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      DADA2: High resolution sample inference from Illumina amplicon data

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          Abstract

          We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.

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          Most cited references25

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          QIIME allows analysis of high-throughput community sequencing data.

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            UPARSE: highly accurate OTU sequences from microbial amplicon reads.

            Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.
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              Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.

              mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.
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                Author and article information

                Journal
                101215604
                32338
                Nat Methods
                Nat. Methods
                Nature methods
                1548-7091
                1548-7105
                1 May 2016
                23 May 2016
                July 2016
                23 November 2016
                : 13
                : 7
                : 581-583
                Affiliations
                [1 ]Department of Statistics, Stanford University, Stanford, CA, USA
                [2 ]Second Genome, South San Francisco, CA, USA
                [3 ]Department of Applied Physics, Stanford University, Stanford, CA, USA
                Author notes
                [* ]Corresponding Author: benjamin.j.callahan@ 123456gmail.com
                Article
                NIHMS782534
                10.1038/nmeth.3869
                4927377
                27214047
                58aada41-2d6e-4f66-a569-38defe6b6083

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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                Life sciences
                Life sciences

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