Dadaist2: A Toolkit to Automate and Simplify Statistical Analysis and Plotting of Metabarcoding Experiments.

Area of Science:

• Microbiology
• Bioinformatics
• Computational Biology

Background:

• Microbial community taxonomic composition is assessed using amplicon sequencing.
• 16S rDNA and ITS are common markers for bacteria and fungi, respectively.
• Sequence denoising algorithms like DADA2 identify Amplicon Sequence Variants (ASVs).

Purpose of the Study:

• To present Dadaist2, a modular pipeline for comprehensive amplicon sequence analysis.
• To provide a streamlined workflow from raw sequencing reads to numerical ecology statistics.
• To offer an optimized approach for variable-length amplicons, such as fungal ITS.

Main Methods:

• Dadaist2 is a command-line and R-integrated pipeline.
• It implements a novel denoising approach optimized for variable-length amplicons.
• The pipeline facilitates data flow and integrates statistical analysis and plotting.

Main Results:

• Dadaist2 provides a complete suite for amplicon sequence analysis.
• It offers optimized performance for fungal ITS amplicons.
• The pipeline streamlines data processing and analysis from raw reads to ecological statistics.

Conclusions:

• Dadaist2 offers a comprehensive and optimized solution for microbial amplicon sequencing data analysis.
• The pipeline enhances the analysis of variable-length markers like fungal ITS.
• Dadaist2 facilitates streamlined data processing and advanced statistical analysis.