maggic (Metagenomically Assembled Genome Generation with Integrated Classification) is an automated workflow for the generation and refinement of Metagenome-Assembled Genomes (MAGs) from metagenomic sequencing data. It integrates multiple binning algorithms (VAMB, SemiBin2, MetaBat 2) followed by consensus-based bin refinement with Binette, taxonomic classification with GTDB-Tk, mobile genetic element detection with geNomad, and antimicrobial resistance gene profiling with AMRFinderPlus.
maggic works with short-read and long-read metagenomic sequencing data and produces quality-checked MAGs alongside comprehensive MultiQC reports.
It is written in Nextflow and is part of the modular data analysis pipelines (CFSAN PIPELINES or CPIPES for short) at HFP.
- The current release version is
v0.7.0. - See the full changelog.
CPIPES:
maggic: READ WIKI.
This is still a work in progress.
maggic: Metagenomically Assembled Genome Generation with Integrated Classification
Kranti Konganti. [Work in Progress].
Add --maggic_wand_run true to the command-line call to generate plots, which will be included in the generated MultiQC report file.
Data Summary
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Quality Scatter
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AMR Class Distribution
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Species Diversity
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Click to expand: Completeness vs contamination scatter, ECDF, and contig count diagnostics.
Click to expand: Genus/species composition, diversity bars, and abundance heatmaps.
Click to expand: AMR gene wordcloud and resistance class distribution.
Click to expand: Plasmid, virus, provirus, and conjugation signals across bins.
- The main workflow has been used for research purposes only.
- Analysis results should be interpreted with caution and should be treated as suspect.
- Binning quality is dependent on sequencing depth, genome complexity, and the reference databases used for taxonomic classification.
- Low
Bacterial_Confidenceassignments should be interpreted with caution.
We gratefully acknowledge the developers and maintainers of all tools used in this pipeline: fastp, MEGAHIT, minimap2, VAMB, SemiBin2, MetaBat 2, Binette, CheckM2, GTDB-Tk, geNomad, AMRFinderPlus, CoverM, and MultiQC.
We also acknowledge all data contributors who have shared reference genomes and metadata through NCBI, GTDB, and other public databases.
HFP, FDA assumes no responsibility whatsoever for use by other parties of the Software, its source code, documentation or compiled or uncompiled executables, and makes no guarantees, expressed or implied, about its quality, reliability, or any other characteristic. Further, HFP, FDA makes no representations that the use of the Software will not infringe any patent or proprietary rights of third parties. The use of this code in no way implies endorsement by the HFP, FDA or confers any advantage in regulatory decisions.