MPUSP/snakemake-assembly-postprocessing

A Snakemake workflow for the post-processing of microbial genome assemblies.

Overview

Latest release: v1.1.0, Last update: 2025-12-10

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Topics: apptainer bacteria conda genome-assembly genome-sequencing microbes pipeline postprocessing quality-control snakemake-workflow genomics

Deployment

Step 1: Install Snakemake and Snakedeploy

Snakemake and Snakedeploy are best installed via the Conda. It is recommended to install conda via Miniforge. Run

conda create -c conda-forge -c bioconda -c nodefaults --name snakemake snakemake snakedeploy

to install both Snakemake and Snakedeploy in an isolated environment. For all following commands ensure that this environment is activated via

conda activate snakemake

For other installation methods, refer to the Snakemake and Snakedeploy documentation.

Step 2: Deploy workflow

With Snakemake and Snakedeploy installed, the workflow can be deployed as follows. First, create an appropriate project working directory on your system and enter it:

mkdir -p path/to/project-workdir
cd path/to/project-workdir

In all following steps, we will assume that you are inside of that directory. Then run

snakedeploy deploy-workflow https://github.com/MPUSP/snakemake-assembly-postprocessing . --tag v1.1.0

Snakedeploy will create two folders, workflow and config. The former contains the deployment of the chosen workflow as a Snakemake module, the latter contains configuration files which will be modified in the next step in order to configure the workflow to your needs.

Step 3: Configure workflow

To configure the workflow, adapt config/config.yml to your needs following the instructions below.

Step 4: Run workflow

The deployment method is controlled using the --software-deployment-method (short --sdm) argument.

To run the workflow using a combination of conda and apptainer/singularity for software deployment, use

snakemake --cores all --sdm conda apptainer

To run the workflow with automatic deployment of all required software via conda/mamba, use

snakemake --cores all --sdm conda

Snakemake will automatically detect the main Snakefile in the workflow subfolder and execute the workflow module that has been defined by the deployment in step 2.

For further options such as cluster and cloud execution, see the docs.

Step 5: Generate report

After finalizing your data analysis, you can automatically generate an interactive visual HTML report for inspection of results together with parameters and code inside of the browser using

snakemake --report report.zip

Configuration

The following section is imported from the workflow’s config/README.md.

Workflow overview

A Snakemake workflow for the post-processing of microbial genome assemblies.

  1. Parse samples.csv table containing the samples’s meta data (python)

  2. Annotate assemblies using one of the following tools:

    1. NCBI’s Prokaryotic Genome Annotation Pipeline (PGAP). Note: needs to be installed manually

    2. prokka, a fast and light-weight prokaryotic annotation tool

    3. bakta, a fast, alignment-free annotation tool. Note: Bakta will automatically download its companion database from zenodo (light: 1.5 GB, full: 40 GB)

  3. Create a QC report for the assemblies using Quast

  4. Create a pangenome analysis (orthologs/homologs) using Panaroo

Running the workflow

Input data

This workflow requires fasta input data. The samplesheet table has the following layout:

sample

species

strain

id_prefix

file

EC2224

“Streptococcus pyogenes”

SF370

SPY

assembly.fasta

…

…

…

…

…

Note: Pangenome analysis with Panaroo requires at least two samples.

Parameters

This table lists all parameters that can be used to run the workflow.

Parameter

Type

Details

Default

samplesheet

string

Path to the sample sheet file in csv format

tool

array[string]

Annotation tool to use (one of prokka, pgap, bakta)

pgap

PGAP configuration object

bin

string

Path to the PGAP script

use_yaml_config

boolean

Whether to use YAML configuration for PGAP

False

prepare_yaml_files

Paths to YAML templates for PGAP

generic

string

Path to the generic YAML configuration file

submol

string

Path to the submol YAML configuration file

prokka

Prokka configuration object

center

string

Center name for Prokka annotation (used in sequence IDs)

extra

string

Extra command-line arguments for Prokka

--addgenes

bakta

Bakta configuration object

download_db

string

Bakta database type (full, light, or none)

light

existing_db

string

Path to an existing Bakta database (optional). Needs to be combined with download_db='none'

--keep-contig-headers --compliant

extra

string

Extra command-line arguments for Bakta

quast

QUAST configuration object

reference_fasta

string

Path to the reference genome for QUAST

reference_gff

string

Path to the reference annotation for QUAST

extra

string

Extra command-line arguments for QUAST

panaroo

Panaroo configuration object

remove_source

string

Source types to remove in Panaroo (regex supported)

cmsearch

remove_feature

string

Feature types to remove in Panaroo (regex supported)

tRNA|rRNA|ncRNA|exon|sequence_feature

extra

string

Extra command-line arguments for Panaroo

--clean-mode strict --remove-invalid-genes

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