nf-core mag

nf-core mag performs assembly, binning, annotation, and taxonomic profiling of shotgun metagenomic sequencing reads to reconstruct metagenome-assembled genomes (MAGs) and characterize microbial community composition.


Key Features:

  • Integration of Short and Long Reads: Optionally combines short- and long-read sequencing data to improve assembly continuity and genome reconstruction.
  • Co-assembly and Genome Binning: Supports sample-wise co-assembly and genome binning using group information to leverage multiple samples for improved MAG recovery.
  • Taxonomic Classification: Performs taxonomic classification of assembled genomes or bins to characterize microbial community composition.
  • Reproducibility and Portability: Implemented in Nextflow with containerized dependencies to ensure reproducible, portable execution across computational environments.

Scientific Applications:

  • Genome-resolved Metagenomics: Reconstruction of MAGs from complex microbial communities for downstream genomic and functional analyses.
  • Microbial Ecology and Environmental Microbiology: Profiling microbial diversity, function, and interactions in microbiology, ecology, and environmental science using genome-resolved data.

Methodology:

Data preprocessing; assembly (optionally integrating short and long reads) and co-assembly; sample-wise genome binning; genome annotation; and taxonomic classification.

Topics

Details

License:
MIT
Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Mac, Linux, Windows
Programming Languages:
Groovy, Python
Added:
2/12/2022
Last Updated:
2/12/2022

Operations

Publications

Krakau S, Straub D, Gourlé H, Gabernet G, Nahnsen S. nf-core/mag: a best-practice pipeline for metagenome hybrid assembly and binning. NAR Genomics and Bioinformatics. 2022;4(1). doi:10.1093/nargab/lqac007. PMID:35118380. PMCID:PMC8808542.

PMID: 35118380
PMCID: PMC8808542
Funding: - Deutsche Forschungsgemeinschaft: 398967434 - TRR 261, EXC 2124 - 390838134, EXC 2180 - 390900677, ZUK63 - German Federal Ministry of Education and Research: 01ZX1301F - Chan Zuckerberg Initiative: EOSS2-0000000270

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