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| Attribut | ＋ Werkzeug hinzufügen | |||
|---|---|---|---|---|
| Category | Research Tooling & Frameworks | Scientific ML Libraries & Supporting Tools | Scientific ML Libraries & Supporting Tools | — |
| Subcategory | Bioinformatics Workflow Engines | Conventional or Statistical Baselines | Conventional or Statistical Baselines | — |
| Company | Snakemake Community (Köster Lab) | Research / method authors | Research / method authors | — |
| Access mode | Open Source | Confirm distribution and exact release | Confirm distribution and exact release | — |
| Licence conditions | MIT License | NOT_INDEPENDENTLY_AUDITED | NOT_INDEPENDENTLY_AUDITED | — |
| Compute requirements | Standard Python environment (runs on laptop or HPC cluster) | Version and data dependent | Version and data dependent | — |
| Biological application | Genomic variant calling, RNA-seq analysis, metagenomics, and multi-omics pipelines | Nicht erfasst | Nicht erfasst | — |
| Research workflow | Define rules with inputs, outputs, and shell commands -> execute with automated DAG resolution | Nicht erfasst | Nicht erfasst | — |
| Evidence level | Peer-reviewed publication (Bioinformatics 2012 / F1000Research 2021) with wide adoption | PEER_REVIEWED_METHOD_OR_CONFERENCE | PEER_REVIEWED_METHOD_OR_CONFERENCE | — |
| Commercial eligibility | Permissive open source release | NOT_INDEPENDENTLY_AUDITED | NOT_INDEPENDENTLY_AUDITED | — |
| Price | Free Open Source | Verify access and licence | Verify access and licence | — |
| Availability ⓘ | Available via Bioconda and PyPI | Method paper or official documentation | Method paper or official documentation | — |
| Features | Python-based rule syntax making pipelines readable and modular, Seamless scaling from single workstations to compute clusters (SLURM, PBS) and cloud environments, Automatic tracking of software dependencies via Conda environments and container images, Integrated reporting tools generating interactive HTML execution and benchmark reports | HMMER 3 scientific method, Query sequences or profile HMM and sequence database, Profile HMM hits and statistical homology significance | MMseqs2 scientific method, Amino acid queries and reference sequence database, Sequence matches, clusters and alignment results | — |
| Entry type | Open Source Software | Classical/statistical scientific method | Classical/statistical scientific method | — |
| AI role | Workflow Orchestration & Reproducibility | NON_AI_CLASSICAL | NON_AI_CLASSICAL | — |
| Input data | Nicht erfasst | Query sequences or profile HMM and sequence database | Amino acid queries and reference sequence database | — |
| Output data | Nicht erfasst | Profile HMM hits and statistical homology significance | Sequence matches, clusters and alignment results | — |
| Validation | Nicht erfasst | Published method scope; no independent BioAtlas execution or benchmark | Published method scope; no independent BioAtlas execution or benchmark | — |
| Type | Workflow management engine | Nicht erfasst | Nicht erfasst | — |
| Intended use | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Compatibility | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Manufacturer | Snakemake Contributors / University of Duisburg-Essen | Nicht erfasst | Nicht erfasst | — |
| Integration evidence | https://snakemake.github.io | Nicht erfasst | Nicht erfasst | — |
| Laboratory handoff | Automates analysis pipelines from raw instrument data to final summary tables | Nicht erfasst | Nicht erfasst | — |