Workflows#
Our workflows use Docker, reducing the need for complex dependencies while allowing us to incorporate many different tools. This approach relies on publicly avaliable images, so we use existing community images whenever possible and create and host our own when necessary.
Installation and usage
This section outlines and summarizes some of the existing workflows. For a full, detailed list of published workflows (including inputs, steps, and outputs), see our WorkflowHub. An introduction to setting up and using one of these workflows can be found in the Setup section.
Workflow: Metagenomics Assembly#
This workflow assembles genomes from Illumina reads and/or long reads. It is customizable to a certain extent regarding which steps to run and can also be used for isolates.
Main steps involved:
Illumina Quality Workflow
Long Read Quality Workflow
Assembly: SPAdes / Flye
Short read polishing (Pilon)
ONT read polishing (Medaka)
QUAST (Assembly quality report)
Metagenomics Binning workflow
Metagenomics GEM workflow
Workflow: Illumina Quality#
This workflow ensures high-quality Illumina read data before further analysis.
Steps included:
FastQC quality plots (before and after filtering)
fastp quality filtering
BBduk PhiX removal and rRNA filtering
BBmap Reference/contamination filtering (mapped or unmapped)
Kraken2 taxonomic read classification (before and after)
Workflow: Long Reads Quality#
This workflow ensures high-quality Nanopore/long-read data before further analysis.
Steps included:
NanoPlot quality plots and reports (before and after filtering)
Filtlong long reads quality filtering
Minimap2 Reference/contamination filtering (mapped or unmapped)
Kraken2 taxonomic read classification (before and after)
Workflow: Metagenomics Binning#
This workflow bins metagenomic reads into individual genomes.
Steps included:
Metabat2 / MaxBin2 / SemiBin binning
DAS Tool bin refinement
EukRep (eukaryotic classification)
CheckM bin quality
BUSCO bin quality
GTDB-Tk bin taxonomic classification
Workflow: Metagenomics GEM#
!! Important caveat: The CarveMe, MEMOTA and SMETANA Docker container images used in this workflow include the licenced CPLEX Optimizer. Therefore, we cannot make these images public. This means the workflow will not work out-of-the-box. However, we have made the Docker Build files available here
Steps included:
Prodigal protein prediction
CarveMe GEnome-scale Metabolic model reconstruction
MEMOTE for metabolic model testing
SMETANA Species METabolic interaction ANAlysis