptop within an hour, two orders of...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2945879/ https://www.ncbi.nlm.nih.gov/pubmed/20805793 http://dx.doi.org/10.1038/nmeth0910-668b |
Sumario: | We developed a fast method for denoising pyrosequencing for community 16S rRNA analysis. We observe a 2–4 fold reduction in the number of observed OTUs (operational taxonomic units) comparing denoised with non-denoised data. ~50,000 sequences can be denoised on a laptop within an hour, two orders of magnitude faster than published techniques. We demonstrate the effects of denoising on alpha and beta diversity of large 16S rRNA datasets. |
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