DADA2

DADA2 is an open-source software package designed for processing high-throughput amplicon and metagenomic sequencing data. Developed by the Bioinformatics Group at the University of Vienna, it is widely used in microbiome research to analyze DNA sequences derived from environmental samples. The name "DADA2" stands for "Divisive Amplicon Denoising Algorithm," which reflects its primary function of denoising sequencing data by removing errors introduced during amplification and sequencing.

The software performs several key steps in microbiome data analysis, including quality filtering, error correction, chimera removal, and sequence variant inference. Unlike traditional operational taxonomic unit (OTU) clustering methods, DADA2 employs a Bayesian approach to identify and correct sequencing errors at the single-nucleotide level, resulting in more accurate and precise sequence variants. This precision improves taxonomic classification and downstream analyses such as diversity metrics and phylogenetic inference.

DADA2 is implemented in the R programming language and integrates seamlessly with other Bioconductor packages, making it accessible to researchers familiar with R. It supports various sequencing platforms and primer schemes, allowing flexibility in handling different datasets. The software also includes tools for visualizing results, such as phylogenetic trees and sequence abundance plots, facilitating interpretation of microbiome composition.

Since its initial release, DADA2 has gained popularity due to its efficiency, accuracy, and ease of use. It has been applied in diverse fields, including environmental microbiology, human and animal health studies, and agricultural research. The project maintains active development, with regular updates addressing new sequencing technologies and methodological improvements. Documentation and tutorials are provided to assist users in implementing DADA2 in their workflows.