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

机译:从Metabarcode序列结构揭开效果,用于分析和微生物组分析

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摘要

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.
机译:下一代测序的出现允许在特定位置内生活的更高吞吐量确定。在这里,我们建立了三种分析方法,用于估算样品内的多样性 - 即运营分类单位;较新的扩增子序列变体;并且通常在序列分析中发现的方法,Minhash-受这些序列数据的各种性质的影响。使用模拟,我们表明,来自每个物种的单核苷酸多态性和覆盖深度的存在影响了这些方法之间的相关性。通过这种分析,我们提供了影响每种方法应用的决策的见解。具体地,序列读取误差的存在和序列读取覆盖的可变性倾向地影响这些处理方法。

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