westerdijk-wm/snakemake-mlsa-ani

Snakemake workflow for MLSA and ANI analysis

Overview

Latest release: None, Last update: 2026-07-08

Share link: https://snakemake.github.io/snakemake-workflow-catalog?wf=westerdijk-wm/snakemake-mlsa-ani

Quality control: linting: passed formatting: passed

Wrappers: bio/fasttree bio/minimap2/aligner bio/quast

Workflow Rule Graph

This visualization of the workflow’s rule graph was automatically generated using Snakevision

Rule Graph light

Deployment

Step 1: Install Snakemake and Snakedeploy

Snakemake and Snakedeploy are best installed via the Conda package manager. 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/westerdijk-wm/snakemake-mlsa-ani . --tag None

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.

Configuration

The workflow is configured through config/config.yaml.

This file defines the analysis parameters: loci selection, phylogenetic inference settings, ANI options, and optional inclusion of public genomes.

Full configuration example

An example config.yaml configuration looks like this:

# Gene configuration — names must match headers in ref-genes.fas exactly
genes:
  - calmodulin
  - actin
  - rpb2
  - benA

# Tree configuration
tree:
  method: iqtree    # iqtree | raxml | fasttree
  bootstrap: 1000

# ANI configuration
ani_method: skani   # skani | fastani | pyani | none

# Reference gene database
ref_genes: config/ref-genes.fas

# Optional: public genomes to download from NCBI
accessions: config/public_genomes.txt

Key

Required

Description

genes

Yes

List of MLSA loci to extract and analyze.

tree.method

Yes

Phylogenetic inference method (iqtree, raxml, fasttree).

tree.bootstrap

Depends on method

Number of bootstrap replicates.

ani_method

Yes

ANI tool to use (skani, fastani, pyani, none).

ref_genes

Yes

Path to the reference gene FASTA database.

accessions

No

Path to TSV listing NCBI accessions to download.

Genes (MLSA loci)

genes defines which loci are extracted from genome assemblies and used for multilocus sequence analysis. Each gene corresponds to a reference locus in the reference gene database and the names must match exactly.

  • At least one gene must be specified.

  • You may specify a subset of the genes present in the reference database to run a reduced analysis.

Reference gene database format

The reference loci are defined in the file pointed to by ref_genes (default: config/ref-genes.fas). Each sequence must follow the required header format:

>{strain}|{gene} {optional description}

For example:

>Af293|actin NC_007199.1:c1114851-1113100 act1
AAGAAGTTGCTGCTCTCGTCATCGACAATGGGTATGTCTTTTATCTTCAG.....

Requirements:

  • The header must contain a strain ID and gene name separated by |.

  • Each strain|gene combination must be unique.

  • Gene names must match those listed under genes in config.yaml.

  • Any text after the first space is treated as an optional description and is ignored during parsing.

It is also possible to include homologous genes from different strains (e.g. flavus|actin, fumigatus|actin). This enables consistent locus comparisons across taxa and is important for downstream phylogenetic inference.

The database is validated automatically at the start of each run. See Outputs for details on validation results.

Phylogenetic inference

Phylogenetic reconstruction is configured under tree. The selected method determines which inference algorithm is used.

raxml

  • Maximum likelihood inference under GTR+GAMMA

  • Standard bootstrap support

  • Bootstrap (tree.bootstrap):

    • Minimum: 1 (lower values raise an error)

    • Recommended: ≥ 100 (lower values trigger a warning)

fasttree

  • Very fast approximate tree inference under GTR+GAMMA

  • No bootstrap support

  • tree.bootstrap is ignored if set (a warning is printed)

ANI analysis

Configured under ani_method. Available options:

fastani

  • Pairwise ANI computation

  • Relatively fast

pyani

  • ANIm-based ANI and alignment coverage analysis

  • Relatively slow; produces both identity and coverage matrices

none

  • Disables ANI analysis entirely; no ANI rules are included in the workflow

Genome input

Genome assemblies must be placed in the genomes/ directory.

Supported file extensions:

  • .fna

  • .fa

  • .fasta

  • .fas

Each file must contain a single genome assembly. The sample name used downstream is derived from the filename (without extension).

Public genomes

Additional public genomes can be specified via accessions in config.yaml, pointing to a tab-separated file (default: config/public_genomes.txt) with a sample column and an assembly column:

sample	assembly
Af293	GCA_000002655.1
A1163	GCA_000150145.1
IFM58399	GCA_010724455.1
PK20-01	GCA_023625555.1
IFM46973	GCA_001078395.2
IFM46972	GCA_010723835.1
NRRL181	GCA_000149645.4
NRRL4585	GCA_014250575.1

  • sample is the name used for that genome throughout the workflow.

  • assembly must be a valid NCBI assembly accession (GCA_ or GCF_).

  • Downloaded assemblies are placed in resources/public_genomes/ and processed identically to local genomes from genomes/.

Compute resources

The number of threads available to the workflow is controlled via Snakemake’s --cores option:

snakemake --cores 10 --use-conda

Most rules use threads: workflow.cores and will use all available cores. A few rules (gene extraction, alignment, concatenation) request min(4, workflow.cores) threads, since these steps rarely benefit from more than 4 threads per task. If --cores is set below 4, these rules automatically scale down to the available core count.

Running with very few cores (e.g. --cores 2) is supported and will not cause errors, but will increase runtime, particularly for QUAST, minimap2, IQ-TREE, and ANI computation.

Workflow parameters

The following table is automatically parsed from the workflow’s config.schema.y(a)ml file.

Parameter

Type

Description

Required

Default

accessions

string

Path to a TSV file (columns: sample, assembly) listing public genomes to download from NCBI. The key may be omitted or commented out entirely to run with local genomes only.

ani_method

string

skani

genes

array

yes

ref_genes

string

Path to the reference gene FASTA file.

yes

tree

yes

. method

string

yes

iqtree

. bootstrap

integer

1000

Linting and formatting

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