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Welcome to PopMAG Docs!

Documentation: https://daasabogalro.github.io/popmag_docs/

Source Code: https://github.com/daasabogalro/popmag

PopMAG is a pipeline that integrates genome-resolved metagenomics data with population genomics tools to analyze metagenome-assembled genomes (MAGs) and their population-level variations. The pipeline processes MAGs alongside paired-end sequencing short reads to perform quality assessment, abundance profiling, variant calling, and population genomics analyses, ending in an interactive visualization dashboard built with shiny.

PopMAG can aid to understand both the functional potential and population dynamics of metagenome-assembled genomes, particularly in the context of comparative genomics and temporal or spatial studies.

Info

This project is under active development.

Pipeline Phases

The pipeline is organized into five main phases:

Wokflow

Phase Descriptions

Phase Description Key Tools
1. Quality Control Assess MAG quality, filter by completeness/contamination, and dereplicate genomes CheckM2, dRep
2. Profiling Profile microbial communities and calculate genome abundances SingleM, CoverM
3. Variant Calling Align reads to MAGs and identify single nucleotide variants Bowtie2, InStrain
4. Population Genomics Predict genes, annotate functions, and calculate population genetics metrics Prodigal, MetaCerberus, POGENOM
5. Visualization Interactive exploration of results through a Shiny dashboard R Shiny

Key Features

  • End-to-end analysis: From MAGs and metagenomic sequencing reads to population genetics metrics
  • Quality filtering: Automated filtering based on CheckM2 completeness and contamination scores
  • Genome dereplication: Remove redundant genomes using dRep
  • Variant detection: Identify SNVs at the population level with InStrain
  • Functional annotation: Annotate genes with MetaCerberus using multiple databases
  • Population metrics: Calculate FST with POGENOM and other population genetics statistics with InStrain
  • Interactive visualization: Explore results through an integrated Shiny dashboard
  • Scalable: Built on Nextflow for seamless execution on local machines, clusters, or cloud

Quick Start

Prepare your input samplesheets and run:

nextflow run daasabogalro/PopMAG \
    -profile docker \
    --mag_paths mags_samplesheet.tsv \
    --reads_paths reads_samplesheet.tsv \
    --metadata metadata.csv \
    --outdir results

See the Getting Started guide for detailed installation instructions and the Usage page for samplesheet preparation.

Credits

PopMAG was developed by Daniel Sabogal under the supervision of Alejandro Caro-Quintero at the Max Planck Tandem Group in Holobiont Research, Universidad Nacional de Colombia.

License

PopMAG is released under the MIT License. See the LICENSE file for details.