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Dadasnake, a Snakemake implementation of DADA2 to process amplicon sequencing data for microbial ecology
Christina Weißbecker1, Beatrix Schnabel1, Anna Heintz-Buschart1,2
1Helmholtz Centre for Environmental Research GmbH - UFZ, Department of Soil Ecology; Theodor-Lieser-Str. 4, 06120 Halle, Germany.
Gigascience
|November 30, 2020
Summary
dadasnake is a user-friendly pipeline for microbial community analysis using the DADA2 algorithm. It simplifies amplicon sequencing data processing, enabling efficient use of computational resources for researchers.
Area of Science:
- Microbiology
- Bioinformatics
- Computational Biology
Background:
- Amplicon sequencing of ribosomal RNA genes (e.g., 16S, 18S, ITS) is standard for microbial community composition analysis.
- Microbial ecologists possess biological expertise but face limitations in bioinformatics skills for efficient computational resource utilization.
Purpose of the Study:
- To present dadasnake, a user-friendly Snakemake pipeline simplifying amplicon sequencing data analysis.
- To enable researchers to efficiently process and analyze microbial community data using the DADA2 algorithm.
Main Methods:
- Developed dadasnake, a 1-command Snakemake pipeline.
- Integrated DADA2 algorithm for sequence variant delineation and taxonomic classification.
- Included preprocessing and post-processing steps for amplicon sequencing data.
Main Results:
- Demonstrated dadasnake's suitability with mock community data for bacteria, archaea, and fungi.
- Showcased efficient utilization of high-performance computing via Snakemake.
- Ensured flexibility for various sequencing platforms and user configurations.
Conclusions:
- dadasnake offers an accessible solution for microbial community analysis, overcoming bioinformatics skill barriers.
- The pipeline facilitates efficient and up-to-date use of computational resources.
- dadasnake is easily installable via conda and available on GitHub.
