16S rRNA amplicon sequencing analysis workflow using QIIME2.

Introduction

nfcore/ampliseq is a bioinformatics analysis pipeline used for 16S rRNA or ITS amplicon sequencing data (currently supported is Illumina paired end or PacBio).

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.

Quick Start

1. Install nextflow

2. Install any of Docker, Singularity or Podman for full pipeline reproducibility (please only use Conda as a last resort; see docs)

3. Download the pipeline and test it on a minimal dataset with a single command:

   nextflow run nf-core/ampliseq -profile test,<docker/singularity/podman/conda/institute>

   Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use -profile <institute> in your command. This will enable either docker or singularity and set the appropriate execution settings for your local compute environment.

4. Start running your own analysis!

   nextflow run nf-core/ampliseq -profile <docker/singularity/podman/conda/institute> --input "data" --FW_primer GTGYCAGCMGCCGCGGTAA --RV_primer GGACTACNVGGGTWTCTAAT --metadata "data/Metadata.tsv"

See usage docs and parameter docs for all of the available options when running the pipeline.

Pipeline Summary

By default, the pipeline currently performs the following:

• Sequencing quality control (FastQC)
• Trimming of reads (Cutadapt)
• Illumina read processing with QIIME2
• Infer Amplicon Sequence Variants (ASVs) (DADA2)
• Taxonomical classification based on SILVA v132 or UNITE database
• excludes unwanted taxa, produces absolute and relative feature/taxa count tables and plots, plots alpha rarefaction curves, computes alpha and beta diversity indices and plots thereof (QIIME2)
• Calls differentially abundant taxa (ANCOM)
• Overall pipeline run summaries (MultiQC)

Documentation

The nf-core/ampliseq pipeline comes with documentation about the pipeline: usage and output.

Credits

nf-core/ampliseq was originally written by Daniel Straub (@d4straub) and Alexander Peltzer (@apeltzer) for use at the Quantitative Biology Center (QBiC) and Microbial Ecology, Center for Applied Geosciences, part of Eberhard Karls Universität Tübingen (Germany).

We thank the following people for their extensive assistance in the development of this pipeline (in alphabetical order):

• Daniel Lundin
• Diego Brambilla
• Emelie Nilsson
• Jeanette Tångrot
• Sabrina Krakau

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don't hesitate to get in touch on the Slack #ampliseq channel (you can join with this invite).

Citations

If you use nf-core/ampliseq for your analysis, please cite the ampliseq article as follows:

Daniel Straub, Nia Blackwell, Adrian Langarica-Fuentes, Alexander Peltzer, Sven Nahnsen, Sara Kleindienst Interpretations of Environmental Microbial Community Studies Are Biased by the Selected 16S rRNA (Gene) Amplicon Sequencing Pipeline Frontiers in Microbiology 2020, 11:2652 doi: 10.3389/fmicb.2020.550420.

You can cite the nf-core/ampliseq zenodo record for a specific version using the following doi: 10.5281/zenodo.1493841

You can cite the nf-core publication as follows:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x. ReadCube: Full Access Link