bio-workflow-management-snakemake-workflows
Build reproducible bioinformatics pipelines with Snakemake using rules, wildcards, and automatic dependency resolution. Use when creating Python-based workflows, automating multi-step analyses with make-like dependency tracking, or running pipelines on HPC clusters with SLURM.
npx skills add BioTender-max/awesome-bio-agent-skills --skill snakemake-workflows --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: BWA 0.7.17+, FastQC 0.12+, MultiQC 1.21+, Nextflow 23.10+, Salmon 1.10+, Snakemake 8.0+, bcftools 1.19+, fastp 0.23+, pandas 2.2+, samtools 1.19+, scanpy 1.10+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Snakemake Workflows **"Build a reproducible bioinformatics pipeline with Snakemake"** → Define analysis steps as rules with input/output declarations, automatic dependency resolution via wildcards, and cluster execution support for HPC/cloud environments. - Python: Snakefile rule syntax with `expand()`, `wildcards`, and `config` for parameterization Compatible with Snakemake 7.x, 8.x, and 9.x. For Snakemake 8.0+, use `--executor` instead of `--cluster`. ## Basic Rule Structure ```python # Snakefile rule all: input: expand("results/{sample}_counts.txt", sample=SAMPLES) rule align: input: r1
- Version Compatibility
- Basic Rule Structure
- Config File
- Wildcards and Expand
- Python Integration
- Conda Environments
- Container Support
- Resource Management
- Cluster Execution
- Checkpoints
- Modular Workflows
- Temporary and Protected Files
- Benchmarking
- Logging
Run with Singularity
snakemake --use-singularity --singularity-args "-B /data"
Snakemake 8.x with executor plugin
pip install snakemake-executor-plugin-slurm
snakemake --executor slurm --jobs 100
Snakemake 7.x cluster execution
snakemake --cluster "sbatch --partition={cluster.partition} \
Or use profile (both versions)
snakemake --profile slurm
Dry run (show what would be executed)What does the bio-workflow-management-snakemake-workflows skill do?
Build reproducible bioinformatics pipelines with Snakemake using rules, wildcards, and automatic dependency resolution. Use when creating Python-based workflows, automating multi-step analyses with make-like dependency tracking, or running pipelines on HPC clusters with SLURM.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill snakemake-workflows --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.