dismech-terms

name

dismech-terms

description

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 anatomical entities). Use this skill when adding phenotype_term, cell_types term, biological_processes term, or other ontology-bound fields to disorder files.

Dismech Ontology Terms Skill

Overview

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.

When to Use

• Adding phenotype_term to phenotype entries (uses HP - Human Phenotype Ontology)
• Adding term to cell_types entries (uses CL - Cell Ontology)
• Adding term to biological_processes entries (uses GO - Gene Ontology)
• Adding disease_term to disease entries (uses MONDO)
• Validating existing ontology term references
• Fixing label mismatches between preferred_term and ontology labels

Term Object Structure

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>

Ontology Lookup with OAK

Use the Ontology Access Kit (OAK) to look up terms:

Exact Match

uv run runoak -i sqlite:obo:hp info "seizure"
# Returns: HP:0001250 ! Seizure

Fuzzy Search

uv run runoak -i sqlite:obo:hp info "l~cognitive impairment"
# Returns multiple matches - select the most appropriate

Get Full Term Details

uv run runoak -i sqlite:obo:cl info CL:0000540 -O obo
# Returns complete term information including definition

Common Ontology Prefixes

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

Specificity Guidelines

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:

1. Review all candidates
2. Check term definitions with -O obo flag
3. Select the term that most precisely matches the biological context
4. If no specific term exists, use the closest parent but note the limitation

Validation

After adding terms, validate with:

just validate-terms

This checks:

• Term IDs exist in the ontology
• Labels match the canonical ontology labels exactly
• Required fields are present

Fixing Label Mismatches

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.

Batch Processing

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")

Common Patterns

Adding HPO to a Phenotype

1. Look up term: uv run runoak -i sqlite:obo:hp info "l~<phenotype name>"
2. Verify specificity: uv run runoak -i sqlite:obo:hp info <HP:ID> -O obo
3. Add to YAML:

   phenotype_term:
     preferred_term: <Original Name>
     term:
       id: <HP:ID>
       label: <Exact label from OAK>
   

4. Validate: just validate-terms

Descriptor Qualifiers for Common Clinical Modifiers

When a base ontology term needs common clinical qualification, prefer the explicit descriptor slots instead of the deprecated generic qualifiers list:

phenotype_term:
  preferred_term: Diarrhea
  term:
    id: HP:0002014
    label: Diarrhea
  temporality: CHRONIC

phenotype_term:
  preferred_term: Muscle weakness
  term:
    id: HP:0001324
    label: Muscle weakness
  clinical_course: PROGRESSIVE

phenotype_term:
  preferred_term: Meningitis
  term:
    id: HP:0001287
    label: Meningitis
  severity: SEVERE
  onset:
    onset_category: NEONATAL

Enum values with ontology meaning mappings:

• temporality: ACUTE = HP:0011009, TRANSIENT = HP:0025153, SUBACUTE = HP:0011011, CHRONIC = HP:0011010, RECURRENT = HP:0031796, DIURNAL = HP:0025302, NOCTURNAL = HP:0025301, PROLONGED = HP:0025297
• clinical_course: PROGRESSIVE = HP:0003676, STABLE = HP:0031915
• severity: MILD = HP:0012825, MODERATE = HP:0012826, SEVERE = HP:0012828

Prefer a precoordinated ontology term when one already exists; otherwise add the qualifier in these dedicated slots.

Adding CL to Cell Types

1. Look up term: uv run runoak -i sqlite:obo:cl info "l~<cell type>"
2. Verify specificity
3. Add term: block under the cell_type entry
4. Validate