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      Modelling and predicting population of core fungi through processing parameters in spontaneous starter (Daqu) fermentation

      , , , ,
      International Journal of Food Microbiology
      Elsevier BV

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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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              Search and clustering orders of magnitude faster than BLAST.

              Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch.
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                Author and article information

                Journal
                International Journal of Food Microbiology
                International Journal of Food Microbiology
                Elsevier BV
                01681605
                February 2022
                February 2022
                : 363
                : 109493
                Article
                10.1016/j.ijfoodmicro.2021.109493
                34953345
                0d669206-8384-476f-9b73-c9c16eda97c7
                © 2022

                https://www.elsevier.com/tdm/userlicense/1.0/

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