1. DNA metabarcoding is becoming the tool of choice for biodiversity assessment across taxa and environments. Yet, the artefacts present in metabarcoding datasets often preclude a proper interpretation of ecological patterns. Bioinformatic pipelines to remove experimental noise exist. However, these often only partially target produced artefacts, or are marker specific. In addition, assessments of data curation quality and chosen filtering thresholds are seldom available in existing pipelines, partly due to the lack of appropriate visualisation tools.
2. Here, we present metabaR, an r package that provides a comprehensive suite of tools to effectively curate DNA metabarcoding data after basic bioinformatic analyses. In particular, metabaR uses experimental negative or positive controls to identify different types of artefactual sequences, that is, contaminants and tag‐jumps. It also flags potentially dysfunctional PCRs based on PCR replicate similarities when those are available. Finally, metabaR provides tools to visualise DNA metabarcoding data characteristics in their experimental context as well as their distribution, and facilitates assessment of the appropriateness of data curation filtering thresholds.
3. metabaR is applicable to any DNA metabarcoding experimental design but is most powerful when the design includes experimental controls and replicates. More generally, the simplicity and flexibility of the package makes it applicable any DNA marker, and data generated with any sequencing platform, and pre‐analysed with any bioinformatic pipeline. Its outputs are easily usable for downstream analyses with any ecological r package.
4. metabaR complements existing bioinformatics pipelines by providing scientists with a variety of functions to effectively clean DNA metabarcoding data and avoid serious misinterpretations. It thus offers a promising platform for automatised data quality assessments of DNA metabarcoding data for environmental research and biomonitoring.

中文翻译：

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metabaR：用于评估和改善DNA元条形码数据质量的r软件包

1. DNA元条形码正成为在整个分类群和环境中进行生物多样性评估的首选工具。然而，存在于元条形码数据集中的伪像经常妨碍对生态模式的正确解释。存在消除实验噪声的生物信息管道。然而，这些通常仅部分地靶向产生的人工制品，或者是标记物特异性的。此外，在现有管道中很少可以评估数据管理质量和选择的过滤阈值，部分原因是缺少适当的可视化工具。
2. 在这里，我们介绍metabaR，它是r包，提供了全面的工具套件，可在基本的生物信息学分析后有效地整理DNA metabarcoding数据。特别是，metabaR使用实验性的阴性或阳性对照来识别不同类型的人工序列，即污染物和标签跳跃。当可用时，它还会基于PCR复制相似性来标记潜在功能异常的PCR。最后，metabaR提供了在实验环境中可视化DNA元条形码数据特征及其分布的工具，并有助于评估数据策展过滤阈值的适用性。
3. metabaR适用于任何DNA元条形码实验设计，但当该设计包括实验对照和复制品时，功能最强大。通常，该软件包的简单性和灵活性使其可适用于任何DNA标记物，通过任何测序平台生成的数据以及通过任何生物信息学管道进行预分析的数据。其输出是容易可用于与任何生态下游分析ř包。
4. metabaR为科学家提供了多种功能，可以有效地清洗DNA元条形码数据并避免严重的误解，从而补充了现有的生物信息学渠道。因此，它为用于环境研究和生物监测的DNA元条形码数据的自动化数据质量评估提供了一个有前途的平台。