FAIRyMAGs

A FAIR Galaxy Metagenome-Assembled Genomes (MAGs) Workflow

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Step-by-step MAGs Generation Guideline

Input

• Paired short reads (e.g., Zenodo dataset)

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Main Workflows and Tools

1. Upload your data to Galaxy

   • Galaxy data upload guide
   • Note: Only usegalaxy.eu currently supports all tools and databases.
   • Optionally, use dedicated fetch tools for published data: SRA fastq_dump

2. Group your data

   • Create a paired collection

3. Run quality control (QC) workflow

   • QC workflow

4. Optional: Remove host contamination

   • Host contamination removal workflow

5. Optional: Group reads for co/grouped assembly

   • Read grouping tool

6. Run MAGs generation workflow

   • MAGs-building workflow

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Potential Downstream Tools or Workflows

MAGs Annotation

• Taxonomy annotation
• AMR gene detection
• Bacterial genome annotation
• Functional annotation of protein sequences

Differential Abundance Analysis

• MaAsLin 2 Differential Analysis
• MaAsLin 3 Differential Analysis

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Run Analysis Scripts

1. Install conda

   • Conda installation guide

2. Install dependencies

conda create -n fairymags_env -c conda-forge -c bioconda --file requirements.txt -y

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MetaSPADES Resource Estimation

• Follow the step-by-step guide in the metaspades-resource-estimation README

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Pipeline Benchmark

• Follow the step-by-step guide in the pipeline-benchmark README

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Use case summary plots

• Follow the step-by-step guide in the use-cases README

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Use case summary plots

• Follow the step-by-step guide in the binning-evaluation README