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Uncovering Effects from the Structure of Metabarcode Sequences for Metagenetic and Microbiome Analysis

1
Biological Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
2
Electrical Engineering and Computer Science, University of Tennessee—Knoxville, Knoxville, TN 37996, USA
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Author to whom correspondence should be addressed.
Methods Protoc. 2020, 3(1), 22; https://doi.org/10.3390/mps3010022
Received: 29 September 2019 / Revised: 20 February 2020 / Accepted: 3 March 2020 / Published: 12 March 2020
(This article belongs to the Special Issue Multi-Omics in Health and Disease)
The advent of next-generation sequencing has allowed for higher-throughput determination of which species live within a specific location. Here we establish that three analysis methods for estimating diversity within samples—namely, Operational Taxonomic Units; the newer Amplicon Sequence Variants; and a method commonly found in sequence analysis, minhash—are affected by various properties of these sequence data. Using simulations we show that the presence of Single Nucleotide Polymorphisms and the depth of coverage from each species affect the correlations between these approaches. Through this analysis, we provide insights which would affect the decisions on the application of each method. Specifically, the presence of sequence read errors and variability in sequence read coverage deferentially affects these processing methods. View Full-Text
Keywords: minhash; k-mer; microbiome; mantel; PERMANOVA; metagenetics; compression; OTU; ASV minhash; k-mer; microbiome; mantel; PERMANOVA; metagenetics; compression; OTU; ASV
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Molik, D.C.; Pfrender, M.E.; Emrich, S.J. Uncovering Effects from the Structure of Metabarcode Sequences for Metagenetic and Microbiome Analysis. Methods Protoc. 2020, 3, 22.

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