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DADA2: High resolution sample inference from amplicon data

Benjamin J Callahan, Paul J McMurdie, Michael J Rosen, Andrew W Han, Amy Jo Johnson, Susan P Holmes
doi: https://doi.org/10.1101/024034
Benjamin J Callahan
1Department of Statistics, Stanford University
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  • For correspondence: benjamin.j.callahan@gmail.com
Paul J McMurdie
2Second Genome, South San Francisco, CA
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Michael J Rosen
3Department of Applied Physics, Stanford University
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Andrew W Han
2Second Genome, South San Francisco, CA
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Amy Jo Johnson
2Second Genome, South San Francisco, CA
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Susan P Holmes
1Department of Statistics, Stanford University
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Abstract

Microbial communities are commonly characterized by amplifying and sequencing target genes, but errors limit the precision of amplicon sequencing. We present DADA2, a software package that models and corrects amplicon errors. DADA2 identified more real variants than other methods in Illumina-sequenced mock communities, some differing by a single nucleotide, while outputting fewer spurious sequences. DADA2 analysis of vaginal samples revealed a diversity of Lactobacillus crispatus strains undetected by OTU methods.

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Posted August 06, 2015.
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DADA2: High resolution sample inference from amplicon data
Benjamin J Callahan, Paul J McMurdie, Michael J Rosen, Andrew W Han, Amy Jo Johnson, Susan P Holmes
bioRxiv 024034; doi: https://doi.org/10.1101/024034
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DADA2: High resolution sample inference from amplicon data
Benjamin J Callahan, Paul J McMurdie, Michael J Rosen, Andrew W Han, Amy Jo Johnson, Susan P Holmes
bioRxiv 024034; doi: https://doi.org/10.1101/024034

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