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Use when the user asks about SDRF templates, wants to select templates for an experiment, or needs to understand template layers, inheritance, mutual exclusivity, and selection rules.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | sdrf:templates |
| description | Use when the user asks about SDRF templates, wants to select templates for an experiment, or needs to understand template layers, inheritance, mutual exclusivity, and selection rules. |
| user-invocable | true |
| argument-hint | [experiment description or template name] |
Templates define which columns are required for a given experiment type.
Each SDRF can declare one or more templates via comment[sdrf template] columns.
The authoritative source for all template information is in the spec/ submodule:
spec/sdrf-proteomics/sdrf-templates/templates.yamlspec/sdrf-proteomics/sdrf-templates/{name}/{version}/{name}.yamlspec/sdrf-proteomics/TERMS.tsv (the usage field shows which templates include each column)Always read templates.yaml when answering questions about templates, versions, inheritance,
or mutual exclusivity. Never rely on memorized template data — the spec evolves.
The manifest file lists every template with these fields:
name — template identifier (e.g., ms-proteomics, human)version — current version (e.g., 1.1.0)extends — parent template with version constraint (e.g., sample-metadata@>=1.0.0)description — what the template addsusable_alone — whether it can be used without other templates (only ms-proteomics and affinity-proteomics)excludes — templates that are mutually exclusive with this onelayer — which selection layer it belongs toEach template has a YAML file at spec/sdrf-proteomics/sdrf-templates/{name}/{version}/{name}.yaml.
These define the columns the template adds, with requirement levels (required/recommended/optional).
Two ways:
usage contains the template nameTemplates are organized into layers. Each layer serves a different purpose:
Technology (REQUIRED — pick exactly one): The measurement technology used.
ms-proteomics — mass spectrometry experimentsaffinity-proteomics — Olink, SomaScan, and other affinity platformsSample/Organism (RECOMMENDED — pick at most one organism template):
human — Homo sapiens samplesvertebrates — mouse, rat, zebrafish, etc.invertebrates — Drosophila, C. elegans, insectsplants — Arabidopsis, cropsclinical-metadata — clinical studies (can combine with organism templates)oncology-metadata — cancer studies (extends clinical-metadata)Experiment (OPTIONAL — pick any applicable):
cell-lines — cultured cell linesdia-acquisition — DIA/SWATH (extends ms-proteomics)single-cell — single-cell proteomics (extends ms-proteomics)immunopeptidomics — MHC peptide studies (extends ms-proteomics)crosslinking — XL-MS (extends ms-proteomics)olink — Olink PEA (extends affinity-proteomics)somascan — SomaScan (extends affinity-proteomics)Metaproteomics (SPECIAL — uses its own sample scheme):
metaproteomics — environmental/microbiome base (excludes sample-metadata)human-gut — host-associated microbiomesoil — soil metaproteomicswater — aquatic metaproteomicsms-proteomics ↔ affinity-proteomics — different technologieshuman ↔ vertebrates ↔ invertebrates ↔ plants — pick at most one organismmetaproteomics excludes sample-metadata — uses its own sample schemeolink and somascan extend affinity-proteomics — cannot combine with ms-proteomicsdia-acquisition, single-cell, immunopeptidomics, crosslinking extend ms-proteomics — cannot combine with affinity-proteomicsRead templates.yaml for the full excludes field on each template to verify mutual exclusivity.
Is it mass spectrometry?
├── YES → ms-proteomics
│ ├── Human samples? → + human
│ │ ├── Cancer study? → + oncology-metadata
│ │ ├── Clinical trial / drug treatment? → + clinical-metadata
│ │ └── Cell lines from human? → + human + cell-lines
│ ├── Mouse/rat/zebrafish? → + vertebrates
│ │ └── Cell lines from animal? → + vertebrates + cell-lines
│ ├── Drosophila/C. elegans? → + invertebrates
│ ├── Plant? → + plants
│ ├── Environmental/microbiome? → metaproteomics (REPLACES organism layer)
│ │ ├── Human gut? → + human-gut
│ │ ├── Soil? → + soil
│ │ └── Water? → + water
│ ├── DIA/SWATH/diaPASEF? → + dia-acquisition
│ ├── Single-cell proteomics? → + single-cell
│ ├── MHC/immunopeptidome? → + immunopeptidomics
│ └── Cross-linking MS? → + crosslinking
│
└── NO (affinity-based) → affinity-proteomics
├── Olink? → + olink
└── SomaScan? → + somascan
When templates are combined, the validator merges all columns from all ancestors. If a parent says OPTIONAL but a child says REQUIRED → REQUIRED wins (strictest requirement).
Read templates.yaml to see the full inheritance tree via the extends field on each template.
The general structure is:
base → sample-metadata → technology + organism + experiment templatesbase → metaproteomics → environment-specific templates (excludes sample-metadata)| Experiment Type | Templates |
|---|---|
| Human tissue DDA (label-free or TMT) | ms-proteomics, human |
| Human cancer clinical trial | ms-proteomics, human, clinical-metadata, oncology-metadata |
| Mouse tissue DIA | ms-proteomics, vertebrates, dia-acquisition |
| Human cell line study | ms-proteomics, human, cell-lines |
| Single-cell proteomics (human) | ms-proteomics, human, single-cell |
| Immunopeptidomics (human) | ms-proteomics, human, immunopeptidomics |
| Cross-linking MS (human) | ms-proteomics, human, crosslinking |
| Gut metaproteomics | ms-proteomics, metaproteomics, human-gut |
| Soil metaproteomics | ms-proteomics, metaproteomics, soil |
| Olink plasma study | affinity-proteomics, human, olink |
| SomaScan serum study | affinity-proteomics, human, somascan |
| Drosophila DDA | ms-proteomics, invertebrates |
| Arabidopsis study | ms-proteomics, plants |
| Drug treatment study (human cells) | ms-proteomics, human, clinical-metadata, cell-lines |
When an SDRF file already exists, detect templates from:
comment[sdrf template] → e.g., NT=ms-proteomics;VV=v1.1.0characteristics[organism] → Homo sapiens = human, Mus musculus = vertebratescomment[proteomics data acquisition method] → DIA = dia-acquisitioncharacteristics[cell line] → cell-linescharacteristics[mhc protein complex] → immunopeptidomicscomment[cross-linker] → crosslinkingcharacteristics[single cell isolation protocol] → single-cellcharacteristics[environmental sample type] → metaproteomicscharacteristics[tumor grading] → oncology-metadatacomment[panel name] (or legacy comment[olink panel]) → olinkcomment[somascan menu] → somascantemplates.yaml to confirm templates exist and get current versionstemplates.yaml for version, extends, excludes, descriptionCompare side by side — read both template YAMLs for their column lists.
Auto-detect from the content using the detection rules above.
Independently falsify and review a created, modified, or proposed SDRF against its specification, ontology terms, source evidence, repository files, and experimental design. Use after SDRF annotation or repair, before contribution or completion, when a review gate reports a pending artifact, or whenever an isolated reviewer must distrust the producer's self-assessment and issue a hash-bound verdict.
Create or improve an SDRF through a producer-reviewer workflow with deterministic validation, an evidence manifest, fresh-context adversarial review, repair, and mandatory re-review. Use when an SDRF must be independently verified before completion or contribution, when the user requests adversarial review, or when automated review hooks require a passing hash-bound receipt.
Use when the user wants SDRF annotation to run as an autonomous retained-improvement loop over one dataset, a manifest, or a dataset class such as all PRIDE cell line or crosslinking datasets.
Use when the user has a completed SDRF annotation for a ProteomeXchange dataset and wants to contribute it back to the community via a PR to sdrf-annotated-datasets.
Use when the user wants a comprehensive quality review of an SDRF file, a PR review of an SDRF submission, or a quality score assessment.
Use before sdrf:autoresearch when the user needs to screen or shortlist proteomics studies from PRIDE, MassIVE, ProteomeXchange accessions, or a manifest using detailed user-defined inclusion/exclusion criteria; extract study-level metadata from repository records and publications; and write an evidence-backed TSV for downstream annotation, review, or meta-analysis.