Loading ontology requires that you know how to login to DeltaBreed test servers, create programs and add users, manage programs, use the germplasm template, append germplasm, and use the germplasm detail viewer with pedigree connections. If you need to review previous training modules, return to the main DeltaBreed training page.
In this training module, you will learn:
Why your program needs an ontology.
How to get started building an ontology.
How to use the ontology template to upload a list of ontology terms.
How to add an individual ontology term.
How to search for ontology terms.
Trait Ontology is a controlled vocabulary used to describe and codify a collection of phenotypic traits in breeding programs. In DeltaBreed, ontology is defined as a controlled vocabulary to support the standardization of observation variables (or ontology terms) so that breeding data are unambiguous, interoperable and reusable. DeltaBreed follows the cropontology.org conceptual model that defines variables as a combination of a trait, a method and a scale. Note: breeders may use the term “trait” interchangeably with observation variable or phenotype, but DeltaBreed uses the term “trait” more specifically and the ontology is designed to manage any type of observation variable, not just phenotypes.
Setting and using Trait Ontologies are vitally important to allow:
• Databases to correctly store and use phenotypic data across years/trials/locations.
• Consistent collection of phenotypic data from person-to-person and program-to-program.
• Sharing and interpretation of data and resources between breeders and breeding programs.
Reach out to your BI Coordinator! They are a great resource to help you get started.
Consider working with other breeding programs of the same species to see if they already have a working ontology.
Use the following resources to see if they might help you define some ontology terms your breeding program often uses.
Plant resources
Crop ontology (DeltaBreed ontology is built off of this model): http://www.cropontology.org/
Plants: http://browser.planteome.org/amigo
Animal resources
Vertebrates: https://www.animalgenome.org/bioinfo/projects/vt/
Livestock products (cattle, chicken, pig, etc.): https://www.animalgenome.org/bioinfo/projects/lpt/
Animal Clinical Measurements: https://www.animalgenome.org/bioinfo/projects/cmo/
Invertebrates: http://www.ontobee.org/
When phenotyping, quantitative variables should always be a breeder preference, because quantitative measures are the best way to characterize quantitative traits and support parametric statistical inference. DeltaBreed supports both qualitative (nominal) and quantitative (ordinal) categorical variables. Nominal variables are described by 1-n categories. Ordinal variables are described by 2-n categories with their corresponding value ranges in DeltaBreed.
Best Practice
When phenotyping use a quantitative variable when possible.
If a categorical phenotype is quantitative, create an ordinal variable.
To avoid ambiguity you must define both the category and the value range ordinal traits.
If you having a hard time assigning values to your categories, consider using fewer categories. Using fewer categories (<6) has been shown to be a good compromise between accuracy and error. (See more about this concept below.)
If you are curating an historical dataset, where values are unknown for an ordinal categories, you will need to create a nominal variable. Once you have loaded the historical data, consider archiving this variable and creating a new ordinal variable to use moving forward.
The DeltaBreed ontology template requires a scale class for an ordinal ontology trait. There is debate amongst breeders and scientist as to whether the 1-9 ordinal scale is the most accurate way to define this type of unit. Although DeltaBreed allows for a 1-9 scale, we suggest best practice might be something different.
This quote comes from "Understanding the ramifications of quantitative ordinal scales on accuracy of estimates of disease severity and data analysis in plant pathology." Kuo-Szu Chiang and Clive H. Bock, published July 13, 2021
This quote comes from "Using visual scores for genomic prediction of complex traits in breeding programs." Camila Ferreira Azevedo, Luis Felipe Ventorim Ferrão, Juliana Benevenuto, Marcos Deon Vilela de Resende, Moyses Nascimento, Ana Carolina Campana Nascimento, Patricio R. Munoz, published December 15, 2023
Please note that germplasm and ontology must be uploaded into DeltaBreed before you attempt to upload experiments, observations or sample submissions. DeltaBreed uses ontology and germplasm details to validate experiments & observations.
Learning Link: using a new ontology template that you downloaded from DeltaBreed, use the following oat ontology methods to craft a list of oat ontologies and practice using the template. You can find the terms at Crop Ontology, but will need to use your knowledge of plant breeding to determine some of the ontology details that you need in order to successfully upload a batch ontology file into DeltaBreed.
Abiotic Stress > Frost Tolerance - Estimation
Agronomic > Above ground bio mass - Measurement
Biochemical > Groat protein content- Determination
Biotic Stress > Fusarium foot rot severity - Estimation
Morphological > Grain Color - Estimation
Congrats! You've completed the Ontology training module. Close this browser tab to return to the main training page
or,
Head to the next module: Experiments and Observations.