Update phenotype docs

docs/reference/data-integration.md

@@ -0,0 +1,7 @@
+## Integrating phenotype data using the uPheno framework
+
+
+### Level 1 integration: Data
+
+
+### Level 2 integration: Knowledge

docs/reference/phenotype-data.md

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+## Phenotype Data in practice
+
+Goals of this section:
+
+- Give a sense of the contexts in which phenotype data is produced (research and clinical)
+- Give a sense of the shape of different styles of phenotype data
+
+### Some examples of phenotype data
+
+### Different shapes of phenotype data
+
+#### Pre-coordinated
+
+- HPO during clinical phenotyping
+- Mouse phenotypes
+
+#### Post-coordinated
+
+- Trait + modifier
+- Bearer only
+- Characteristics + modifier + bearer
+- Complex bearers
+
+#### Standardised/non-standardized
+
+#### Quantitative/qualitative

docs/reference/use_cases.md → docs/reference/use-cases.md

@@ -5,3 +5,8 @@
 - Cross-species inference in Variant and Gene Prioritisation algorithms (Exomiser).
 - Cross-species comparison of phenotypic profiles (Monarch Initiative Knowledge Graph)
 - Cross-species data in biomedical knowledge graphs (Kids First)
+
+
+- Association prediction
+- Phenotypic profile matching
+- Data aggregation

docs/tutorials/curation.md

@@ -7,22 +7,9 @@ Authors:
 
 Last update: 27.03.2024.
 
-## Overview
-
-Phenotyping is, in essence, the process of recording the observable characteristics, or phenotypic profile, of an organism. 
-There are many use cases for doing this task: clinicians have to record a patient's phenotypic profile to facilitate more accurate diagnosis. 
-Researchers have to record phenotypic profiles of model organisms to characterise them to assess interventions (genetic or drug or otherwise). 
-Curators that seek to build a knowledge base which contains associations between phenotypes and other data types need to extract information about phenotypes from often unstructured data sources. 
-
-All of these are different processes, but the essence is the same: a set of observable characteristics has to be recorded using terms from a controlled vocabulary.
-
-There are different schools about how to record phenotypes in a structured manner. 
-Quantified phenotypes can be recorded using either a trait in combination with a measurement datum (“head circumference”, “35 cm”) or a qualified term expressing “phenotypic change” (“increased head circumference”). 
-Furthermore, we can express phenotype terms as “pre-coordinated” terms, like “increased head circumference” or a “post-coordinated expression”, like “head”, “circumference”, “increased”). In the following, we will describe the different concepts and categories around phenotype data, and provide an introduction on how to best use them.
-
 ## Pre-requisites
 
-- [Familiarise yourself with the core concepts](../reference/core_concepts.md)
+- [Familiarise yourself with the core concepts](../reference/core-concepts.md)
 
 ## Examples of phenotype data
 

mkdocs.yaml

@@ -33,13 +33,14 @@ nav:
       - Using uPheno in Curation: tutorials/curation.md
       - Using uPheno for Grouping Data: tutorials/grouping.md
   - Reference:
-    - Core concepts: reference/core_concepts.md
+    - Core concepts: reference/core-concepts.md
+    - Phenotype data: reference/phenotype-data.md
     - EQ modelling:
       - Overview of EQ modelling: reference/eq.md
       - Abnormal phenotypes: reference/modelling/abnormal.md 
       - Absence modelling: reference/modelling/absence.md
-    - The Phenotype Reconciliation Effort: reference/reconciliation_effort.md
-    - Use Cases: reference/use_cases.md
+    - The Phenotype Reconciliation Effort: reference/reconciliation-effort.md
+    - Use Cases: reference/use-cases.md
     - Components:
       - Overview: reference/components.md
       - Drosophila Phenotype Ontology: reference/components/dpo.md