Abstract

The investigation of environmental microbial communities and microbiomes has been revolutionized by the

About This Material

This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.

Questions this will address

• What are the primary steps involved in generating an ASV table using DADA2 from 16S rRNA gene sequencing data?
• How does DADA2 improve the accuracy of microbial community analysis compared to traditional OTU-based methods?
• What is the importance of quality filtering in the DADA2 workflow, and how does it impact downstream analyses?
• How does the error rate learning process contribute to the identification of true biological sequences in DADA2?
• What role does chimera removal play in the DADA2 pipeline, and why is it crucial for obtaining reliable ASV data?
• How can phyloseq be used to explore and visualize the ASV table generated by DADA2, and what types of ecological insights can it provide?

Learning Objectives

• Identify the key steps in the DADA2 workflow for generating an ASV table from 16S rRNA gene sequencing data
• Explain the importance of quality filtering, error rate learning, and chimera removal in ensuring accurate microbial community analysis
• Execute the DADA2 pipeline to process raw 16S sequencing data and produce a high-resolution ASV table
• Compare the advantages of ASV-based methods over traditional OTU-based approaches in terms of accuracy and resolution
• Assess the effectiveness of using phyloseq for exploring and visualizing ASV data to gain ecological and evolutionary insights