Rapidly denoising pyrosequencing amplicon reads by exploiting rank-abundance distributions
University of Colorado Boulder · Howard Hughes Medical Institute
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Abstract
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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Authors
2Topics & keywords
Topics
Keywords
- Pyrosequencing
- Amplicon
- Computational biology
- Biology
- Rank (graph theory)
- Abundance (ecology)
- Computer science
- Genetics
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