Ultrafast and accurate 16S rRNA microbial community analysis using Kraken 2
Ultrafast and accurate 16S rRNA microbial community analysis using Kraken 2
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DOI：
10.1186/s40168-020-00900-2
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发表时间：
2020-08-28
期刊：
影响因子：
15.5
通讯作者：
Salzberg, Steven L.
中科院分区：
文献类型：
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作者：
Lu, Jennifer;Salzberg, Steven L.
背景：几十年来，16S 核糖体 RNA 测序一直是鉴定未知成分样品中细菌种类的主要手段。目前用于此目的最广泛使用的工具之一是 QIIME（微生物生态学定量洞察）软件包。最近的结果表明，最新版本的 QIIME 2 在对模拟人类肠道、海洋和土壤宏基因组中的细菌属进行分类时，比 QIIME、MAPseq 和 mothur 具有更高的准确性，尽管 QIIME 2 也被证明是计算成本最高的。 Kraken 于 2014 年首次发布，已被证明可为鸟枪法宏基因组测序项目提供异常快速和准确的分类。 Bracken 于 2016 年发布，随后为用户提供了使用 Kraken 分类结果准确估计物种或属相对丰度的能力。 Kraken 2 与 Kraken 1 的精度和速度相匹配，现在支持 16S rRNA 数据库，可以与 QIIME 和类似系统进行直接比较。 方法：为了对每个工具进行全面评估，我们比较了 QIIME 2 的 q2-feature-classifier、Kraken 2 和 Bracken 在生成三个主要 16S rRNA 数据库（Greengenes、SILVA 和 RDP）时的计算资源和速度。为了评估准确性，我们使用来自人类肠道、海洋和土壤宏基因组的相同模拟 16S rRNA 读数来评估每个工具，这些读数之前用于比较 QIIME、MAPseq、mothur 和 QIIME 2。我们根据每个工具分配的最终属读数计数的准确性来评估准确性。最后，由于 Kraken 2 是唯一提供每次读取分类分配的工具，我们评估了 Kraken 2 每次读取分类的敏感性和精度。结果：对于 Greengenes 和 SILVA 数据库，Kraken 2 和 Bracken 的数据库生成速度快了 100 倍。对于分类，使用与之前研究相同的数据，Kraken 2 和 Bracken 的速度提高了 300 倍，使用的 RAM 减少了 100 倍，并且生成的 16S rRNA 分析结果比 QIIME 2 的 q2-feature-classifier 更准确。结论：Kraken 2 和 Bracken 为 16S rRNA 元分类数据分析提供了非常快速、高效且准确的解决方案。
Background: For decades, 16S ribosomal RNA sequencing has been the primary means for identifying the bacterial species present in a sample with unknown composition. One of the most widely used tools for this purpose today is the QIIME (Quantitative Insights Into Microbial Ecology) package. Recent results have shown that the newest release, QIIME 2, has higher accuracy than QIIME, MAPseq, and mothur when classifying bacterial genera from simulated human gut, ocean, and soil metagenomes, although QIIME 2 also proved to be the most computationally expensive. Kraken, first released in 2014, has been shown to provide exceptionally fast and accurate classification for shotgun metagenomics sequencing projects. Bracken, released in 2016, then provided users with the ability to accurately estimate species or genus relative abundances using Kraken classification results. Kraken 2, which matches the accuracy and speed of Kraken 1, now supports 16S rRNA databases, allowing for direct comparisons to QIIME and similar systems.Methods: For a comprehensive assessment of each tool, we compare the computational resources and speed of QIIME 2's q2-feature-classifier, Kraken 2, and Bracken in generating the three main 16S rRNA databases: Greengenes, SILVA, and RDP. For an evaluation of accuracy, we evaluated each tool using the same simulated 16S rRNA reads from human gut, ocean, and soil metagenomes that were previously used to compare QIIME, MAPseq, mothur, and QIIME 2. We evaluated accuracy based on the accuracy of the final genera read counts assigned by each tool. Finally, as Kraken 2 is the only tool providing per-read taxonomic assignments, we evaluate the sensitivity and precision of Kraken 2's per-read classifications.Results: For both the Greengenes and SILVA database, Kraken 2 and Bracken are up to 100 times faster at database generation. For classification, using the same data as previous studies, Kraken 2 and Bracken are up to 300 times faster, use 100x less RAM, and generate results that more accurate at 16S rRNA profiling than QIIME 2's q2-feature-classifier.Conclusion: Kraken 2 and Bracken provide a very fast, efficient, and accurate solution for 16S rRNA metataxonomic data analysis.