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Merge pull request #936 from obophenotype/upheno-docs
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Update phenotype docs
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matentzn authored Mar 30, 2024
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7 changes: 7 additions & 0 deletions docs/reference/data-integration.md
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## Integrating phenotype data using the uPheno framework


### Level 1 integration: Data


### Level 2 integration: Knowledge
26 changes: 26 additions & 0 deletions 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
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5 changes: 5 additions & 0 deletions docs/reference/use_cases.md → docs/reference/use-cases.md
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- 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
15 changes: 1 addition & 14 deletions docs/tutorials/curation.md
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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

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- 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
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