Scholarlink

This chapter covers methods and best practices for analyzing 16S datasets, with a particular emphasis on the quality control steps, from the preprocessing of the raw sequencing reads to the removal of chimeric amplification products. It describes outputs from the analysis of raw reads that provide the foundation for downstream analyses and interpretation of the microbial community composition and diversity. It provides details of the tools to perform each step and how the framework Qiime2 and a Nextflow pipeline (nf-core/ampliseq) can improve the reproducibility and traceability of the analysis. Finally, it describes Lotus2, an efficient end-to-end pipeline developed at QIB, which allows the user to select the strategy to adopt for feature identification and taxonomic profiling.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Bioinformatics Processing of 16S Datasets

  • 实验方案

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

查看全文
  • Alise J. Ponsero,
  • Anthony Duncan,
  • Judit Talas,
  • Katarzyna Sidorczuk,
  • Wing Koon,
  • Falk Hildebrand,
  • Andrea Telatin

摘要

This chapter covers methods and best practices for analyzing 16S datasets, with a particular emphasis on the quality control steps, from the preprocessing of the raw sequencing reads to the removal of chimeric amplification products. It describes outputs from the analysis of raw reads that provide the foundation for downstream analyses and interpretation of the microbial community composition and diversity. It provides details of the tools to perform each step and how the framework Qiime2 and a Nextflow pipeline (nf-core/ampliseq) can improve the reproducibility and traceability of the analysis. Finally, it describes Lotus2, an efficient end-to-end pipeline developed at QIB, which allows the user to select the strategy to adopt for feature identification and taxonomic profiling.