Fung Calvin, Rusling Mathew, Lampeter Thomas, Love Charles, Karim Anisha, Bongiorno Christian, Yuan Li-Lian
Des Moines University, College of Osteopathic Medicine, Des Moines, Iowa.
New York Institute of Technology, College of Osteopathic Medicine, Old Westbury, New York.
Curr Protoc. 2021 Sep;1(9):e254. doi: 10.1002/cpz1.254.
QIIME is a widely used, open-source microbiome analysis software package that converts raw sequence data into interpretable visualizations and statistical results. QIIME2 has recently succeeded QIIME1, becoming the most updated platform. The protocols in this article describe our effort in automating core functions of QIIME2, using datasets available at docs.qiime2.org. While these specific examples are microbial 16S rRNA gene sequences, our automation can be easily applied to other types of QIIME2 analysis. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Preparing files and folders Support Protocol 1: Preparing your data for QAP Support Protocol 2: Understanding automated options Basic Protocol 2: Importing into QIIME Basic Protocol 3: DADA2: Filtering, trimming, merging pairs Basic Protocol 4: Performing core metrics Basic Protocol 5: Sample filtering by metadata Basic Protocol 6: Alpha diversity metrics Basic Protocol 7: Cross-sectional beta diversity Basic Protocol 8: Longitudinal feature volatility Basic Protocol 9: Sample classification.
QIIME是一个广泛使用的开源微生物组分析软件包,它将原始序列数据转换为可解释的可视化结果和统计结果。QIIME2最近取代了QIIME1,成为最新的平台。本文中的协议描述了我们利用docs.qiime2.org上提供的数据集,对QIIME2的核心功能进行自动化的工作。虽然这些具体示例是微生物16S rRNA基因序列,但我们的自动化方法可以轻松应用于其他类型的QIIME2分析。© 2021威利期刊有限责任公司。基本方案1:准备文件和文件夹 支持方案1:为QAP准备数据 支持方案2:了解自动化选项 基本方案2:导入QIIME 基本方案3:DADA2:过滤、修剪、合并配对 基本方案4:执行核心指标 基本方案5:按元数据进行样本过滤 基本方案6:α多样性指标 基本方案7:横断面β多样性 基本方案8:纵向特征波动性 基本方案9:样本分类。