Skip to content

Latest commit

 

History

History
94 lines (52 loc) · 5.97 KB

README_nfcore.md

File metadata and controls

94 lines (52 loc) · 5.97 KB
Raw

gms_16S

Nextflow run with conda run with docker run with singularity

Introduction

nf-core/gmsemu is a bioinformatics analysis pipeline for the EMU tool (https://gitlab.com/treangenlab/emu).

This Nextflow pipeline utilizes Falco, Porechop_ABI, Longfilt, and EMU for taxonomic profiling of 16S rRNA gene sequences. Built with Nextflow, it ensures portability and reproducibility across different computational infrastructures. Falco performs quality control, Porechop_ABI trims adapters and demultiplexes data, Longfilt filters the fastq-files such that only reads that are close to 1500 bp are used, and EMU assigns taxonomic classifications. The pipeline enables microbial community analysis, offering insights into the diversity in samples.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies.

Pipeline summary

236446648-c93dded5-1d51-4987-afad-5b0eedc01574

Quick Start

  1. Install Nextflow (>=22.10.1)

  2. Install any of Docker, Singularity (you can follow this tutorial), Podman, Shifter or Charliecloud for full pipeline reproducibility (you can use Conda both to install Nextflow itself and also to manage software within pipelines. Please only use it within pipelines as a last resort; see docs).

  3. Add you samples to a sample_sheet.csv

  4. gunzip the files in the database directory (if they are gzipped).

  5. Run your command

nextflow run main.nf --input assets/samplesheet_medium.csv     --outdir results_emu     --db /aux/db/workdir_fwa010/emu_pipe_project/gms_16S/assets/databases/emu_database/     --seqtype map-ont     -profile singularity,test

Credits

gms16S was originally written by @fwaa93.

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

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. In addition, references of tools and data used in this pipeline are as follows:

Nextflow

Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017 Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 2839>

Pipeline tools

  • FastQC

  • MultiQC

    Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354.>

Software packaging/containerisation tools

  • Anaconda

    Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web.

  • Bioconda

    Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018>

  • BioContainers

    da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-R>

  • Docker

  • Singularity

    Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; >

  • EMU

Kristen D. Curry et al., “Emu: Species-Level Microbial Community Profiling of Full-Length 16S RRNA Oxford Nanopore Sequencing Data,” Nature Methods, June 30, 2022, 1–9, https://doi.org/10.1038/s41592-022-015>

Citations

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.