xiaohongshu
xiaohongshu
dismech-terms
Skill for adding and validating ontology term references in the dismech knowledge base. This skill should be used when working with disorder YAML files that need ontology term annotations (HPO for phenotypes, CL for cell types, GO for biological processes, MONDO for diseases, UBERON for anatomica...
Full skill instructions
Add and validate ontology term references in the dismech disorder knowledge base. This ensures phenotypes, cell types, biological processes, and other entities are properly linked to authoritative ontology terms with correct IDs and labels.
phenotype_term to phenotype entries (uses HP - Human Phenotype Ontology)term to cell_types entries (uses CL - Cell Ontology)term to biological_processes entries (uses GO - Gene Ontology)disease_term to disease entries (uses MONDO)All term references follow this YAML structure:
# For phenotypes:
phenotype_term:
preferred_term: <Human readable name>
term:
id: HP:XXXXXXX
label: <Exact HP label from ontology>
# For cell types:
cell_types:
- preferred_term: <Human readable name>
term:
id: CL:XXXXXXX
label: <Exact CL label from ontology>
# For biological processes:
biological_processes:
- preferred_term: <Human readable name>
term:
id: GO:XXXXXXX
label: <Exact GO label from ontology>
Use the Ontology Access Kit (OAK) to look up terms:
uv run runoak -i sqlite:obo:hp info "seizure"
# Returns: HP:0001250 ! Seizure
uv run runoak -i sqlite:obo:hp info "l~cognitive impairment"
# Returns multiple matches - select the most appropriate
uv run runoak -i sqlite:obo:cl info CL:0000540 -O obo
# Returns complete term information including definition
| Ontology | Prefix | Adapter | Use For |
|---|---|---|---|
| Human Phenotype | HP | sqlite:obo:hp | phenotype_term |
| Cell Ontology | CL | sqlite:obo:cl | cell_types |
| Gene Ontology | GO | sqlite:obo:go | biological_processes |
| MONDO Disease | MONDO | sqlite:obo:mondo | disease_term |
| Uberon Anatomy | UBERON | sqlite:obo:uberon | anatomical locations |
Critical: Always use the most specific term that accurately describes the entity:
| Incorrect (too general) | Correct (specific) |
|---|---|
| CL:0000066 epithelial cell | CL:0002202 epithelial cell of tracheobronchial tree |
| HP:0000001 All | HP:0001250 Seizure |
| CL:0000000 cell | CL:0000540 neuron |
When a fuzzy search returns multiple results:
-O obo flagAfter adding terms, validate with:
just validate-terms
This checks:
If validation reports a label mismatch:
LABEL MISMATCH: Cholera.yaml
Term: HP:0003394
Expected: Muscle cramps
Actual: Muscle spasm
Update the label field to match the ontology's canonical label exactly.
To find entries missing term annotations:
import yaml
import glob
for f in glob.glob("kb/disorders/*.yaml"):
with open(f) as file:
data = yaml.safe_load(file)
for pheno in data.get('phenotypes', []):
if 'phenotype_term' not in pheno:
print(f"{f}: {pheno.get('name')} - missing phenotype_term")
uv run runoak -i sqlite:obo:hp info "l~<phenotype name>"uv run runoak -i sqlite:obo:hp info <HP:ID> -O obophenotype_term:
preferred_term: <Original Name>
term:
id: <HP:ID>
label: <Exact label from OAK>
just validate-termsuv run runoak -i sqlite:obo:cl info "l~<cell type>"term: block under the cell_type entryxiaohongshu
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