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

Rebecca Ansorge¹, Giovanni Birolo², Stephen A James¹

¹Gut Microbes and Health Programme, Quadram Institute Bioscience, Norwich NR4 7UQ, UK.

International Journal of Molecular Sciences

|June 2, 2021

Summary

Dadaist2 is a new bioinformatics pipeline for analyzing microbial community sequencing data. It streamlines the process from raw reads to ecological statistics, especially for variable-length fungal ITS amplicons.

Keywords:

amplicon sequence variant bacterial taxonomy bioinformatics exact amplicon variant metabarcoding microbial communities numerical ecology statistical analysis visualizations

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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.