moiexpositoalonsolab/grenepipe

A flexible, scalable, and reproducible pipeline to automate variant calling from raw sequence reads, with lots of bells and whistles - for sampled individuals, and for pool sequencing.

Overview

Topics: variant-calls snakemake evolve-and-resequence population-genetics ancient-dna variant-calling pool-sequencing genomic-variant-calling snakemake-workflow

Latest release: v0.14.0, Last update: 2025-02-24

Linting: linting: failed, Formatting:formatting: passed

Deployment

Step 1: Install Snakemake and Snakedeploy

Snakemake and Snakedeploy are best installed via the Mamba package manager (a drop-in replacement for conda). If you have neither Conda nor Mamba, it is recommended to install Miniforge. More details regarding Mamba can be found here.

When using Mamba, run

mamba create -c conda-forge -c bioconda --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

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/moiexpositoalonsolab/grenepipe . --tag v0.14.0

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 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.

Configuring grenepipe

Grenepipe is a highly flexible workflow for variant calling from raw sample sequences, with lots of bells and whistles. To configure this workflow, modify config/config.yaml according to your needs, following the explanations provided in the file.

Furthermore, for the general usage of grenepipe, see our wiki. See there to get started with grenepipe.

Pipeline Overview

Minimal input:

• Reference genome fasta file
• Per-sample fastq files
• Optionally, a vcf file of known variants to restrict the variant calling process

Process and available tools:

• Read trimming (single or paired end)
  • AdapterRemoval
  • Cutadapt
  • fastp
  • SeqPrep
  • skewer
  • trimmomatic
• Read mapping
  • bwa mem
  • bwa aln
  • bwa mem2
  • Bowtie2
• Optional read filtering, clipping, duplication removal, and quality score recalibration
  • samtool view
  • BamUtil clipOverlap
  • Picard MarkDuplicates
  • DeDup
  • GATK BaseRecalibrator (BQSR)
  • samtools mpileup
• Damage profiling (optional; e.g., for ancient DNA)
  • mapDamage
  • DamageProfiler
• Variant calling and genotyping
  • GATK HaplotypeCaller / GATK GenotypeGVCFs
  • freebayes
  • bcftools call
• Variant filtering
  • GATK VariantFiltration
  • GATK VariantRecalibrator (VQSR)
  • bcftools filter
• Frequency calling (for pool sequencing data, as an alternative to variant calling)
  • HAF-pipe
• Quality control, statistics, SNP annotation, reporting
  • FastQC
  • samtool stats
  • samtool flagstat
  • QualiMap
  • Picard CollectMultipleMetrics
  • bcftools stats
  • snpEff
  • VEP (Ensembl Variant Effect Predictor)
  • MultiQC

Typical output:

• Variant calls vcf, raw and filtered, and potentially with annotations
• MultiQC report (includes summaries of most other tools, and of the final vcf)
• Snakemake report (optional)

Linting and formatting

Linting results

Using workflow specific profile workflow/profiles/default for setting default command line arguments.
WorkflowError in file /tmp/tmpiks6dpa1/moiexpositoalonsolab-grenepipe-1aae2c9/workflow/rules/initialize.smk, line 50:
Workflow defines configfile config.yaml but it is not present or accessible (full checked path: /tmp/tmpiks6dpa1/moiexpositoalonsolab-grenepipe-1aae2c9/config.yaml).

Formatting results

None