The uPheno project aims to unify the annotation of phenotypes across species in a manner analogous to unification of gene function annotation by the Gene Ontology.
+uPheno 2.0 builds on earlier efforts with a strategy that directly leverages the work of the phenotype ontology development community and incorporates phenotypes from a much wider range of species.
+We have organised a collaborative community effort, including representatives of all major model organism databases, to document and align formal design patterns for representing phenotypes and further develop reference ontologies, such as PATO, which are used in these patterns.
+A common development infrastructure makes it easy to use these design patterns to generate both species-specific ontologies and a species-independent layer that subsumes them.
+The resulting community-curated ontology for the representation and integration of phenotypes across species serves two general purposes:
+- Providing a community-developed framework for ontology editors to bootstrap, maintain and extend their phenotype ontologies in a scalable and standardised manner.
+- Facilitating the retrieval and comparative analysis of species-specific phenotypes through a deep layer of species-independent phenotypes.
Currently, the development of uPheno is organized by a group that meets biweekly. See the meetings page for more info, including how to participate.
+ + + + + + +EQ definitions are powerful tools for reconciling phenotypes across species and driving reasoning. However, they are not all that useful for many "normal" users of our ontologies.
+We have developed a little workflow extension to take care of that.
+src/ontology/mp-odk.yaml):components:
+ products:
+ - filename: eq-relations.owl
+http://purl.obolibrary.org/obo/YOURONTOLOGY/components/eq-relations.owl. For example, for MP, the IRI is http://purl.obolibrary.org/obo/mp/components/eq-relations.owl.sh run.sh make components/eq-relations.owl
+This command will be run automatically during a release (prepare_release).
The custom uPheno Makefile is an extension to your normal custom Makefile (for example, hp.Makefile, mp.Makefile, etc), located in the src/ontology directory of your ODK set up.
+To install it:
+(1) Open your normal custom Makefile and add a line in the very end:
+include pheno.Makefile
+(2) Now download the custom Makefile:
+https://raw.githubusercontent.com/obophenotype/upheno/master/src/ontology/config/pheno.Makefile
+and save it in your src/ontology directory.
Feel free to use, for example, wget:
+cd src/ontology
+wget https://raw.githubusercontent.com/obophenotype/upheno/master/src/ontology/config/pheno.Makefile -O pheno.Makefile
+From now on you can simply run
+sh run.sh make update_pheno_makefile
+whenever you wish to synchronise the Makefile with the uPheno repo.
+(Note: it would probably be good to add a GitHub action that does that automatically.)
+ + + + + + +brew install yamllintCongiguring yamllint
+ You can ignore the error line too long yaml syntax errors for dos-dp yaml templates.
+ You can create a custom configuration file for yamllint in your home folder:
+ sh
+ touch ~/.config/yamllint/config
+ The content of the config file should look like this:
+ ```yaml
+ # Custom configuration file for yamllint
+ # It extends the default conf by adjusting some options.
extends: default
+rules: + line-length: + max: 80 # 80 chars should be enough, but don't fail if a line is longer
+level: warning
+allow-non-breakable-words: true
+allow-non-breakable-inline-mappings: true
+``
+The custom config should turn theerror line too longerrors to warnings.
+ 2. [DOS-DP validator:](https://incatools.github.io/dead_simple_owl_design_patterns/validator/): DOS-DP format validator
+* [Installing ](https://github.com/INCATools/dead_simple_owl_design_patterns):pip install dosdp`
Patternisation is the process of ensuring that all entity quality (EQ) descriptions from textual phenotype term definitions have a logical definition pattern. A pattern is a standard format for describing a phenotype that includes a quality and an entity. For example, "increased body size" is a pattern that includes the quality "increased" and the entity "body size." The goal of patternisation is to make the EQ descriptions more uniform and machine-readable, which facilitates downstream analysis.
+The first step in the Phenotype Ontology Editors' Workflow is to identify a group of related phenotypes from diverse organisms. This can be done by considering proposals from phenotype editors or by using the pattern suggestion pipeline. +The phenotype editors may propose a group of related phenotypes based on their domain knowledge, while the pattern suggestion pipeline uses semantic similarity and shared Phenotype And Trait Ontology (PATO) quality terms to identify patterns in phenotype terms from different organism-specific ontologies.
+Once a group of related phenotypes is identified, the editors propose a phenotype pattern. To do this, they create a Github issue to request the phenotype pattern template in the uPheno repository. +Alternatively, a new template can be proposed at a phenotype editors' meeting which can lead to the creation of a new term request as a Github issue. +Ideally, the proposed phenotype pattern should include an appropriate PATO quality term for logical definition, use cases, term examples, and a textual definition pattern for the phenotype terms.
+The next step is to discuss the new phenotype pattern draft at the regular uPheno phenotype editors meeting. During the meeting, the editors' comments and suggestions for improvements are collected as comments on the DOS-DP yaml template in the corresponding Github pull request. Based on the feedback and discussions, a consensus on improvements should be achieved.
+The DOS-DP yaml template is named should start with a lower case letter, should be informative, and must include the PATO quality term.
+A Github pull request is created for the DOS-DP yaml template.
---
+pattern_name: ??pattern_and_file_name
+
+pattern_iri: http://purl.obolibrary.org/obo/upheno/patterns-dev/??pattern_and_file_name.yaml
+
+description: 'A description that helps people chose this pattern for the appropriate scenario.'
+
+# examples:
+# - example_IRI-1 # term name
+# - example_IRI-2 # term name
+# - example_IRI-3 # term name
+# - http://purl.obolibrary.org/obo/XXXXXXXXXX # XXXXXXXX
+
+contributors:
+ - https://orcid.org/XXXX-XXXX-XXXX-XXXX # Yyy Yyyyyyyyy
+
+classes:
+ process_quality: PATO:0001236
+ abnormal: PATO:0000460
+ anatomical_entity: UBERON:0001062
+
+relations:
+ characteristic_of: RO:0000052
+ has_modifier: RO:0002573
+ has_part: BFO:0000051
+
+annotationProperties:
+ exact_synonym: oio:hasExactSynonym
+ related_synonym: oio:hasRelatedSynonym
+ xref: oio:hasDbXref
+
+vars:
+ var??: "'anatomical_entity'" # "'variable_range'"
+
+name:
+ text: "trait ?? %s"
+ vars:
+ - var??
+
+annotations:
+ - annotationProperty: exact_synonym
+ text: "? of %s"
+ vars:
+ - var??
+
+ - annotationProperty: related_synonym
+ text: "? %s"
+ vars:
+ - var??
+
+ - annotationProperty: xref
+ text: "AUTO:patterns/patterns/chemical_role_attribute"
+
+def:
+ text: "A trait that ?? %s."
+ vars:
+ - var??
+
+equivalentTo:
+ text: "'has_part' some (
+ 'XXXXXXXXXXXXXXXXX' and
+ ('characteristic_of' some %s) and
+ ('has_modifier' some 'abnormal')
+ )"
+ vars:
+ - var??
+...
+Once a consensus on the improvements for a particular template is achieved, they are incorporated into the DOS-DP yaml file. Typically, the improvements are applied to the template some time before a subsequent ontology editor's meeting. There should be enough time for off-line review of the proposed pattern to allow community feedback.
+The improved phenotype pattern candidate draft should get approval from the community at one of the regular ontology editors' call or in a Github comment.
+The ontology editors who approve the pattern provide their ORCIDs and they are credited as contributors in an appropriate field of the DOS-DP pattern template.
Once the community-approved phenotype pattern template is created, it is added to the uPheno Github repository.
+The approved DOS-DP yaml phenotype pattern template should pass quality control (QC) steps.
+1. Validate yaml syntax: yamllint
+2. Validate DOS-DP
+Use DOSDP Validator.
+* To validate a template using the command line interface, execute:
+```sh
+yamllint
After successfully passing QC, the responsible editor merges the approved pull request, and the phenotype pattern becomes part of the uPheno phenotype pattern template collection.
+ + + + + + +This document is on how to merge new DOSDP design patterns into an ODK ontology and then how to replace the old classes with the new ones.
+$ODK-ONTOLOGY/src/patterns/data/default/
+Make sure that the tsv filenames match that of the relevant yaml DOSDP pattern files.
+$ODK-ONTOLOGY/src/patterns/dosdp-patterns/external.txt
+external.txt list from external sources into the current working repositorycd ODK-ONTOLOGY/src/ontology
+sh run.sh make update_patterns
+cd ODK-ONTOLOGY/src/ontology
+sh run.sh make ../patterns/definitions.owl IMP=false
+cd ODK-ONTOLOGY/src/ontology
+sh run.sh make remove_patternised_classes
+For example:
+++ + + + + + +I have migrated the ... table and changed the tab colour to blue. +You can delete the tab if you wish.
+
In order to run a release you will have to have completed the steps to set up s3.
+cd src/scriptssh upheno_pipeline.shcd ../ontologymake prepare_upload S3_VERSION=2022-06-19make deploy S3_VERSION=2022-06-19To be able to upload new uPheno release to the uPheno S3 bucket, you need to set yourself up for S3 first.
+ +The most convenient way to interact with S3 is the AWS Command Line Interface (CLI). You can find the installers and install instructions on that page (different depending on your Operation System): +- For Mac +- For Windows
+Next, you need to ask someone at BBOP (such as Chris Mungall or Seth Carbon) to provide you with an account that gives you access to the BBOP s3 buckets. You will have to provide a username. You will receive: +- User name +- Access key ID- +- Secret access key +- Console link to sign into bucket
+You will now have to set up your local system. You will create two files:
+$ less ~/.aws/config
+[default]
+region = us-east-1
+and
+$ less ~/.aws/credentials
+[default]
+aws_access_key_id = ***
+aws_secret_access_key = ***
+in ~/.aws/credentials make sure you add the correct keys as provided above.
Now, you should be set up to write to your s3 bucket. Note that in order for your data to be accessible through https after your upload, you need to add --acl public read.
aws s3 sync --exclude "*.DS_Store*" my/data-dir s3://bbop-ontologies/myproject/data-dir --acl public-read
+If you have previously pushed data to the same location, you wont be able to set it to "publicly readable" by simply rerunning the sync command. If you want to publish previously private data, follow the instructions here, e.g.:
+aws s3api put-object-acl --bucket s3://bbop-ontologies/myproject/data-dir --key exampleobject --acl public-read
+Welcome to the UPHENO documentation!
+It is entirely empty at the moment so look no further!
+You can find descriptions of the standard ontology engineering workflows here.
+ + + + + + +Historically, most repos have been using Travis CI for continuous integration testing and building, but due to +runtime restrictions, we recently switched a lot of our repos to GitHub actions. You can set up your repo with CI by adding +this to your configuration file (src/ontology/upheno-odk.yaml):
+ci:
+ - github_actions
+When updateing your repo, you will notice a new file being added: .github/workflows/qc.yml.
This file contains your CI logic, so if you need to change, or add anything, this is the place!
+Alternatively, if your repo is in GitLab instead of GitHub, you can set up your repo with GitLab CI by adding +this to your configuration file (src/ontology/upheno-odk.yaml):
+ci:
+ - gitlab-ci
+This will add a file called .gitlab-ci.yml in the root of your repo.
The editors workflow is one of the formal workflows to ensure that the ontology is developed correctly according to ontology engineering principles. There are a few different editors workflows:
+This document only covers the first editing workflow, but more will be added in the future
+Workflow requirements:
+Ensure that there is a ticket on your issue tracker that describes the change you are about to make. While this seems optional, this is a very important part of the social contract of building an ontology - no change to the ontology should be performed without a good ticket, describing the motivation and nature of the intended change.
+In your local environment (e.g. your laptop), make sure you are on the main (prev. master) branch and ensure that you have all the upstream changes, for example:
git checkout master
+git pull
+Create a new branch. Per convention, we try to use meaningful branch names such as: +- issue23removeprocess (where issue 23 is the related issue on GitHub) +- issue26addcontributor +- release20210101 (for releases)
+On your command line, this looks like this:
+git checkout -b issue23removeprocess
+Using your editor of choice, perform the intended edit. For example:
+Protégé
+src/ontology/upheno-edit.owl in ProtégéTextEdit
+src/ontology/upheno-edit.owl in TextEdit (or Sublime, Atom, Vim, Nano)Consider the following when making the edit.
+src/ontology/upheno-edit.owlsrc/ontology/components), see here.This step is very important. Rather than simply trusting your change had the intended effect, we should always use a git diff as a first pass for sanity checking.
+In our experience, having a visual git client like GitHub Desktop or sourcetree is really helpful for this part. In case you prefer the command line:
+git status
+git diff
+Now it's time to run your quality control checks. This can either happen locally (5a) or through your continuous integration system (7/5b).
+If you chose to run your test locally:
+sh run.sh make IMP=false test
+This will run the whole set of configured ODK tests on including your change. If you have a complex DOSDP pattern pipeline you may want to add PAT=false to skip the potentially lengthy process of rebuilding the patterns.
sh run.sh make IMP=false PAT=false test
+When you are happy with the changes, you commit your changes to your feature branch, push them upstream (to GitHub) and create a pull request. For example:
+git add NAMEOFCHANGEDFILES
+git commit -m "Added biological process term #12"
+git push -u origin issue23removeprocess
+Then you go to your project on GitHub, and create a new pull request from the branch, for example: https://github.com/INCATools/ontology-development-kit/pulls
+There is a lot of great advise on how to write pull requests, but at the very least you should:
+- mention the tickets affected: see #23 to link to a related ticket, or fixes #23 if, by merging this pull request, the ticket is fixed. Tickets in the latter case will be closed automatically by GitHub when the pull request is merged.
+- summarise the changes in a few sentences. Consider the reviewer: what would they want to know right away.
+- If the diff is large, provide instructions on how to review the pull request best (sometimes, there are many changed files, but only one important change).
If you didn't run and local quality control checks (see 5a), you should have Continuous Integration (CI) set up, for example: +- Travis +- GitHub Actions
+More on how to set this up here. Once the pull request is created, the CI will automatically trigger. If all is fine, it will show up green, otherwise red.
+Once all the automatic tests have passed, it is important to put a second set of eyes on the pull request. Ontologies are inherently social - as in that they represent some kind of community consensus on how a domain is organised conceptually. This seems high brow talk, but it is very important that as an ontology editor, you have your work validated by the community you are trying to serve (e.g. your colleagues, other contributors etc.). In our experience, it is hard to get more than one review on a pull request - two is great. You can set up GitHub branch protection to actually require a review before a pull request can be merged! We recommend this.
+This step seems daunting to some hopefully under-resourced ontologies, but we recommend to put this high up on your list of priorities - train a colleague, reach out!
+When the QC is green and the reviews are in (approvals), it is time to merge the pull request. After the pull request is merged, remember to delete the branch as well (this option will show up as a big button right after you have merged the pull request). If you have not done so, close all the associated tickets fixed by the pull request.
+It is sometimes difficult to keep track of changes made to an ontology. Some ontology teams opt to document changes in a changelog (simply a text file in your repository) so that when release day comes, you know everything you have changed. This is advisable at least for major changes (such as a new release system, a new pattern or template etc.).
+ + + + + + +We can define custom checks using SPARQL. SPARQL queries define bad modelling patterns (missing labels, misspelt URIs, and many more) in the ontology. If these queries return any results, then the build will fail. Custom checks are designed to be run as part of GitHub Actions Continuous Integration testing, but they can also run locally.
+src/sparql. The name of the file should end with -violation.sparql. Please give a name that helps to understand which violation the query wants to check.src/ontology/uberon-odk.yaml:-violation.sparql part) to the list inside the key custom_sparql_checks that is inside robot_report key.If the robot_report or custom_sparql_checks keys are not available, please add this code block to the end of the file.
yaml
+ robot_report:
+ release_reports: False
+ fail_on: ERROR
+ use_labels: False
+ custom_profile: True
+ report_on:
+ - edit
+ custom_sparql_checks:
+ - name-of-the-file-check
+3. Update the repository so your new SPARQL check will be included in the QC.
sh run.sh make update_repo
+The documentation for UPHENO is managed in two places (relative to the repository root):
+docs directory contains all the files that pertain to the content of the documentation (more below)mkdocs.yaml file contains the documentation config, in particular its navigation bar and theme.The documentation is hosted using GitHub pages, on a special branch of the repository (called gh-pages). It is important that this branch is never deleted - it contains all the files GitHub pages needs to render and deploy the site. It is also important to note that the gh-pages branch should never be edited manually. All changes to the docs happen inside the docs directory on the main branch.
All the documentation is contained in the docs directory, and is managed in Markdown. Markdown is a very simple and convenient way to produce text documents with formatting instructions, and is very easy to learn - it is also used, for example, in GitHub issues. This is a normal editing workflow:
.md file you want to change in an editor of choice (a simple text editor is often best). IMPORTANT: Do not edit any files in the docs/odk-workflows/ directory. These files are managed by the ODK system and will be overwritten when the repository is upgraded! If you wish to change these files, make an issue on the ODK issue tracker.The documentation is not automatically updated from the Markdown, and needs to be deployed deliberately. To do this, perform the following steps:
+cd upheno/src/ontologysh run.sh make update_docs
+ Mkdocs now sets off to build the site from the markdown pages. You will be asked toIf everything was successful, you will see a message similar to this one:
+INFO - Your documentation should shortly be available at: https://obophenotype.github.io/upheno/
+3. Just to double check, you can now navigate to your documentation pages (usually https://obophenotype.github.io/upheno/).
+ Just make sure you give GitHub 2-5 minutes to build the pages!
The release workflow recommended by the ODK is based on GitHub releases and works as follows:
+These steps are outlined in detail in the following.
+Preparation:
+git status should say that there are no modified files)git pull)git checkout -b release-2021-01-01)docker pull obolibrary/odkfullTo actually run the release, you:
+cd upheno/src/ontology)sh run.sh make prepare_release -B. Note that for some ontologies, this process can take up to 90 minutes - especially if there are large ontologies you depend on, like PRO or CHEBI.Release files are now in ../.. - now you should commit, push and make a release on your git hosting site such as GitHub or GitLab.This will create all the specified release targets (OBO, OWL, JSON, and the variants, ont-full and ont-base) and copy them into your release directory (the top level of your repo).
+upheno.obo - this reflects a useful subset of the whole ontology (everything that can be covered by OBO format). OBO format has that speaking for it: it is very easy to review!upheno-base.owl - this reflects the asserted axioms in your ontology that you have actually edited.upheno-full.owl, which may reveal interesting new inferences you did not know about. Note that the diff of this file is sometimes quite large.Once your CI checks have passed, and your reviews are completed, you can now merge the branch into your main branch (don't forget to delete the branch afterwards - a big button will appear after the merge is finished).
+upheno.obo file and check the data-version: property. The date needs to be prefixed with a v, so, for example v2020-02-06.When you are dealing with large ontologies, you need a lot of memory. When you see error messages relating to large ontologies such as CHEBI, PRO, NCBITAXON, or Uberon, you should think of memory first, see here.
+Sometimes you will get cryptic error messages when using legacy tools using OBO format, such as the ontology release tool (OORT), which is also available as part of the ODK docker container. In these cases, you need to track down what axiom or annotation actually caused the breakdown. In our experience (in about 60% of the cases) the problem lies with duplicate annotations (def, comment) which are illegal in OBO. Here is an example recipe of how to deal with such a problem:
make: *** [cl.Makefile:84: oort] Error 255 you might have a OORT error. sh run.sh make IMP=false PAT=false oort -B (assuming you are already in the ontology folder in your directory) upheno-edit.owl in Protégé and find the offending term and delete all offending issue (e.g. delete ALL definition, if the problem was "multiple def tags not allowed") and save.
+*While this is not idea, as it will remove all definitions from that term, it will be added back again when the term is fixed in the ontology it was imported from and added back in.sh run.sh make IMP=false PAT=false oort -B and if it all passes, commit your changes to a branch and make a pull request as usual.Your ODK repositories configuration is managed in src/ontology/upheno-odk.yaml. Once you have made your changes, you can run the following to apply your changes to the repository:
sh run.sh make update_repo
+There are a large number of options that can be set to configure your ODK, but we will only discuss a few of them here.
+NOTE for Windows users:
+You may get a cryptic failure such as Set Illegal Option - if the update script located in src/scripts/update_repo.sh
+was saved using Windows Line endings. These need to change to unix line endings. In Notepad++, for example, you can
+click on Edit->EOL Conversion->Unix LF to change this.
You can use the update repository workflow described on this page to perform the following operations to your imports:
+We will discuss all these workflows in the following.
+To add a new import, you first edit your odk config as described above, adding an id to the product list in the import_group section (for the sake of this example, we assume you already import RO, and your goal is to also import GO):
import_group:
+ products:
+ - id: ro
+ - id: go
+Note: our ODK file should only have one import_group which can contain multiple imports (in the products section). Next, you run the update repo workflow to apply these changes. Note that by default, this module is going to be a SLME Bottom module, see here. To change that or customise your module, see section "Customise an import". To finalise the addition of your import, perform the following steps:
src/ontology/upheno-edit.owl file. We suggest to do this using a text editor, by simply copying an existing import declaration and renaming it to the new ontology import, for example as follows:
+ ...
+ Ontology(<http://purl.obolibrary.org/obo/upheno.owl>
+ Import(<http://purl.obolibrary.org/obo/upheno/imports/ro_import.owl>)
+ Import(<http://purl.obolibrary.org/obo/upheno/imports/go_import.owl>)
+ ...src/ontology/catalog-v001.xml, for example:
+ <uri name="http://purl.obolibrary.org/obo/upheno/imports/go_import.owl" uri="imports/go_import.owl"/>Note: The catalog file src/ontology/catalog-v001.xml has one purpose: redirecting
+imports from URLs to local files. For example, if you have
Import(<http://purl.obolibrary.org/obo/upheno/imports/go_import.owl>)
+in your editors file (the ontology) and
+<uri name="http://purl.obolibrary.org/obo/upheno/imports/go_import.owl" uri="imports/go_import.owl"/>
+in your catalog, tools like robot or Protégé will recognize the statement
+in the catalog file to redirect the URL http://purl.obolibrary.org/obo/upheno/imports/go_import.owl
+to the local file imports/go_import.owl (which is in your src/ontology directory).
If you simply wish to refresh your import in light of new terms, see here. If you wish to change the type of your module see section "Customise an import".
+To remove an existing import, perform the following steps:
+src/ontology/upheno-edit.owl.src/ontology/upheno-odk.yaml, eg. - id: go from the list of products in the import_group.src/imports/go_import.owlsrc/imports/go_terms.txtsrc/ontology/catalog-v001.xml file.By default, an import module extracted from a source ontology will be a SLME module, see here. There are various options to change the default.
+The following change to your repo config (src/ontology/upheno-odk.yaml) will switch the go import from an SLME module to a simple ROBOT filter module:
import_group:
+ products:
+ - id: ro
+ - id: go
+ module_type: filter
+A ROBOT filter module is, essentially, importing all external terms declared by your ontology (see here on how to declare external terms to be imported). Note that the filter module does
+not consider terms/annotations from namespaces other than the base-namespace of the ontology itself. For example, in the
+example of GO above, only annotations / axioms related to the GO base IRI (http://purl.obolibrary.org/obo/GO_) would be considered. This
+behaviour can be changed by adding additional base IRIs as follows:
import_group:
+ products:
+ - id: go
+ module_type: filter
+ base_iris:
+ - http://purl.obolibrary.org/obo/GO_
+ - http://purl.obolibrary.org/obo/CL_
+ - http://purl.obolibrary.org/obo/BFO
+If you wish to customise your import entirely, you can specify your own ROBOT command to do so. To do that, add the following to your repo config (src/ontology/upheno-odk.yaml):
import_group:
+ products:
+ - id: ro
+ - id: go
+ module_type: custom
+Now add a new goal in your custom Makefile (src/ontology/upheno.Makefile, not src/ontology/Makefile).
imports/go_import.owl: mirror/ro.owl imports/ro_terms_combined.txt
+ if [ $(IMP) = true ]; then $(ROBOT) query -i $< --update ../sparql/preprocess-module.ru \
+ extract -T imports/ro_terms_combined.txt --force true --individuals exclude --method BOT \
+ query --update ../sparql/inject-subset-declaration.ru --update ../sparql/postprocess-module.ru \
+ annotate --ontology-iri $(ONTBASE)/$@ $(ANNOTATE_ONTOLOGY_VERSION) --output $@.tmp.owl && mv $@.tmp.owl $@; fi
+Now feel free to change this goal to do whatever you wish it to do! It probably makes some sense (albeit not being a strict necessity), to leave most of the goal instead and replace only:
+extract -T imports/ro_terms_combined.txt --force true --individuals exclude --method BOT \
+to another ROBOT pipeline.
+A component is an import which belongs to your ontology, e.g. is managed by +you and your team.
+src/ontology/upheno-odk.yamlcomponentscomponents section, add a new section called products.
+This is where all your components are specifiedproducts section, add a new component, e.g. - filename: mycomp.owlExample
+components:
+ products:
+ - filename: mycomp.owl
+When running sh run.sh make update_repo, a new file src/ontology/components/mycomp.owl will
+be created which you can edit as you see fit. Typical ways to edit:
components/mycomp.owl: make target in src/ontology/upheno.Makefile
+and provide a custom command to generate the componentWARNING: Note that the custom rule to generate the component MUST NOT depend on any other ODK-generated file such as seed files and the like (see issue).src/ontology/upheno-odk.yaml, source,
+to specify that this component should simply be downloaded from somewhere on the web.Since ODK 1.3.2, it is possible to simply link a ROBOT template to a component without having to specify any of the import logic. In order to add a new component that is connected to one or more template files, follow these steps:
+src/ontology/upheno-odk.yaml.use_templates: TRUE is set in the global project options. You should also make sure that use_context: TRUE is set in case you are using prefixes in your templates that are not known to robot, such as OMOP:, CPONT: and more. All non-standard prefixes you are using should be added to config/context.json.products section.use_template: TRUE. This will create an empty template for you in the templates directory, which will automatically be processed when recreating the component (e.g. run.bat make recreate-mycomp).templates field to add as many template names as you wish. ODK will look for them in the src/templates directory.template_options field. This should be a string with option from robot template. One typical example for additional options you may want to provide is --add-prefixes config/context.json to ensure the prefix map of your context is provided to robot, see above.Example:
+components:
+ products:
+ - filename: mycomp.owl
+ use_template: TRUE
+ template_options: --add-prefixes config/context.json
+ templates:
+ - template1.tsv
+ - template2.tsv
+Note: if your mirror is particularly large and complex, read this ODK recommendation.
+ + + + + + +The main kinds of files in the repository:
+Release file are the file that are considered part of the official ontology release and to be used by the community. A detailed description of the release artefacts can be found here.
+Imports are subsets of external ontologies that contain terms and axioms you would like to re-use in your ontology. These are considered "external", like dependencies in software development, and are not included in your "base" product, which is the release artefact which contains only those axioms that you personally maintain.
+These are the current imports in UPHENO
+| Import | +URL | +Type | +
|---|---|---|
| go | +https://raw.githubusercontent.com/obophenotype/pro_obo_slim/master/pr_slim.owl | +None | +
| nbo | +http://purl.obolibrary.org/obo/nbo.owl | +None | +
| uberon | +http://purl.obolibrary.org/obo/uberon.owl | +None | +
| cl | +http://purl.obolibrary.org/obo/cl.owl | +None | +
| pato | +http://purl.obolibrary.org/obo/pato.owl | +None | +
| mpath | +http://purl.obolibrary.org/obo/mpath.owl | +None | +
| ro | +http://purl.obolibrary.org/obo/ro.owl | +None | +
| omo | +http://purl.obolibrary.org/obo/omo.owl | +None | +
| chebi | +https://raw.githubusercontent.com/obophenotype/chebi_obo_slim/main/chebi_slim.owl | +None | +
| oba | +http://purl.obolibrary.org/obo/oba.owl | +None | +
| ncbitaxon | +http://purl.obolibrary.org/obo/ncbitaxon/subsets/taxslim.owl | +None | +
| pr | +https://raw.githubusercontent.com/obophenotype/pro_obo_slim/master/pr_slim.owl | +None | +
| bspo | +http://purl.obolibrary.org/obo/bspo.owl | +None | +
| ncit | +http://purl.obolibrary.org/obo/ncit.owl | +None | +
| fbbt | +http://purl.obolibrary.org/obo/fbbt.owl | +None | +
| fbdv | +http://purl.obolibrary.org/obo/fbdv.owl | +None | +
| hsapdv | +http://purl.obolibrary.org/obo/hsapdv.owl | +None | +
| wbls | +http://purl.obolibrary.org/obo/wbls.owl | +None | +
| wbbt | +http://purl.obolibrary.org/obo/wbbt.owl | +None | +
| plana | +http://purl.obolibrary.org/obo/plana.owl | +None | +
| zfa | +http://purl.obolibrary.org/obo/zfa.owl | +None | +
| xao | +http://purl.obolibrary.org/obo/xao.owl | +None | +
| hsapdv-uberon | +http://purl.obolibrary.org/obo/uberon/bridge/uberon-bridge-to-hsapdv.owl | +custom | +
| zfa-uberon | +http://purl.obolibrary.org/obo/uberon/bridge/uberon-bridge-to-zfa.owl | +custom | +
| zfs-uberon | +http://purl.obolibrary.org/obo/uberon/bridge/uberon-bridge-to-zfs.owl | +custom | +
| xao-uberon | +http://purl.obolibrary.org/obo/uberon/bridge/uberon-bridge-to-xao.owl | +custom | +
| wbbt-uberon | +http://purl.obolibrary.org/obo/uberon/bridge/uberon-bridge-to-wbbt.owl | +custom | +
| wbls-uberon | +http://purl.obolibrary.org/obo/uberon/bridge/uberon-bridge-to-wbls.owl | +custom | +
| fbbt-uberon | +http://purl.obolibrary.org/obo/uberon/bridge/uberon-bridge-to-fbbt.owl | +custom | +
| xao-cl | +http://purl.obolibrary.org/obo/uberon/bridge/cl-bridge-to-xao.owl | +custom | +
| wbbt-cl | +http://purl.obolibrary.org/obo/uberon/bridge/cl-bridge-to-wbbt.owl | +custom | +
| fbbt-cl | +http://purl.obolibrary.org/obo/uberon/bridge/cl-bridge-to-fbbt.owl | +custom | +
Components, in contrast to imports, are considered full members of the ontology. This means that any axiom in a component is also included in the ontology base - which means it is considered native to the ontology. While this sounds complicated, consider this: conceptually, no component should be part of more than one ontology. If that seems to be the case, we are most likely talking about an import. Components are often not needed for ontologies, but there are some use cases:
+These are the components in UPHENO
+| Filename | +URL | +
|---|---|
| phenotypes_manual.owl | +None | +
| upheno-mappings.owl | +None | +
| cross-species-mappings.owl | +None | +
One of the most frequent problems with running the ODK for the first time is failure because of lack of memory. This can look like a Java OutOfMemory exception,
+but more often than not it will appear as something like an Error 137. There are two places you need to consider to set your memory:
robot_java_args: '-Xmx8G' to your src/ontology/upheno-odk.yaml file, see for example here.robot_java_args variable. You can manage your memory settings
+by right-clicking on the docker whale in your system bar-->Preferences-->Resources-->Advanced, see picture below.
This page discusses how to update the contents of your imports, like adding or removing terms. If you are looking to customise imports, like changing the module type, see here.
+Note: some ontologies now use a merged-import system to manage dynamic imports, for these please follow instructions in the section title "Using the Base Module approach".
+Importing a new term is split into two sub-phases:
+There are three ways to declare terms that are to be imported from an external ontology. Choose the appropriate one for your particular scenario (all three can be used in parallel if need be):
+This workflow is to be avoided, but may be appropriate if the editor does not have access to the ODK docker container. +This approach also applies to ontologies that use base module import approach.
+
Now you can use this term for example to construct logical definitions. The next time the imports are refreshed (see how to refresh here), the metadata (labels, definitions, etc.) for this term are imported from the respective external source ontology and becomes visible in your ontology.
+Every import has, by default a term file associated with it, which can be found in the imports directory. For example, if you have a GO import in src/ontology/go_import.owl, you will also have an associated term file src/ontology/go_terms.txt. You can add terms in there simply as a list:
GO:0008150
+GO:0008151
+Now you can run the refresh imports workflow) and the two terms will be imported.
+This workflow is appropriate if:
+To enable this workflow, you add the following to your ODK config file (src/ontology/upheno-odk.yaml), and update the repository:
use_custom_import_module: TRUE
+Now you can manage your imported terms directly in the custom external terms template, which is located at src/templates/external_import.owl. Note that this file is a ROBOT template, and can, in principle, be extended to include any axioms you like. Before extending the template, however, read the following carefully.
The main purpose of the custom import template is to enable the management off all terms to be imported in a centralised place. To enable that, you do not have to do anything other than maintaining the template. So if you, say currently import APOLLO_SV:00000480, and you wish to import APOLLO_SV:00000532, you simply add a row like this:
ID Entity Type
+ID TYPE
+APOLLO_SV:00000480 owl:Class
+APOLLO_SV:00000532 owl:Class
+When the imports are refreshed see imports refresh workflow, the term(s) will simply be imported from the configured ontologies.
+Now, if you wish to extend the Makefile (which is beyond these instructions) and add, say, synonyms to the imported terms, you can do that, but you need to (a) preserve the ID and ENTITY columns and (b) ensure that the ROBOT template is valid otherwise, see here.
WARNING. Note that doing this is a widespread antipattern (see related issue). You should not change the axioms of terms that do not belong into your ontology unless necessary - such changes should always be pushed into the ontology where they belong. However, since people are doing it, whether the OBO Foundry likes it or not, at least using the custom imports module as described here localises the changes to a single simple template and ensures that none of the annotations added this way are merged into the base file.
+If you want to refresh the import yourself (this may be necessary to pass the travis tests), and you have the ODK installed, you can do the following (using go as an example):
+First, you navigate in your terminal to the ontology directory (underneath src in your hpo root directory).
+cd src/ontology
+Then, you regenerate the import that will now include any new terms you have added. Note: You must have docker installed.
+sh run.sh make PAT=false imports/go_import.owl -B
+Since ODK 1.2.27, it is also possible to simply run the following, which is the same as the above:
+sh run.sh make refresh-go
+Note that in case you changed the defaults, you need to add IMP=true and/or MIR=true to the command below:
sh run.sh make IMP=true MIR=true PAT=false imports/go_import.owl -B
+If you wish to skip refreshing the mirror, i.e. skip downloading the latest version of the source ontology for your import (e.g. go.owl for your go import) you can set MIR=false instead, which will do the exact same thing as the above, but is easier to remember:
sh run.sh make IMP=true MIR=false PAT=false imports/go_import.owl -B
+Since ODK 1.2.31, we support an entirely new approach to generate modules: Using base files. +The idea is to only import axioms from ontologies that actually belong to it. +A base file is a subset of the ontology that only contains those axioms that nominally +belong there. In other words, the base file does not contain any axioms that belong +to another ontology. An example would be this:
+Imagine this being the full Uberon ontology:
+Axiom 1: BFO:123 SubClassOf BFO:124
+Axiom 1: UBERON:123 SubClassOf BFO:123
+Axiom 1: UBERON:124 SubClassOf UBERON 123
+The base file is the set of all axioms that are about UBERON terms:
+Axiom 1: UBERON:123 SubClassOf BFO:123
+Axiom 1: UBERON:124 SubClassOf UBERON 123
+I.e.
+Axiom 1: BFO:123 SubClassOf BFO:124
+Gets removed.
+The base file pipeline is a bit more complex than the normal pipelines, because +of the logical interactions between the imported ontologies. This is solved by _first +merging all mirrors into one huge file and then extracting one mega module from it.
+Example: Let's say we are importing terms from Uberon, GO and RO in our ontologies. +When we use the base pipelines, we
+1) First obtain the base (usually by simply downloading it, but there is also an option now to create it with ROBOT)
+2) We merge all base files into one big pile
+3) Then we extract a single module imports/merged_import.owl
The first implementation of this pipeline is PATO, see https://github.com/pato-ontology/pato/blob/master/src/ontology/pato-odk.yaml.
+To check if your ontology uses this method, check src/ontology/upheno-odk.yaml to see if use_base_merging: TRUE is declared under import_group
If your ontology uses Base Module approach, please use the following steps:
+First, add the term to be imported to the term file associated with it (see above "Using term files" section if this is not clear to you)
+Next, you navigate in your terminal to the ontology directory (underneath src in your hpo root directory).
+cd src/ontology
+Then refresh imports by running
+sh run.sh make imports/merged_import.owl
+Note: if your mirrors are updated, you can run sh run.sh make no-mirror-refresh-merged
This requires quite a bit of memory on your local machine, so if you encounter an error, it might be a lack of memory on your computer. A solution would be to create a ticket in an issue tracker requesting for the term to be imported, and one of the local devs should pick this up and run the import for you.
+Lastly, restart Protégé, and the term should be imported in ready to be used.
+ + + + + + +For details on what components are, please see component section of repository file structure document.
+To add custom components to an ODK repo, please follow the following steps:
+1) Locate your odk yaml file and open it with your favourite text editor (src/ontology/upheno-odk.yaml) +2) Search if there is already a component section to the yaml file, if not add it accordingly, adding the name of your component:
+components:
+ products:
+ - filename: your-component-name.owl
+3) Add the component to your catalog file (src/ontology/catalog-v001.xml)
+ <uri name="http://purl.obolibrary.org/obo/upheno/components/your-component-name.owl" uri="components/your-component-name.owl"/>
+4) Add the component to the edit file (src/ontology/upheno-edit.obo) +for .obo formats:
+import: http://purl.obolibrary.org/obo/upheno/components/your-component-name.owl
+for .owl formats:
+Import(<http://purl.obolibrary.org/obo/upheno/components/your-component-name.owl>)
+5) Refresh your repo by running sh run.sh make update_repo - this should create a new file in src/ontology/components.
+6) In your custom makefile (src/ontology/upheno.Makefile) add a goal for your custom make file. In this example, the goal is a ROBOT template.
$(COMPONENTSDIR)/your-component-name.owl: $(SRC) ../templates/your-component-template.tsv
+ $(ROBOT) template --template ../templates/your-component-template.tsv \
+ annotate --ontology-iri $(ONTBASE)/$@ --output $(COMPONENTSDIR)/your-component-name.owl
+(If using a ROBOT template, do not forget to add your template tsv in src/templates/)
+7) Make the file by running sh run.sh make components/your-component-name.owl
The uPheno editors call is held every second Thursday (bi-weekly) on Zoom, provided by members of the Monarch Initiative and co-organised by members of the Alliance and Genome Resources. If you wish to join the meeting, you can open an issue on https://github.com/obophenotype/upheno/issues with the request to be added, or send an email to phenotype-ontologies-editors@googlegroups.com.
+The meeting coordinator (MC) is the person charged with organising the meeting. The current MC is Ray, @rays22.
+The uPheno organises an outreach call every four weeks to listen to external stakeholders describing their need for cross-species phenotype integration.
+| Date | +Lesson | +Notes | +Recordings | +
|---|---|---|---|
| 2024/04/05 | +TBD | +TBD | ++ |
| 2024/3/08 | +Computational identification of disease models through cross-species phenotype comparison | +Diego A. Pava, Pilar Cacheiro, Damian Smedley (IMPC) | +Recording | +
| 2024/02/09 | +Use cases for uPheno in the Alliance of Genome Resources and MGI | +Sue Bello (Alliance of Genome Resources, MGI) | +Recording | +
*The Drosophila phenotype
+ontologyOsumi-Sutherland et al, J Biomed Sem.
The DPO is formally a subset of FBcv, made available from +http://purl.obolibrary.org/obo/fbcv/dpo.owl
+Phenotypes in FlyBase may either by assigned to FBcv (dpo) classes, or +they may have a phenotype_manifest_in to FBbt (anatomy).
+For integration we generate the following ontologies:
+*http://purl.obolibrary.org/obo/upheno/imports/fbbt_phenotype.owl\
+*http://purl.obolibrary.org/obo/upheno/imports/uberon_phenotype.owl\
+*http://purl.obolibrary.org/obo/upheno/imports/go_phenotype.owl\
+*http://purl.obolibrary.org/obo/upheno/imports/cl_phenotype.owl
(see Makefile)
+This includes a phenotype class for every anatomy class - the IRI is +suffixed with "PHENOTYPE". Using these ontologies, Uberon and CL +phenotypes make the groupings.
+We include
+*http://purl.obolibrary.org/obo/upheno/dpo/dpo-importer.owl
Which imports dpo plus auto-generated fbbt phenotypes.
+The dpo-importer is included in the [MetazoanImporter]
+We create a local copy of fbbt that has "Drosophila " prefixed to all +labels. This gives us a hierarchy:
+* eye phenotype (defined using Uberon)\
+* compound eye phenotype (defined using Uberon)\
+* drosophila eye phenotype (defined using FBbt)
*http://code.google.com/p/cell-ontology/issues/detail?id=115ensure all CL to FBbt equiv axioms are present (we have good coverage for Uberon)
* project page -https://sourceforge.net/apps/trac/pombase/wiki/FissionYeastPhenotypeOntology\
+*FYPO: the fission yeast phenotype ontologyHarris et al, Bioinformatics
Note that the OWL axioms for FYPO are managed directly in the FYPO +project repo, we do not duplicate them here
+ + + + + + +*http://www.human-phenotype-ontology.org/\
+* Köhler S, Doelken SC, Mungall CJ, Bauer S, Firth HV, Bailleul-Forestier I, Black GC, Brown DL, Brudno M, Campbell J, FitzPatrick DR, Eppig JT, Jackson AP, Freson K, Girdea M, Helbig I, Hurst JA, Jähn J, Jackson LG, Kelly AM, Ledbetter DH, Mansour S, Martin CL, Moss C, Mumford A, Ouwehand WH, Park SM, Riggs ER, Scott RH, Sisodiya S, Van Vooren S, Wapner RJ, Wilkie AO, Wright CF, Vulto-van Silfhout AT, de Leeuw N, de Vries BB, Washingthon NL, Smith CL, Westerfield M, Schofield P, Ruef BJ, Gkoutos GV, Haendel M, Smedley D, Lewis SE, Robinson PN. The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data.Nucleic Acids Res.2014 Jan;42(Database issue):D966-74 [pubmed]
*HPO
+browser\
+*HP in
+OntoBee\
+*HP in OLSVis
The OWL axioms for HP are in the +src/ontology/hp +directory on this site.
+The structure is analagous to that of the [MP].
+The OWL axiomatization is updated frequently to stay in sync with +changes in the MP
+The edit file is currently:
+*http://purl.obolibrary.org/obo/hp/hp-equivalence-axioms-subq-ubr.owl
Edit this in protege.
+ + + + + + +*The Mammalian Phenotype Ontology: enabling robust
+annotation and comparative
+analysisSmith CL, Eppig JT\
+*MP browser at
+MGI\
+*MP in
+OntoBee\
+*MP in OLSVis
The OWL axioms for MP are in the +src/ontology/mp +directory on this site.
+*http://purl.obolibrary.org/obo/mp.owl- direct conversion of MGI-supplied obo file\
+*http://purl.obolibrary.org/obo/mp/mp-importer.owl- imports additional axioms, including the following ones below:\
+*http://purl.obolibrary.org/obo/mp.owl\
+*http://purl.obolibrary.org/obo/upheno/imports/chebi_import.owl\
+*http://purl.obolibrary.org/obo/upheno/imports/uberon_import.owl\
+*http://purl.obolibrary.org/obo/upheno/imports/pato_import.owl\
+*http://purl.obolibrary.org/obo/upheno/imports/go_import.owl\
+*http://purl.obolibrary.org/obo/upheno/imports/mpath_import.owl\
+*http://purl.obolibrary.org/obo/mp/mp-equivalence-axioms-subq-ubr.owl\
+\
The OWL axiomatization is updated frequently to stay in sync with +changes in the MP
+The edit file is currently:
+*http://purl.obolibrary.org/obo/mp/mp-equivalence-axioms-edit.owl
Edit this in protege.
+The file mp-equivalence-axioms.obo is DEPRECATED!
+*http://mp.termgenie.org/\
+*http://mp.termgenie.org/TermGenieFreeForm
* Schindelman, Gary, et al.Worm Phenotype Ontology:
+integrating phenotype data within and beyond the C.
+elegans
+community.BMC bioinformatics 12.1 (2011): 32.\
+*WBPhenotype in
+OntoBee\
+*WBPhenotype in
+OLSVis
The OWL axioms for WBPhenotype are in the +src/ontology/wbphenotype +directory on this site.
+*http://purl.obolibrary.org/obo/wbphenotype.owl- direct conversion of WormBase-supplied obo file\
+*http://purl.obolibrary.org/obo/wbphenotype/wbphenotype-importer.owl- imports additional axioms.
The structure roughly follows that of the [MP]. The worm anatomy is +used.
+Currently the source is wbphenotype/wbphenotype-equivalence-axioms.obo, +the OWL is generated from here. We are considering switching this +around, so the OWL is edited, using Protege.
+ + + + + + +This page describes the generation of the zebrafish phenotype ontology
+The ZP differs considerably from [HP], [MP] and others. ZFIN do not +annotate with a pre-composed phenotype ontology - all annotations +compose phenotypes on-the-fly using a combination of PATO, ZFA, GO and +other ontologies.
+We use these combinations to construct ZP on the fly, by naming each +distinct combination, assigning it an ID, and placing it in the +hierarchy.
+The process is described here:
+The OWL formalism for ZFIN annotations is described here:
+The java implementation is here:
+The OWL axioms for ZP are in +zp.owl +that is build on our hudson server.
+ + + + + + +"Characteristics" or "qualities" refer to an inherent or distinguishing characteristic or attribute of something or someone. +It represents a feature that defines the nature of an object, organism, or entity and can be used to describe, compare, and categorize different things. +Characteristics can be either qualitative (such as color, texture, or taste) or quantitative (such as height, weight, or age).
+The Phenotype And Trait Ontology (PATO) is the reference ontology for general characteristics in the OBO world.
+Some of the most widely use characteristics can be seen in the following tables
+| quality | +description | +example | +
|---|---|---|
| Length (PATO:0000122) | +A 1-D extent quality which is equal to the distance between two points. | ++ |
| Mass (PATO:0000128) | +A physical quality that inheres in a bearer by virtue of the proportion of the bearer's amount of matter. | ++ |
| Amount (PATO:0000070) | +The number of entities of a type that are part of the whole organism. | ++ |
| Morphology (PATO:0000051) | +A quality of a single physical entity inhering in the bearer by virtue of the bearer's size or shape or structure. | ++ |
Note from the authors: The descriptions above have been taken from PATO, but they are not very.. user friendly.
+ +Characteristics such as the one above can be used to describe a variety of entities such as biological, environmental and social. +We are specifically concerned with biological traits, which are characteristics that refer to an inherent characteristic of a biological entity, such as an organ (the heart), a process (cell division), a chemical entity (lysine) in the blood.
+The Ontology of Biological Attributes (OBA) is the reference ontology for biological characteristics in the OBO world. +There are a few other ontologies that describe biological traits, such as the Vertebrate Phenotype Ontology and the Ascomycete Phenotype Ontology (APO), but these are more species specific, and, more importantly, are not integrated in the wider EQ modelling framework.
+| Property | +Example term | +Definition | +
|---|---|---|
| Length | +OBA:VT0002544 | +The length of a digit. | +
| Mass | +OBA:VT0001259 | +The mass of a multicellular organism. | +
| Level | +OBA:2020005 | +The amount of lysine in blood. | +
| Morphology | +OBA:VT0005406 | +The size of a heart. | +
In biological contexts, the term "bearer" refers to the entity that possesses or carries a particular characteristic or quality. +The bearer can be any biological entity, such as an organism, an organ, a cell, or even a molecular structure, that exhibits a specific trait or feature. +Some examples:
+In each example, the "bearer" is the entity that has, carries, or exhibits a particular biological characteristic. This concept is fundamental in biology and bioinformatics for linking specific traits, qualities, or features to the entities that possess them, thereby enabling a clearer understanding and categorization of biological diversity and functions.
+ +A phenotypic change refers to some deviation from reference morphology, physiology, or behavior. +This is the most widely used, and most complicated category of phenotype terms for data specialists to understand.
+Conceptually, a phenotypic abnormality comprises:
+Biological attributes such as blood lysine amount (OBA:2020005) have been discussed earlier in this document.
+The most widely used change modifier used in practice is abnormal (PATO:0000460).
+This modifier signifies that the phenotypic change term describes a deviation that is abnormal, such as "Hyperlysinemia" (HP:0002161), which describes and increased concentration of lysine in the blood.
+Other modifiers include normal (PATO:0000461), which describes a change within in the normal range (sometimes interpreted as "no change").
+A directional modifier like increased (PATO:0040043) or decreased (PATO:0040042). In practice, most of our "characteristic" terms have specialised directional variants such as decreased amount (PATO:0001997) which can be used to describe phenotypes.
+Comparators are the most confusing aspects of phenotypic change.
+The first question someone has to ask when they see a concept describing is change like increased blood lysine levels is "compared to what?".
+Depending on biological context, the assumed comparators vary widely.
+For example, in clinical phenotyping, it is mostly assumed that
+a phenotypic feature corresponds to a deviation from the normal range, see HPO docs.
The Unified Phenotype Ontology (uPheno) is the reference ontology for biological abnormalities in the OBO world. +There are a many species-specific ontologies in the OBO world, such as the Mammalian Phenotype Ontology (MP), the Human Phenotype Ontology (HPO) and the Drosophila Phenotype Ontology (DPO), see here.
+| Property | +Example term | +Definition | +
|---|---|---|
| Length | +UPHENO:0072215 | +Increased length of the digit. | +
| Mass | +UPHENO:0054299 | +Decreased multicellular organism mass. | +
| Level | +UPHENO:0034327 | +Decreased level of lysine in blood. | +
| Morphology | +UPHENO:0001471 | +Increased size of the heart. | +
In biological data curation, it’s essential to differentiate between measurements and traits. Measurements, such as “blood glucose amount,” are quantitative indicators, providing numerical values. In contrast, traits, like “Hyperglycemia,” encompass both qualitative and quantitative characteristics, representing broader phenotypic states. This difference is crucial in ontology modeling, where measurements are directly linked to specific values, while traits reflect more comprehensive biological attributes. For example, “body temperature” is a measurement, whereas “Fever” represents a trait associated with elevated temperatures. Understanding this contrast is fundamental for accurate data representation and interpretation, ensuring nuanced understanding of biological entities and phenotypic variability.
+ + + + + + +Imports directory:
+*http://purl.obolibrary.org/obo/upheno/imports/
Currently the imports includes:
+* imports/chebi_import.owl\
+* imports/doid_import.owl\
+* imports/go_import.owl\
+* imports/mpath_import.owl\
+* imports/pato_import.owl\
+* imports/pr_import.owl\
+* imports/uberon_import.owl\
+* imports/wbbt_import.owl
To avoid multiple duplicate classes for heart, lung, skin etc we map all +classes to [Uberon] where this is applicable. For more divergent species +such as fly and C elegans we use the appropriate species-specific +ontology.
+Currently there are a small number of highly specific classes in FMA +that are being used and have no corresponding class in Uberon
+We use the OWLAPI SyntacticLocalityModularityExtractor, via [OWLTools]. +See the http://purl.obolibrary.org/obo/upheno/Makefile for details
+ + + + + + +PATO is an ontology of phenotypic qualities. We use PATO to compose +phenotypic descriptions. See [OWLAxiomatization]
+The current design patterns are such that the abnormal qualifier is only +added when the quality class in the definition is neutral.
+However, we still need to be able to infer
+* Hyoplasia of right ventricle SubClassOf Abnormality of right ventricle
Because the latter class definition includes qualifier some abnormal, +the SubClassOf axiom will not be entailed unless the qualifier is +explicitly stated or inferred
+We achieve this by including an axiom to PATO such that decreased sizes +etc are inferred to be qualifier some abnormal.
+We do this with an exiom in imports/extra.owl
+* 'deviation(from normal)' SubClassOf qualifier some abnormal
Anything under 'increased', 'decreased' etc in PATO is pre-reasoned in +PATO to be here.
+See the following explanation:
+http://phenotype-ontologies.googlecode.com/svn/trunk/doc/images/has-qualifier-inference.png
+For this strategy to work it requires the PATO classes themselves to be +classified under deviation from normal. This may not always be the case
+Do not be distracted by the fact the has-qualifier relation is named +has-component at the moment
+https://code.google.com/p/phenotype-ontologies/issues/detail?id=45
+Much has been written on the subject of representing absence. Before +diving into the logical issues it is worth examining patterns in +existing phenotype ontologies to understand what user expectations may +typically be for absence.
+*Absence_Phenotypes_in_OWL(Phenoscape Wiki)\
+* (outdated) material on the oldPATO
+wiki.
It is not uncommon to see patterns such as
+From a strict logical perspective, this is inverted. "absent incisors" +surely means "absence of all incisors", or put another way "the animal +has no incisors". Yet it would be possible to have an animal with +*absent* lower incisors and *present* upper incisors, yielding what +seems a contradiction (because the subClass axiom would say this +partial-incisor animal lacked all incisors).
+If the ontology were in fact truly modeling "absence of *all* S" then +it would lead to a curious ontology structure, with the typical tree +structure of the anatomy ontology representing S inverted into a +polyhierarchical fan in the absent-S ontology.
+From this it can be cautiously inferred that the intent of the phenotype +ontology curator and user is in fact to model "absence of *some* S" +rather than "absence of *all* S". This is not necessarily a universal +rule, and the intent may vary depending on whether we are talking about +a serially repeated structure or one that typically occurs in isolation. +The intent may also be to communicate that a *significant number* of S +is missing.
+It is also not uncommon to see patterns such as:
+Again, from a strict logical perspective this is false. If the spleen is +absent then what does the "morphology" of the parent refer to?
+However, this inference is clearly a desirable one from the point of +view of the phenotype ontology editors and users, as it is common in +ontologies for a variety of structures. For example:
+And:
+These patterns can be formally defended on developmental biology +grounds. "absence" here is _not_ equivalent to logical absence. It +refers specifically to developmental absence.
+Furthermore, strict logical absence leads to undesirable inferences. It +would be odd to include a nematode worm as having the phenotype "spleen +absent", because worms have not evolved spleens. But the logical +description of not having a spleen as part fets a worm.
+Similarly, if the strict cardinality interpretation were intended, we +would expect to see:
+i.e. if you're missing your entire hindlegs, you're *necessarily* +missing your femurs. But it must be emphatisized that this is *not* +how phenotype ontologies are classified. This goes for a wide range of +structures and other relationship types. In MP, "absent limb buds" are +*not* classified under "absent limbs", even though it is impossible +for a mammal to have limbs without having had limb buds.
+The existing treatment of absence can be formally defended +morphologically by conceiving of a morphological value space, with +"large" at one end and "small" at the other. As we get continuously +smaller, there may come an arbitrary point whereby we say "surely this +is no longer a limb" (and of course, we are not talking about a pure +geometrical size transformation here - as a limb reaches extreme edges +of a size range various other morphological changes necessarily happen). +But this cutoff is arguably arbitrary, and the resulting discontinuity +causes problems. It is simpler to treat absence as being one end of a +size scale.
+This is barely touching the subject, and is intended to illustrate that +things may be more subtle than naively treating words like "absent" as +precisely equivalent to cardinality=0. An understanding of the medical, +developmental and evolutionary contexts are absolutely required, +together with an understanding of the entailments of different logical +formulations.
+Even though existing phenotype ontologies may not be conceived of +formally, it is implicit than they do not model absence as being +equivalent to cardinality=0 / not(has_part), because the structure of +these ontologies would look radically different.
+Link to Jim Balhoff's PhenoDay paper and discussion
+Here's the link: http://phenoday2014.bio-lark.org/pdf/11.pdf
+ + + + + + +Phenotype ontologies use different reference ontologies for their EQs. Everything in uPheno is integrated towards a common set of reference ontologies, in particular Uberon and CL. In order to integrate species-independent anatomy ontologies we employ the following workflow for phenotype ontologies:
+When two classes are merged in uPheno based on a cross-species mapping, we assert the most general common ancestor as parent.
+ + + + + + +' + escapeHtml(summary) +'
' + noResultsText + '
'); + } +} + +function doSearch () { + var query = document.getElementById('mkdocs-search-query').value; + if (query.length > min_search_length) { + if (!window.Worker) { + displayResults(search(query)); + } else { + searchWorker.postMessage({query: query}); + } + } else { + // Clear results for short queries + displayResults([]); + } +} + +function initSearch () { + var search_input = document.getElementById('mkdocs-search-query'); + if (search_input) { + search_input.addEventListener("keyup", doSearch); + } + var term = getSearchTermFromLocation(); + if (term) { + search_input.value = term; + doSearch(); + } +} + +function onWorkerMessage (e) { + if (e.data.allowSearch) { + initSearch(); + } else if (e.data.results) { + var results = e.data.results; + displayResults(results); + } else if (e.data.config) { + min_search_length = e.data.config.min_search_length-1; + } +} + +if (!window.Worker) { + console.log('Web Worker API not supported'); + // load index in main thread + $.getScript(joinUrl(base_url, "search/worker.js")).done(function () { + console.log('Loaded worker'); + init(); + window.postMessage = function (msg) { + onWorkerMessage({data: msg}); + }; + }).fail(function (jqxhr, settings, exception) { + console.error('Could not load worker.js'); + }); +} else { + // Wrap search in a web worker + var searchWorker = new Worker(joinUrl(base_url, "search/worker.js")); + searchWorker.postMessage({init: true}); + searchWorker.onmessage = onWorkerMessage; +} diff --git a/search/search_index.json b/search/search_index.json new file mode 100644 index 00000000..9b954b42 --- /dev/null +++ b/search/search_index.json @@ -0,0 +1 @@ +{"config":{"indexing":"full","lang":["en"],"min_search_length":3,"prebuild_index":false,"separator":"[\\s\\-]+"},"docs":[{"location":"","text":"UPHENO Ontology Documentation Welcome to the UPHENO documentation! It is entirely empty at the moment so look no further! You can find descriptions of the standard ontology engineering workflows here .","title":"Getting started"},{"location":"#upheno-ontology-documentation","text":"Welcome to the UPHENO documentation! It is entirely empty at the moment so look no further! You can find descriptions of the standard ontology engineering workflows here .","title":"UPHENO Ontology Documentation"},{"location":"about/","text":"About uPheno The uPheno project aims to unify the annotation of phenotypes across species in a manner analogous to unification of gene function annotation by the Gene Ontology. uPheno 2.0 builds on earlier efforts with a strategy that directly leverages the work of the phenotype ontology development community and incorporates phenotypes from a much wider range of species. We have organised a collaborative community effort, including representatives of all major model organism databases, to document and align formal design patterns for representing phenotypes and further develop reference ontologies, such as PATO, which are used in these patterns. A common development infrastructure makes it easy to use these design patterns to generate both species-specific ontologies and a species-independent layer that subsumes them. The resulting community-curated ontology for the representation and integration of phenotypes across species serves two general purposes: - Providing a community-developed framework for ontology editors to bootstrap, maintain and extend their phenotype ontologies in a scalable and standardised manner. - Facilitating the retrieval and comparative analysis of species-specific phenotypes through a deep layer of species-independent phenotypes. Currently, the development of uPheno is organized by a group that meets biweekly. See the meetings page for more info, including how to participate.","title":"About uPheno"},{"location":"about/#about-upheno","text":"The uPheno project aims to unify the annotation of phenotypes across species in a manner analogous to unification of gene function annotation by the Gene Ontology. uPheno 2.0 builds on earlier efforts with a strategy that directly leverages the work of the phenotype ontology development community and incorporates phenotypes from a much wider range of species. We have organised a collaborative community effort, including representatives of all major model organism databases, to document and align formal design patterns for representing phenotypes and further develop reference ontologies, such as PATO, which are used in these patterns. A common development infrastructure makes it easy to use these design patterns to generate both species-specific ontologies and a species-independent layer that subsumes them. The resulting community-curated ontology for the representation and integration of phenotypes across species serves two general purposes: - Providing a community-developed framework for ontology editors to bootstrap, maintain and extend their phenotype ontologies in a scalable and standardised manner. - Facilitating the retrieval and comparative analysis of species-specific phenotypes through a deep layer of species-independent phenotypes. Currently, the development of uPheno is organized by a group that meets biweekly. See the meetings page for more info, including how to participate.","title":"About uPheno"},{"location":"cite/","text":"How to cite uPheno Papers uPheno 2 Matentzoglu N, Osumi-Sutherland D, Balhoff JP, Bello S, Bradford Y, Cardmody L, Grove C, Harris MA, Harris N, K\u00f6hler S, McMurry J, Mungall C, Munoz-Torres M, Pilgrim C, Robb S, Robinson PN, Segerdell E, Vasilevsky N, Haendel M. uPheno 2: Framework for standardised representation of phenotypes across species. 2019 Apr 8. http://dx.doi.org/10.7490/f1000research.1116540.1 Original uPheno Sebastian K\u00f6hler, Sandra C Doelken, Barbara J Ruef, Sebastian Bauer, Nicole Washington, Monte Westerfield, George Gkoutos, Paul Schofield, Damian Smedley, Suzanna E Lewis, Peter N Robinson, Christopher J Mungall (2013) Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research F1000Research Entity-Quality definitions and phenotype modelling C J Mungall, Georgios Gkoutos, Cynthia Smith, Melissa Haendel, Suzanna Lewis, Michael Ashburner (2010) Integrating phenotype ontologies across multiple species Genome Biology 11 (1)","title":"Cite"},{"location":"cite/#how-to-cite-upheno","text":"","title":"How to cite uPheno"},{"location":"cite/#papers","text":"","title":"Papers"},{"location":"cite/#upheno-2","text":"Matentzoglu N, Osumi-Sutherland D, Balhoff JP, Bello S, Bradford Y, Cardmody L, Grove C, Harris MA, Harris N, K\u00f6hler S, McMurry J, Mungall C, Munoz-Torres M, Pilgrim C, Robb S, Robinson PN, Segerdell E, Vasilevsky N, Haendel M. uPheno 2: Framework for standardised representation of phenotypes across species. 2019 Apr 8. http://dx.doi.org/10.7490/f1000research.1116540.1","title":"uPheno 2"},{"location":"cite/#original-upheno","text":"Sebastian K\u00f6hler, Sandra C Doelken, Barbara J Ruef, Sebastian Bauer, Nicole Washington, Monte Westerfield, George Gkoutos, Paul Schofield, Damian Smedley, Suzanna E Lewis, Peter N Robinson, Christopher J Mungall (2013) Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research F1000Research","title":"Original uPheno"},{"location":"cite/#entity-quality-definitions-and-phenotype-modelling","text":"C J Mungall, Georgios Gkoutos, Cynthia Smith, Melissa Haendel, Suzanna Lewis, Michael Ashburner (2010) Integrating phenotype ontologies across multiple species Genome Biology 11 (1)","title":"Entity-Quality definitions and phenotype modelling"},{"location":"contributing/","text":"How to contribute to UPHENO","title":"Contributing"},{"location":"contributing/#how-to-contribute-to-upheno","text":"","title":"How to contribute to UPHENO"},{"location":"howto/add-relation-extension/","text":"How to add the uPheno direct relation extension EQ definitions are powerful tools for reconciling phenotypes across species and driving reasoning. However, they are not all that useful for many \"normal\" users of our ontologies. We have developed a little workflow extension to take care of that. As usual please follow the steps to install the custom uPheno Makefile extension first. Now add a new component to your ont-odk.yaml file (e.g. src/ontology/mp-odk.yaml ): components: products: - filename: eq-relations.owl We can now choose if we want to add the component to your edit file as well. To do that, follow the instructions on adding an import (i.e. adding the component to the edit file and catalog file). The IRI of the component is http://purl.obolibrary.org/obo/YOURONTOLOGY/components/eq-relations.owl . For example, for MP, the IRI is http://purl.obolibrary.org/obo/mp/components/eq-relations.owl . Now we can generate the component: sh run.sh make components/eq-relations.owl This command will be run automatically during a release ( prepare_release ).","title":"Add the uPheno direct relation extension"},{"location":"howto/add-relation-extension/#how-to-add-the-upheno-direct-relation-extension","text":"EQ definitions are powerful tools for reconciling phenotypes across species and driving reasoning. However, they are not all that useful for many \"normal\" users of our ontologies. We have developed a little workflow extension to take care of that. As usual please follow the steps to install the custom uPheno Makefile extension first. Now add a new component to your ont-odk.yaml file (e.g. src/ontology/mp-odk.yaml ): components: products: - filename: eq-relations.owl We can now choose if we want to add the component to your edit file as well. To do that, follow the instructions on adding an import (i.e. adding the component to the edit file and catalog file). The IRI of the component is http://purl.obolibrary.org/obo/YOURONTOLOGY/components/eq-relations.owl . For example, for MP, the IRI is http://purl.obolibrary.org/obo/mp/components/eq-relations.owl . Now we can generate the component: sh run.sh make components/eq-relations.owl This command will be run automatically during a release ( prepare_release ).","title":"How to add the uPheno direct relation extension"},{"location":"howto/custom-upheno-makefile/","text":"Add custom uPheno Makefile The custom uPheno Makefile is an extension to your normal custom Makefile (for example, hp.Makefile, mp.Makefile, etc), located in the src/ontology directory of your ODK set up. To install it: (1) Open your normal custom Makefile and add a line in the very end: include pheno.Makefile (2) Now download the custom Makefile: https://raw.githubusercontent.com/obophenotype/upheno/master/src/ontology/config/pheno.Makefile and save it in your src/ontology directory. Feel free to use, for example, wget: cd src/ontology wget https://raw.githubusercontent.com/obophenotype/upheno/master/src/ontology/config/pheno.Makefile -O pheno.Makefile From now on you can simply run sh run.sh make update_pheno_makefile whenever you wish to synchronise the Makefile with the uPheno repo. (Note: it would probably be good to add a GitHub action that does that automatically.)","title":"Add custom uPheno Makefile"},{"location":"howto/custom-upheno-makefile/#add-custom-upheno-makefile","text":"The custom uPheno Makefile is an extension to your normal custom Makefile (for example, hp.Makefile, mp.Makefile, etc), located in the src/ontology directory of your ODK set up. To install it: (1) Open your normal custom Makefile and add a line in the very end: include pheno.Makefile (2) Now download the custom Makefile: https://raw.githubusercontent.com/obophenotype/upheno/master/src/ontology/config/pheno.Makefile and save it in your src/ontology directory. Feel free to use, for example, wget: cd src/ontology wget https://raw.githubusercontent.com/obophenotype/upheno/master/src/ontology/config/pheno.Makefile -O pheno.Makefile From now on you can simply run sh run.sh make update_pheno_makefile whenever you wish to synchronise the Makefile with the uPheno repo. (Note: it would probably be good to add a GitHub action that does that automatically.)","title":"Add custom uPheno Makefile"},{"location":"howto/editors_workflow/","text":"Phenotype Ontology Editors' Workflow Useful links Phenotype Ontology Working Group Meetings agenda and minutes gdoc . phenotype-ontologies slack channel : to send meeting reminders; ask for agenda items; questions; discussions etc. Dead simple owl design pattern (DOS-DP) Documentation Getting started with DOSDP templates . Dead Simple Ontology Design Patterns (DOSDP) . Using DOSDP templates in ODK Workflows . Validate DOS-DP yaml templates: yamllint : yaml syntax validator Installing yamllint : brew install yamllint Congiguring yamllint You can ignore the error line too long yaml syntax errors for dos-dp yaml templates. You can create a custom configuration file for yamllint in your home folder: sh touch ~/.config/yamllint/config The content of the config file should look like this: ```yaml # Custom configuration file for yamllint # It extends the default conf by adjusting some options. extends: default rules: line-length: max: 80 # 80 chars should be enough, but don't fail if a line is longer max: 140 # allow long lines level: warning allow-non-breakable-words: true allow-non-breakable-inline-mappings: true `` The custom config should turn the error line too long errors to warnings. 2. [DOS-DP validator:](https://incatools.github.io/dead_simple_owl_design_patterns/validator/): DOS-DP format validator * [Installing ](https://github.com/INCATools/dead_simple_owl_design_patterns): pip install dosdp` Patternisation is the process of ensuring that all entity quality (EQ) descriptions from textual phenotype term definitions have a logical definition pattern. A pattern is a standard format for describing a phenotype that includes a quality and an entity. For example, \"increased body size\" is a pattern that includes the quality \"increased\" and the entity \"body size.\" The goal of patternisation is to make the EQ descriptions more uniform and machine-readable, which facilitates downstream analysis. 1. Identify a group of related phenotypes from diverse organisms The first step in the Phenotype Ontology Editors' Workflow is to identify a group of related phenotypes from diverse organisms. This can be done by considering proposals from phenotype editors or by using the pattern suggestion pipeline. The phenotype editors may propose a group of related phenotypes based on their domain knowledge, while the pattern suggestion pipeline uses semantic similarity and shared Phenotype And Trait Ontology (PATO) quality terms to identify patterns in phenotype terms from different organism-specific ontologies. 2. Propose a phenotype pattern Once a group of related phenotypes is identified, the editors propose a phenotype pattern. To do this, they create a Github issue to request the phenotype pattern template in the uPheno repository. Alternatively, a new template can be proposed at a phenotype editors' meeting which can lead to the creation of a new term request as a Github issue. Ideally, the proposed phenotype pattern should include an appropriate PATO quality term for logical definition, use cases, term examples, and a textual definition pattern for the phenotype terms. 3. Discuss the new phenotype pattern draft at the regular uPheno phenotype editors meeting The next step is to discuss the new phenotype pattern draft at the regular uPheno phenotype editors meeting. During the meeting, the editors' comments and suggestions for improvements are collected as comments on the DOS-DP yaml template in the corresponding Github pull request. Based on the feedback and discussions, a consensus on improvements should be achieved. The DOS-DP yaml template is named should start with a lower case letter, should be informative, and must include the PATO quality term. A Github pull request is created for the DOS-DP yaml template. A DOS-DP phenotype pattern template example: --- pattern_name: ??pattern_and_file_name pattern_iri: http://purl.obolibrary.org/obo/upheno/patterns-dev/??pattern_and_file_name.yaml description: 'A description that helps people chose this pattern for the appropriate scenario.' # examples: # - example_IRI-1 # term name # - example_IRI-2 # term name # - example_IRI-3 # term name # - http://purl.obolibrary.org/obo/XXXXXXXXXX # XXXXXXXX contributors: - https://orcid.org/XXXX-XXXX-XXXX-XXXX # Yyy Yyyyyyyyy classes: process_quality: PATO:0001236 abnormal: PATO:0000460 anatomical_entity: UBERON:0001062 relations: characteristic_of: RO:0000052 has_modifier: RO:0002573 has_part: BFO:0000051 annotationProperties: exact_synonym: oio:hasExactSynonym related_synonym: oio:hasRelatedSynonym xref: oio:hasDbXref vars: var??: \"'anatomical_entity'\" # \"'variable_range'\" name: text: \"trait ?? %s\" vars: - var?? annotations: - annotationProperty: exact_synonym text: \"? of %s\" vars: - var?? - annotationProperty: related_synonym text: \"? %s\" vars: - var?? - annotationProperty: xref text: \"AUTO:patterns/patterns/chemical_role_attribute\" def: text: \"A trait that ?? %s.\" vars: - var?? equivalentTo: text: \"'has_part' some ( 'XXXXXXXXXXXXXXXXX' and ('characteristic_of' some %s) and ('has_modifier' some 'abnormal') )\" vars: - var?? ... 4. Review the candidate phenotype pattern Once a consensus on the improvements for a particular template is achieved, they are incorporated into the DOS-DP yaml file. Typically, the improvements are applied to the template some time before a subsequent ontology editor's meeting. There should be enough time for off-line review of the proposed pattern to allow community feedback. The improved phenotype pattern candidate draft should get approval from the community at one of the regular ontology editors' call or in a Github comment. The ontology editors who approve the pattern provide their ORCIDs and they are credited as contributors in an appropriate field of the DOS-DP pattern template. 5. Add the community-approved phenotype pattern template to uPheno Once the community-approved phenotype pattern template is created, it is added to the uPheno Github repository. The approved DOS-DP yaml phenotype pattern template should pass quality control (QC) steps. 1. Validate yaml syntax: yamllint 2. Validate DOS-DP Use DOSDP Validator . * To validate a template using the command line interface, execute: ```sh yamllint dosdp validate -i After successfully passing QC, the responsible editor merges the approved pull request, and the phenotype pattern becomes part of the uPheno phenotype pattern template collection.","title":"Phenotype Ontology Editors' Workflow"},{"location":"howto/editors_workflow/#phenotype-ontology-editors-workflow","text":"","title":"Phenotype Ontology Editors' Workflow"},{"location":"howto/editors_workflow/#useful-links","text":"Phenotype Ontology Working Group Meetings agenda and minutes gdoc . phenotype-ontologies slack channel : to send meeting reminders; ask for agenda items; questions; discussions etc. Dead simple owl design pattern (DOS-DP) Documentation Getting started with DOSDP templates . Dead Simple Ontology Design Patterns (DOSDP) . Using DOSDP templates in ODK Workflows . Validate DOS-DP yaml templates: yamllint : yaml syntax validator Installing yamllint : brew install yamllint Congiguring yamllint You can ignore the error line too long yaml syntax errors for dos-dp yaml templates. You can create a custom configuration file for yamllint in your home folder: sh touch ~/.config/yamllint/config The content of the config file should look like this: ```yaml # Custom configuration file for yamllint # It extends the default conf by adjusting some options. extends: default rules: line-length: max: 80 # 80 chars should be enough, but don't fail if a line is longer","title":"Useful links"},{"location":"howto/editors_workflow/#max-140-allow-long-lines","text":"level: warning allow-non-breakable-words: true allow-non-breakable-inline-mappings: true `` The custom config should turn the error line too long errors to warnings. 2. [DOS-DP validator:](https://incatools.github.io/dead_simple_owl_design_patterns/validator/): DOS-DP format validator * [Installing ](https://github.com/INCATools/dead_simple_owl_design_patterns): pip install dosdp` Patternisation is the process of ensuring that all entity quality (EQ) descriptions from textual phenotype term definitions have a logical definition pattern. A pattern is a standard format for describing a phenotype that includes a quality and an entity. For example, \"increased body size\" is a pattern that includes the quality \"increased\" and the entity \"body size.\" The goal of patternisation is to make the EQ descriptions more uniform and machine-readable, which facilitates downstream analysis.","title":"max: 140 # allow long lines"},{"location":"howto/editors_workflow/#1-identify-a-group-of-related-phenotypes-from-diverse-organisms","text":"The first step in the Phenotype Ontology Editors' Workflow is to identify a group of related phenotypes from diverse organisms. This can be done by considering proposals from phenotype editors or by using the pattern suggestion pipeline. The phenotype editors may propose a group of related phenotypes based on their domain knowledge, while the pattern suggestion pipeline uses semantic similarity and shared Phenotype And Trait Ontology (PATO) quality terms to identify patterns in phenotype terms from different organism-specific ontologies.","title":"1. Identify a group of related phenotypes from diverse organisms"},{"location":"howto/editors_workflow/#2-propose-a-phenotype-pattern","text":"Once a group of related phenotypes is identified, the editors propose a phenotype pattern. To do this, they create a Github issue to request the phenotype pattern template in the uPheno repository. Alternatively, a new template can be proposed at a phenotype editors' meeting which can lead to the creation of a new term request as a Github issue. Ideally, the proposed phenotype pattern should include an appropriate PATO quality term for logical definition, use cases, term examples, and a textual definition pattern for the phenotype terms.","title":"2. Propose a phenotype pattern"},{"location":"howto/editors_workflow/#3-discuss-the-new-phenotype-pattern-draft-at-the-regular-upheno-phenotype-editors-meeting","text":"The next step is to discuss the new phenotype pattern draft at the regular uPheno phenotype editors meeting. During the meeting, the editors' comments and suggestions for improvements are collected as comments on the DOS-DP yaml template in the corresponding Github pull request. Based on the feedback and discussions, a consensus on improvements should be achieved. The DOS-DP yaml template is named should start with a lower case letter, should be informative, and must include the PATO quality term. A Github pull request is created for the DOS-DP yaml template. A DOS-DP phenotype pattern template example: --- pattern_name: ??pattern_and_file_name pattern_iri: http://purl.obolibrary.org/obo/upheno/patterns-dev/??pattern_and_file_name.yaml description: 'A description that helps people chose this pattern for the appropriate scenario.' # examples: # - example_IRI-1 # term name # - example_IRI-2 # term name # - example_IRI-3 # term name # - http://purl.obolibrary.org/obo/XXXXXXXXXX # XXXXXXXX contributors: - https://orcid.org/XXXX-XXXX-XXXX-XXXX # Yyy Yyyyyyyyy classes: process_quality: PATO:0001236 abnormal: PATO:0000460 anatomical_entity: UBERON:0001062 relations: characteristic_of: RO:0000052 has_modifier: RO:0002573 has_part: BFO:0000051 annotationProperties: exact_synonym: oio:hasExactSynonym related_synonym: oio:hasRelatedSynonym xref: oio:hasDbXref vars: var??: \"'anatomical_entity'\" # \"'variable_range'\" name: text: \"trait ?? %s\" vars: - var?? annotations: - annotationProperty: exact_synonym text: \"? of %s\" vars: - var?? - annotationProperty: related_synonym text: \"? %s\" vars: - var?? - annotationProperty: xref text: \"AUTO:patterns/patterns/chemical_role_attribute\" def: text: \"A trait that ?? %s.\" vars: - var?? equivalentTo: text: \"'has_part' some ( 'XXXXXXXXXXXXXXXXX' and ('characteristic_of' some %s) and ('has_modifier' some 'abnormal') )\" vars: - var?? ...","title":"3. Discuss the new phenotype pattern draft at the regular uPheno phenotype editors meeting"},{"location":"howto/editors_workflow/#4-review-the-candidate-phenotype-pattern","text":"Once a consensus on the improvements for a particular template is achieved, they are incorporated into the DOS-DP yaml file. Typically, the improvements are applied to the template some time before a subsequent ontology editor's meeting. There should be enough time for off-line review of the proposed pattern to allow community feedback. The improved phenotype pattern candidate draft should get approval from the community at one of the regular ontology editors' call or in a Github comment. The ontology editors who approve the pattern provide their ORCIDs and they are credited as contributors in an appropriate field of the DOS-DP pattern template.","title":"4. Review the candidate phenotype pattern"},{"location":"howto/editors_workflow/#5-add-the-community-approved-phenotype-pattern-template-to-upheno","text":"Once the community-approved phenotype pattern template is created, it is added to the uPheno Github repository. The approved DOS-DP yaml phenotype pattern template should pass quality control (QC) steps. 1. Validate yaml syntax: yamllint 2. Validate DOS-DP Use DOSDP Validator . * To validate a template using the command line interface, execute: ```sh yamllint dosdp validate -i After successfully passing QC, the responsible editor merges the approved pull request, and the phenotype pattern becomes part of the uPheno phenotype pattern template collection.","title":"5. Add the community-approved phenotype pattern template to uPheno"},{"location":"howto/pattern-merge-replace-workflow/","text":"Pattern merge - replace workflow This document is on how to merge new DOSDP design patterns into an ODK ontology and then how to replace the old classes with the new ones. 1. You need the tables in tsv format with the DOSDP filler data. Download the tsv tables to $ODK-ONTOLOGY/src/patterns/data/default/ Make sure that the tsv filenames match that of the relevant yaml DOSDP pattern files. 2. Add the new matching pattern yaml filename to $ODK-ONTOLOGY/src/patterns/dosdp-patterns/external.txt 3. Import the new pattern templates that you have just added to the external.txt list from external sources into the current working repository cd ODK-ONTOLOGY/src/ontology sh run.sh make update_patterns 4. make definitions.owl cd ODK-ONTOLOGY/src/ontology sh run.sh make ../patterns/definitions.owl IMP=false 5. Remove old classes and replace them with the equivalent and patternised new classes cd ODK-ONTOLOGY/src/ontology sh run.sh make remove_patternised_classes 6. Announce the pattern migration in an appropriate channel, for example on the phenotype-ontologies Slack channel. For example: I have migrated the ... table and changed the tab colour to blue. You can delete the tab if you wish.","title":"Pattern merge - replace workflow"},{"location":"howto/pattern-merge-replace-workflow/#pattern-merge-replace-workflow","text":"This document is on how to merge new DOSDP design patterns into an ODK ontology and then how to replace the old classes with the new ones.","title":"Pattern merge - replace workflow"},{"location":"howto/pattern-merge-replace-workflow/#1-you-need-the-tables-in-tsv-format-with-the-dosdp-filler-data-download-the-tsv-tables-to","text":"$ODK-ONTOLOGY/src/patterns/data/default/ Make sure that the tsv filenames match that of the relevant yaml DOSDP pattern files.","title":"1. You need the tables in tsv format with the DOSDP filler data. Download the tsv tables to"},{"location":"howto/pattern-merge-replace-workflow/#2-add-the-new-matching-pattern-yaml-filename-to","text":"$ODK-ONTOLOGY/src/patterns/dosdp-patterns/external.txt","title":"2. Add the new matching pattern yaml filename to"},{"location":"howto/pattern-merge-replace-workflow/#3-import-the-new-pattern-templates-that-you-have-just-added-to-the-externaltxt-list-from-external-sources-into-the-current-working-repository","text":"cd ODK-ONTOLOGY/src/ontology sh run.sh make update_patterns","title":"3. Import the new pattern templates that you have just added to the external.txt list from external sources into the current working repository"},{"location":"howto/pattern-merge-replace-workflow/#4-make-definitionsowl","text":"cd ODK-ONTOLOGY/src/ontology sh run.sh make ../patterns/definitions.owl IMP=false","title":"4. make definitions.owl"},{"location":"howto/pattern-merge-replace-workflow/#5-remove-old-classes-and-replace-them-with-the-equivalent-and-patternised-new-classes","text":"cd ODK-ONTOLOGY/src/ontology sh run.sh make remove_patternised_classes","title":"5. Remove old classes and replace them with the equivalent and patternised new classes"},{"location":"howto/pattern-merge-replace-workflow/#6-announce-the-pattern-migration-in-an-appropriate-channel-for-example-on-the-phenotype-ontologies-slack-channel","text":"For example: I have migrated the ... table and changed the tab colour to blue. You can delete the tab if you wish.","title":"6. Announce the pattern migration in an appropriate channel, for example on the phenotype-ontologies Slack channel."},{"location":"howto/run-upheno2-release/","text":"How to run a uPheno 2 release In order to run a release you will have to have completed the steps to set up s3 . Clone https://github.com/obophenotype/upheno-dev cd src/scripts sh upheno_pipeline.sh cd ../ontology make prepare_upload S3_VERSION=2022-06-19 make deploy S3_VERSION=2022-06-19","title":"How to run a uPheno 2 release"},{"location":"howto/run-upheno2-release/#how-to-run-a-upheno-2-release","text":"In order to run a release you will have to have completed the steps to set up s3 . Clone https://github.com/obophenotype/upheno-dev cd src/scripts sh upheno_pipeline.sh cd ../ontology make prepare_upload S3_VERSION=2022-06-19 make deploy S3_VERSION=2022-06-19","title":"How to run a uPheno 2 release"},{"location":"howto/set-up-s3/","text":"How to set yourself up for S3 To be able to upload new uPheno release to the uPheno S3 bucket, you need to set yourself up for S3 first. Download and install AWS CLI Obtain secrets from BBOP Add configuration for secrets 1. Download and install AWS CLI The most convenient way to interact with S3 is the AWS Command Line Interface (CLI) . You can find the installers and install instructions on that page (different depending on your Operation System): - For Mac - For Windows 2. Obtain secrets from BBOP Next, you need to ask someone at BBOP (such as Chris Mungall or Seth Carbon) to provide you with an account that gives you access to the BBOP s3 buckets. You will have to provide a username. You will receive: - User name - Access key ID- - Secret access key - Console link to sign into bucket 3. Add configuration for secrets You will now have to set up your local system. You will create two files: $ less ~/.aws/config [default] region = us-east-1 and $ less ~/.aws/credentials [default] aws_access_key_id = *** aws_secret_access_key = *** in ~/.aws/credentials make sure you add the correct keys as provided above. 4. Write to your bucket Now, you should be set up to write to your s3 bucket. Note that in order for your data to be accessible through https after your upload, you need to add --acl public read . aws s3 sync --exclude \"*.DS_Store*\" my/data-dir s3://bbop-ontologies/myproject/data-dir --acl public-read If you have previously pushed data to the same location, you wont be able to set it to \"publicly readable\" by simply rerunning the sync command. If you want to publish previously private data, follow the instructions here , e.g.: aws s3api put-object-acl --bucket s3://bbop-ontologies/myproject/data-dir --key exampleobject --acl public-read","title":"How to set up s3 for uploading upheno data files"},{"location":"howto/set-up-s3/#how-to-set-yourself-up-for-s3","text":"To be able to upload new uPheno release to the uPheno S3 bucket, you need to set yourself up for S3 first. Download and install AWS CLI Obtain secrets from BBOP Add configuration for secrets","title":"How to set yourself up for S3"},{"location":"howto/set-up-s3/#1-download-and-install-aws-cli","text":"The most convenient way to interact with S3 is the AWS Command Line Interface (CLI) . You can find the installers and install instructions on that page (different depending on your Operation System): - For Mac - For Windows","title":"1. Download and install AWS CLI"},{"location":"howto/set-up-s3/#2-obtain-secrets-from-bbop","text":"Next, you need to ask someone at BBOP (such as Chris Mungall or Seth Carbon) to provide you with an account that gives you access to the BBOP s3 buckets. You will have to provide a username. You will receive: - User name - Access key ID- - Secret access key - Console link to sign into bucket","title":"2. Obtain secrets from BBOP"},{"location":"howto/set-up-s3/#3-add-configuration-for-secrets","text":"You will now have to set up your local system. You will create two files: $ less ~/.aws/config [default] region = us-east-1 and $ less ~/.aws/credentials [default] aws_access_key_id = *** aws_secret_access_key = *** in ~/.aws/credentials make sure you add the correct keys as provided above.","title":"3. Add configuration for secrets"},{"location":"howto/set-up-s3/#4-write-to-your-bucket","text":"Now, you should be set up to write to your s3 bucket. Note that in order for your data to be accessible through https after your upload, you need to add --acl public read . aws s3 sync --exclude \"*.DS_Store*\" my/data-dir s3://bbop-ontologies/myproject/data-dir --acl public-read If you have previously pushed data to the same location, you wont be able to set it to \"publicly readable\" by simply rerunning the sync command. If you want to publish previously private data, follow the instructions here , e.g.: aws s3api put-object-acl --bucket s3://bbop-ontologies/myproject/data-dir --key exampleobject --acl public-read","title":"4. Write to your bucket"},{"location":"odk-workflows/","text":"Default ODK Workflows Daily Editors Workflow Release Workflow Manage your ODK Repository Setting up Docker for ODK Imports management Managing the documentation Managing your Automated Testing","title":"Overview"},{"location":"odk-workflows/#default-odk-workflows","text":"Daily Editors Workflow Release Workflow Manage your ODK Repository Setting up Docker for ODK Imports management Managing the documentation Managing your Automated Testing","title":"Default ODK Workflows"},{"location":"odk-workflows/ContinuousIntegration/","text":"Introduction to Continuous Integration Workflows with ODK Historically, most repos have been using Travis CI for continuous integration testing and building, but due to runtime restrictions, we recently switched a lot of our repos to GitHub actions. You can set up your repo with CI by adding this to your configuration file (src/ontology/upheno-odk.yaml): ci: - github_actions When updateing your repo , you will notice a new file being added: .github/workflows/qc.yml . This file contains your CI logic, so if you need to change, or add anything, this is the place! Alternatively, if your repo is in GitLab instead of GitHub, you can set up your repo with GitLab CI by adding this to your configuration file (src/ontology/upheno-odk.yaml): ci: - gitlab-ci This will add a file called .gitlab-ci.yml in the root of your repo.","title":"Manage Continuous Integration"},{"location":"odk-workflows/ContinuousIntegration/#introduction-to-continuous-integration-workflows-with-odk","text":"Historically, most repos have been using Travis CI for continuous integration testing and building, but due to runtime restrictions, we recently switched a lot of our repos to GitHub actions. You can set up your repo with CI by adding this to your configuration file (src/ontology/upheno-odk.yaml): ci: - github_actions When updateing your repo , you will notice a new file being added: .github/workflows/qc.yml . This file contains your CI logic, so if you need to change, or add anything, this is the place! Alternatively, if your repo is in GitLab instead of GitHub, you can set up your repo with GitLab CI by adding this to your configuration file (src/ontology/upheno-odk.yaml): ci: - gitlab-ci This will add a file called .gitlab-ci.yml in the root of your repo.","title":"Introduction to Continuous Integration Workflows with ODK"},{"location":"odk-workflows/EditorsWorkflow/","text":"Editors Workflow The editors workflow is one of the formal workflows to ensure that the ontology is developed correctly according to ontology engineering principles. There are a few different editors workflows: Local editing workflow: Editing the ontology in your local environment by hand, using tools such as Prot\u00e9g\u00e9, ROBOT templates or DOSDP patterns. Completely automated data pipeline (GitHub Actions) DROID workflow This document only covers the first editing workflow, but more will be added in the future Local editing workflow Workflow requirements: git github docker editing tool of choice, e.g. Prot\u00e9g\u00e9, your favourite text editor, etc 1. Create issue Ensure that there is a ticket on your issue tracker that describes the change you are about to make. While this seems optional, this is a very important part of the social contract of building an ontology - no change to the ontology should be performed without a good ticket, describing the motivation and nature of the intended change. 2. Update main branch In your local environment (e.g. your laptop), make sure you are on the main (prev. master ) branch and ensure that you have all the upstream changes, for example: git checkout master git pull 3. Create feature branch Create a new branch. Per convention, we try to use meaningful branch names such as: - issue23removeprocess (where issue 23 is the related issue on GitHub) - issue26addcontributor - release20210101 (for releases) On your command line, this looks like this: git checkout -b issue23removeprocess 4. Perform edit Using your editor of choice, perform the intended edit. For example: Prot\u00e9g\u00e9 Open src/ontology/upheno-edit.owl in Prot\u00e9g\u00e9 Make the change Save the file TextEdit Open src/ontology/upheno-edit.owl in TextEdit (or Sublime, Atom, Vim, Nano) Make the change Save the file Consider the following when making the edit. According to our development philosophy, the only places that should be manually edited are: src/ontology/upheno-edit.owl Any ROBOT templates you chose to use (the TSV files only) Any DOSDP data tables you chose to use (the TSV files, and potentially the associated patterns) components (anything in src/ontology/components ), see here . Imports should not be edited (any edits will be flushed out with the next update). However, refreshing imports is a potentially breaking change - and is discussed elsewhere . Changes should usually be small. Adding or changing 1 term is great. Adding or changing 10 related terms is ok. Adding or changing 100 or more terms at once should be considered very carefully. 4. Check the Git diff This step is very important. Rather than simply trusting your change had the intended effect, we should always use a git diff as a first pass for sanity checking. In our experience, having a visual git client like GitHub Desktop or sourcetree is really helpful for this part. In case you prefer the command line: git status git diff 5. Quality control Now it's time to run your quality control checks. This can either happen locally ( 5a ) or through your continuous integration system ( 7/5b ). 5a. Local testing If you chose to run your test locally: sh run.sh make IMP=false test This will run the whole set of configured ODK tests on including your change. If you have a complex DOSDP pattern pipeline you may want to add PAT=false to skip the potentially lengthy process of rebuilding the patterns. sh run.sh make IMP=false PAT=false test 6. Pull request When you are happy with the changes, you commit your changes to your feature branch, push them upstream (to GitHub) and create a pull request. For example: git add NAMEOFCHANGEDFILES git commit -m \"Added biological process term #12\" git push -u origin issue23removeprocess Then you go to your project on GitHub, and create a new pull request from the branch, for example: https://github.com/INCATools/ontology-development-kit/pulls There is a lot of great advise on how to write pull requests, but at the very least you should: - mention the tickets affected: see #23 to link to a related ticket, or fixes #23 if, by merging this pull request, the ticket is fixed. Tickets in the latter case will be closed automatically by GitHub when the pull request is merged. - summarise the changes in a few sentences. Consider the reviewer: what would they want to know right away. - If the diff is large, provide instructions on how to review the pull request best (sometimes, there are many changed files, but only one important change). 7/5b. Continuous Integration Testing If you didn't run and local quality control checks (see 5a ), you should have Continuous Integration (CI) set up, for example: - Travis - GitHub Actions More on how to set this up here . Once the pull request is created, the CI will automatically trigger. If all is fine, it will show up green, otherwise red. 8. Community review Once all the automatic tests have passed, it is important to put a second set of eyes on the pull request. Ontologies are inherently social - as in that they represent some kind of community consensus on how a domain is organised conceptually. This seems high brow talk, but it is very important that as an ontology editor, you have your work validated by the community you are trying to serve (e.g. your colleagues, other contributors etc.). In our experience, it is hard to get more than one review on a pull request - two is great. You can set up GitHub branch protection to actually require a review before a pull request can be merged! We recommend this. This step seems daunting to some hopefully under-resourced ontologies, but we recommend to put this high up on your list of priorities - train a colleague, reach out! 9. Merge and cleanup When the QC is green and the reviews are in (approvals), it is time to merge the pull request. After the pull request is merged, remember to delete the branch as well (this option will show up as a big button right after you have merged the pull request). If you have not done so, close all the associated tickets fixed by the pull request. 10. Changelog (Optional) It is sometimes difficult to keep track of changes made to an ontology. Some ontology teams opt to document changes in a changelog (simply a text file in your repository) so that when release day comes, you know everything you have changed. This is advisable at least for major changes (such as a new release system, a new pattern or template etc.).","title":"Editors Workflow"},{"location":"odk-workflows/EditorsWorkflow/#editors-workflow","text":"The editors workflow is one of the formal workflows to ensure that the ontology is developed correctly according to ontology engineering principles. There are a few different editors workflows: Local editing workflow: Editing the ontology in your local environment by hand, using tools such as Prot\u00e9g\u00e9, ROBOT templates or DOSDP patterns. Completely automated data pipeline (GitHub Actions) DROID workflow This document only covers the first editing workflow, but more will be added in the future","title":"Editors Workflow"},{"location":"odk-workflows/EditorsWorkflow/#local-editing-workflow","text":"Workflow requirements: git github docker editing tool of choice, e.g. Prot\u00e9g\u00e9, your favourite text editor, etc","title":"Local editing workflow"},{"location":"odk-workflows/EditorsWorkflow/#1-create-issue","text":"Ensure that there is a ticket on your issue tracker that describes the change you are about to make. While this seems optional, this is a very important part of the social contract of building an ontology - no change to the ontology should be performed without a good ticket, describing the motivation and nature of the intended change.","title":"1. Create issue"},{"location":"odk-workflows/EditorsWorkflow/#2-update-main-branch","text":"In your local environment (e.g. your laptop), make sure you are on the main (prev. master ) branch and ensure that you have all the upstream changes, for example: git checkout master git pull","title":"2. Update main branch"},{"location":"odk-workflows/EditorsWorkflow/#3-create-feature-branch","text":"Create a new branch. Per convention, we try to use meaningful branch names such as: - issue23removeprocess (where issue 23 is the related issue on GitHub) - issue26addcontributor - release20210101 (for releases) On your command line, this looks like this: git checkout -b issue23removeprocess","title":"3. Create feature branch"},{"location":"odk-workflows/EditorsWorkflow/#4-perform-edit","text":"Using your editor of choice, perform the intended edit. For example: Prot\u00e9g\u00e9 Open src/ontology/upheno-edit.owl in Prot\u00e9g\u00e9 Make the change Save the file TextEdit Open src/ontology/upheno-edit.owl in TextEdit (or Sublime, Atom, Vim, Nano) Make the change Save the file Consider the following when making the edit. According to our development philosophy, the only places that should be manually edited are: src/ontology/upheno-edit.owl Any ROBOT templates you chose to use (the TSV files only) Any DOSDP data tables you chose to use (the TSV files, and potentially the associated patterns) components (anything in src/ontology/components ), see here . Imports should not be edited (any edits will be flushed out with the next update). However, refreshing imports is a potentially breaking change - and is discussed elsewhere . Changes should usually be small. Adding or changing 1 term is great. Adding or changing 10 related terms is ok. Adding or changing 100 or more terms at once should be considered very carefully.","title":"4. Perform edit"},{"location":"odk-workflows/EditorsWorkflow/#4-check-the-git-diff","text":"This step is very important. Rather than simply trusting your change had the intended effect, we should always use a git diff as a first pass for sanity checking. In our experience, having a visual git client like GitHub Desktop or sourcetree is really helpful for this part. In case you prefer the command line: git status git diff","title":"4. Check the Git diff"},{"location":"odk-workflows/EditorsWorkflow/#5-quality-control","text":"Now it's time to run your quality control checks. This can either happen locally ( 5a ) or through your continuous integration system ( 7/5b ).","title":"5. Quality control"},{"location":"odk-workflows/EditorsWorkflow/#5a-local-testing","text":"If you chose to run your test locally: sh run.sh make IMP=false test This will run the whole set of configured ODK tests on including your change. If you have a complex DOSDP pattern pipeline you may want to add PAT=false to skip the potentially lengthy process of rebuilding the patterns. sh run.sh make IMP=false PAT=false test","title":"5a. Local testing"},{"location":"odk-workflows/EditorsWorkflow/#6-pull-request","text":"When you are happy with the changes, you commit your changes to your feature branch, push them upstream (to GitHub) and create a pull request. For example: git add NAMEOFCHANGEDFILES git commit -m \"Added biological process term #12\" git push -u origin issue23removeprocess Then you go to your project on GitHub, and create a new pull request from the branch, for example: https://github.com/INCATools/ontology-development-kit/pulls There is a lot of great advise on how to write pull requests, but at the very least you should: - mention the tickets affected: see #23 to link to a related ticket, or fixes #23 if, by merging this pull request, the ticket is fixed. Tickets in the latter case will be closed automatically by GitHub when the pull request is merged. - summarise the changes in a few sentences. Consider the reviewer: what would they want to know right away. - If the diff is large, provide instructions on how to review the pull request best (sometimes, there are many changed files, but only one important change).","title":"6. Pull request"},{"location":"odk-workflows/EditorsWorkflow/#75b-continuous-integration-testing","text":"If you didn't run and local quality control checks (see 5a ), you should have Continuous Integration (CI) set up, for example: - Travis - GitHub Actions More on how to set this up here . Once the pull request is created, the CI will automatically trigger. If all is fine, it will show up green, otherwise red.","title":"7/5b. Continuous Integration Testing"},{"location":"odk-workflows/EditorsWorkflow/#8-community-review","text":"Once all the automatic tests have passed, it is important to put a second set of eyes on the pull request. Ontologies are inherently social - as in that they represent some kind of community consensus on how a domain is organised conceptually. This seems high brow talk, but it is very important that as an ontology editor, you have your work validated by the community you are trying to serve (e.g. your colleagues, other contributors etc.). In our experience, it is hard to get more than one review on a pull request - two is great. You can set up GitHub branch protection to actually require a review before a pull request can be merged! We recommend this. This step seems daunting to some hopefully under-resourced ontologies, but we recommend to put this high up on your list of priorities - train a colleague, reach out!","title":"8. Community review"},{"location":"odk-workflows/EditorsWorkflow/#9-merge-and-cleanup","text":"When the QC is green and the reviews are in (approvals), it is time to merge the pull request. After the pull request is merged, remember to delete the branch as well (this option will show up as a big button right after you have merged the pull request). If you have not done so, close all the associated tickets fixed by the pull request.","title":"9. Merge and cleanup"},{"location":"odk-workflows/EditorsWorkflow/#10-changelog-optional","text":"It is sometimes difficult to keep track of changes made to an ontology. Some ontology teams opt to document changes in a changelog (simply a text file in your repository) so that when release day comes, you know everything you have changed. This is advisable at least for major changes (such as a new release system, a new pattern or template etc.).","title":"10. Changelog (Optional)"},{"location":"odk-workflows/ManageAutomatedTest/","text":"Constraint violation checks We can define custom checks using SPARQL . SPARQL queries define bad modelling patterns (missing labels, misspelt URIs, and many more) in the ontology. If these queries return any results, then the build will fail. Custom checks are designed to be run as part of GitHub Actions Continuous Integration testing, but they can also run locally. Steps to add a constraint violation check: Add the SPARQL query in src/sparql . The name of the file should end with -violation.sparql . Please give a name that helps to understand which violation the query wants to check. Add the name of the new file to odk configuration file src/ontology/uberon-odk.yaml : Include the name of the file (without the -violation.sparql part) to the list inside the key custom_sparql_checks that is inside robot_report key. If the robot_report or custom_sparql_checks keys are not available, please add this code block to the end of the file. yaml robot_report: release_reports: False fail_on: ERROR use_labels: False custom_profile: True report_on: - edit custom_sparql_checks: - name-of-the-file-check 3. Update the repository so your new SPARQL check will be included in the QC. sh run.sh make update_repo","title":"Manage automated tests"},{"location":"odk-workflows/ManageAutomatedTest/#constraint-violation-checks","text":"We can define custom checks using SPARQL . SPARQL queries define bad modelling patterns (missing labels, misspelt URIs, and many more) in the ontology. If these queries return any results, then the build will fail. Custom checks are designed to be run as part of GitHub Actions Continuous Integration testing, but they can also run locally.","title":"Constraint violation checks"},{"location":"odk-workflows/ManageAutomatedTest/#steps-to-add-a-constraint-violation-check","text":"Add the SPARQL query in src/sparql . The name of the file should end with -violation.sparql . Please give a name that helps to understand which violation the query wants to check. Add the name of the new file to odk configuration file src/ontology/uberon-odk.yaml : Include the name of the file (without the -violation.sparql part) to the list inside the key custom_sparql_checks that is inside robot_report key. If the robot_report or custom_sparql_checks keys are not available, please add this code block to the end of the file. yaml robot_report: release_reports: False fail_on: ERROR use_labels: False custom_profile: True report_on: - edit custom_sparql_checks: - name-of-the-file-check 3. Update the repository so your new SPARQL check will be included in the QC. sh run.sh make update_repo","title":"Steps to add a constraint violation check:"},{"location":"odk-workflows/ManageDocumentation/","text":"Updating the Documentation The documentation for UPHENO is managed in two places (relative to the repository root): The docs directory contains all the files that pertain to the content of the documentation (more below) the mkdocs.yaml file contains the documentation config, in particular its navigation bar and theme. The documentation is hosted using GitHub pages, on a special branch of the repository (called gh-pages ). It is important that this branch is never deleted - it contains all the files GitHub pages needs to render and deploy the site. It is also important to note that the gh-pages branch should never be edited manually . All changes to the docs happen inside the docs directory on the main branch. Editing the docs Changing content All the documentation is contained in the docs directory, and is managed in Markdown . Markdown is a very simple and convenient way to produce text documents with formatting instructions, and is very easy to learn - it is also used, for example, in GitHub issues. This is a normal editing workflow: Open the .md file you want to change in an editor of choice (a simple text editor is often best). IMPORTANT : Do not edit any files in the docs/odk-workflows/ directory. These files are managed by the ODK system and will be overwritten when the repository is upgraded! If you wish to change these files, make an issue on the ODK issue tracker . Perform the edit and save the file Commit the file to a branch, and create a pull request as usual. If your development team likes your changes, merge the docs into master branch. Deploy the documentation (see below) Deploy the documentation The documentation is not automatically updated from the Markdown, and needs to be deployed deliberately. To do this, perform the following steps: In your terminal, navigate to the edit directory of your ontology, e.g.: cd upheno/src/ontology Now you are ready to build the docs as follows: sh run.sh make update_docs Mkdocs now sets off to build the site from the markdown pages. You will be asked to Enter your username Enter your password (see here for using GitHub access tokens instead) IMPORTANT : Using password based authentication will be deprecated this year (2021). Make sure you read up on personal access tokens if that happens! If everything was successful, you will see a message similar to this one: INFO - Your documentation should shortly be available at: https://obophenotype.github.io/upheno/ 3. Just to double check, you can now navigate to your documentation pages (usually https://obophenotype.github.io/upheno/). Just make sure you give GitHub 2-5 minutes to build the pages!","title":"Manage documentation"},{"location":"odk-workflows/ManageDocumentation/#updating-the-documentation","text":"The documentation for UPHENO is managed in two places (relative to the repository root): The docs directory contains all the files that pertain to the content of the documentation (more below) the mkdocs.yaml file contains the documentation config, in particular its navigation bar and theme. The documentation is hosted using GitHub pages, on a special branch of the repository (called gh-pages ). It is important that this branch is never deleted - it contains all the files GitHub pages needs to render and deploy the site. It is also important to note that the gh-pages branch should never be edited manually . All changes to the docs happen inside the docs directory on the main branch.","title":"Updating the Documentation"},{"location":"odk-workflows/ManageDocumentation/#editing-the-docs","text":"","title":"Editing the docs"},{"location":"odk-workflows/ManageDocumentation/#changing-content","text":"All the documentation is contained in the docs directory, and is managed in Markdown . Markdown is a very simple and convenient way to produce text documents with formatting instructions, and is very easy to learn - it is also used, for example, in GitHub issues. This is a normal editing workflow: Open the .md file you want to change in an editor of choice (a simple text editor is often best). IMPORTANT : Do not edit any files in the docs/odk-workflows/ directory. These files are managed by the ODK system and will be overwritten when the repository is upgraded! If you wish to change these files, make an issue on the ODK issue tracker . Perform the edit and save the file Commit the file to a branch, and create a pull request as usual. If your development team likes your changes, merge the docs into master branch. Deploy the documentation (see below)","title":"Changing content"},{"location":"odk-workflows/ManageDocumentation/#deploy-the-documentation","text":"The documentation is not automatically updated from the Markdown, and needs to be deployed deliberately. To do this, perform the following steps: In your terminal, navigate to the edit directory of your ontology, e.g.: cd upheno/src/ontology Now you are ready to build the docs as follows: sh run.sh make update_docs Mkdocs now sets off to build the site from the markdown pages. You will be asked to Enter your username Enter your password (see here for using GitHub access tokens instead) IMPORTANT : Using password based authentication will be deprecated this year (2021). Make sure you read up on personal access tokens if that happens! If everything was successful, you will see a message similar to this one: INFO - Your documentation should shortly be available at: https://obophenotype.github.io/upheno/ 3. Just to double check, you can now navigate to your documentation pages (usually https://obophenotype.github.io/upheno/). Just make sure you give GitHub 2-5 minutes to build the pages!","title":"Deploy the documentation"},{"location":"odk-workflows/ReleaseWorkflow/","text":"The release workflow The release workflow recommended by the ODK is based on GitHub releases and works as follows: Run a release with the ODK Review the release Merge to main branch Create a GitHub release These steps are outlined in detail in the following. Run a release with the ODK Preparation: Ensure that all your pull requests are merged into your main (master) branch Make sure that all changes to master are committed to GitHub ( git status should say that there are no modified files) Locally make sure you have the latest changes from master ( git pull ) Checkout a new branch (e.g. git checkout -b release-2021-01-01 ) You may or may not want to refresh your imports as part of your release strategy (see here ) Make sure you have the latest ODK installed by running docker pull obolibrary/odkfull To actually run the release, you: Open a command line terminal window and navigate to the src/ontology directory ( cd upheno/src/ontology ) Run release pipeline: sh run.sh make prepare_release -B . Note that for some ontologies, this process can take up to 90 minutes - especially if there are large ontologies you depend on, like PRO or CHEBI. If everything went well, you should see the following output on your machine: Release files are now in ../.. - now you should commit, push and make a release on your git hosting site such as GitHub or GitLab . This will create all the specified release targets (OBO, OWL, JSON, and the variants, ont-full and ont-base) and copy them into your release directory (the top level of your repo). Review the release (Optional) Rough check. This step is frequently skipped, but for the more paranoid among us (like the author of this doc), this is a 3 minute additional effort for some peace of mind. Open the main release (upheno.owl) in you favourite development environment (i.e. Prot\u00e9g\u00e9) and eyeball the hierarchy. We recommend two simple checks: Does the very top level of the hierarchy look ok? This means that all new terms have been imported/updated correctly. Does at least one change that you know should be in this release appear? For example, a new class. This means that the release was actually based on the recent edit file. Commit your changes to the branch and make a pull request In your GitHub pull request, review the following three files in detail (based on our experience): upheno.obo - this reflects a useful subset of the whole ontology (everything that can be covered by OBO format). OBO format has that speaking for it: it is very easy to review! upheno-base.owl - this reflects the asserted axioms in your ontology that you have actually edited. Ideally also take a look at upheno-full.owl , which may reveal interesting new inferences you did not know about. Note that the diff of this file is sometimes quite large. Like with every pull request, we recommend to always employ a second set of eyes when reviewing a PR! Merge the main branch Once your CI checks have passed, and your reviews are completed, you can now merge the branch into your main branch (don't forget to delete the branch afterwards - a big button will appear after the merge is finished). Create a GitHub release Go to your releases page on GitHub by navigating to your repository, and then clicking on releases (usually on the right, for example: https://github.com/obophenotype/upheno/releases). Then click \"Draft new release\" As the tag version you need to choose the date on which your ontologies were build. You can find this, for example, by looking at the upheno.obo file and check the data-version: property. The date needs to be prefixed with a v , so, for example v2020-02-06 . You can write whatever you want in the release title, but we typically write the date again. The description underneath should contain a concise list of changes or term additions. Click \"Publish release\". Done. Debugging typical ontology release problems Problems with memory When you are dealing with large ontologies, you need a lot of memory. When you see error messages relating to large ontologies such as CHEBI, PRO, NCBITAXON, or Uberon, you should think of memory first, see here . Problems when using OBO format based tools Sometimes you will get cryptic error messages when using legacy tools using OBO format, such as the ontology release tool (OORT), which is also available as part of the ODK docker container. In these cases, you need to track down what axiom or annotation actually caused the breakdown. In our experience (in about 60% of the cases) the problem lies with duplicate annotations ( def , comment ) which are illegal in OBO. Here is an example recipe of how to deal with such a problem: If you get a message like make: *** [cl.Makefile:84: oort] Error 255 you might have a OORT error. To debug this, in your terminal enter sh run.sh make IMP=false PAT=false oort -B (assuming you are already in the ontology folder in your directory) This should show you where the error is in the log (eg multiple different definitions) WARNING: THE FIX BELOW IS NOT IDEAL, YOU SHOULD ALWAYS TRY TO FIX UPSTREAM IF POSSIBLE Open upheno-edit.owl in Prot\u00e9g\u00e9 and find the offending term and delete all offending issue (e.g. delete ALL definition, if the problem was \"multiple def tags not allowed\") and save. *While this is not idea, as it will remove all definitions from that term, it will be added back again when the term is fixed in the ontology it was imported from and added back in. Rerun sh run.sh make IMP=false PAT=false oort -B and if it all passes, commit your changes to a branch and make a pull request as usual.","title":"Release Workflow"},{"location":"odk-workflows/ReleaseWorkflow/#the-release-workflow","text":"The release workflow recommended by the ODK is based on GitHub releases and works as follows: Run a release with the ODK Review the release Merge to main branch Create a GitHub release These steps are outlined in detail in the following.","title":"The release workflow"},{"location":"odk-workflows/ReleaseWorkflow/#run-a-release-with-the-odk","text":"Preparation: Ensure that all your pull requests are merged into your main (master) branch Make sure that all changes to master are committed to GitHub ( git status should say that there are no modified files) Locally make sure you have the latest changes from master ( git pull ) Checkout a new branch (e.g. git checkout -b release-2021-01-01 ) You may or may not want to refresh your imports as part of your release strategy (see here ) Make sure you have the latest ODK installed by running docker pull obolibrary/odkfull To actually run the release, you: Open a command line terminal window and navigate to the src/ontology directory ( cd upheno/src/ontology ) Run release pipeline: sh run.sh make prepare_release -B . Note that for some ontologies, this process can take up to 90 minutes - especially if there are large ontologies you depend on, like PRO or CHEBI. If everything went well, you should see the following output on your machine: Release files are now in ../.. - now you should commit, push and make a release on your git hosting site such as GitHub or GitLab . This will create all the specified release targets (OBO, OWL, JSON, and the variants, ont-full and ont-base) and copy them into your release directory (the top level of your repo).","title":"Run a release with the ODK"},{"location":"odk-workflows/ReleaseWorkflow/#review-the-release","text":"(Optional) Rough check. This step is frequently skipped, but for the more paranoid among us (like the author of this doc), this is a 3 minute additional effort for some peace of mind. Open the main release (upheno.owl) in you favourite development environment (i.e. Prot\u00e9g\u00e9) and eyeball the hierarchy. We recommend two simple checks: Does the very top level of the hierarchy look ok? This means that all new terms have been imported/updated correctly. Does at least one change that you know should be in this release appear? For example, a new class. This means that the release was actually based on the recent edit file. Commit your changes to the branch and make a pull request In your GitHub pull request, review the following three files in detail (based on our experience): upheno.obo - this reflects a useful subset of the whole ontology (everything that can be covered by OBO format). OBO format has that speaking for it: it is very easy to review! upheno-base.owl - this reflects the asserted axioms in your ontology that you have actually edited. Ideally also take a look at upheno-full.owl , which may reveal interesting new inferences you did not know about. Note that the diff of this file is sometimes quite large. Like with every pull request, we recommend to always employ a second set of eyes when reviewing a PR!","title":"Review the release"},{"location":"odk-workflows/ReleaseWorkflow/#merge-the-main-branch","text":"Once your CI checks have passed, and your reviews are completed, you can now merge the branch into your main branch (don't forget to delete the branch afterwards - a big button will appear after the merge is finished).","title":"Merge the main branch"},{"location":"odk-workflows/ReleaseWorkflow/#create-a-github-release","text":"Go to your releases page on GitHub by navigating to your repository, and then clicking on releases (usually on the right, for example: https://github.com/obophenotype/upheno/releases). Then click \"Draft new release\" As the tag version you need to choose the date on which your ontologies were build. You can find this, for example, by looking at the upheno.obo file and check the data-version: property. The date needs to be prefixed with a v , so, for example v2020-02-06 . You can write whatever you want in the release title, but we typically write the date again. The description underneath should contain a concise list of changes or term additions. Click \"Publish release\". Done.","title":"Create a GitHub release"},{"location":"odk-workflows/ReleaseWorkflow/#debugging-typical-ontology-release-problems","text":"","title":"Debugging typical ontology release problems"},{"location":"odk-workflows/ReleaseWorkflow/#problems-with-memory","text":"When you are dealing with large ontologies, you need a lot of memory. When you see error messages relating to large ontologies such as CHEBI, PRO, NCBITAXON, or Uberon, you should think of memory first, see here .","title":"Problems with memory"},{"location":"odk-workflows/ReleaseWorkflow/#problems-when-using-obo-format-based-tools","text":"Sometimes you will get cryptic error messages when using legacy tools using OBO format, such as the ontology release tool (OORT), which is also available as part of the ODK docker container. In these cases, you need to track down what axiom or annotation actually caused the breakdown. In our experience (in about 60% of the cases) the problem lies with duplicate annotations ( def , comment ) which are illegal in OBO. Here is an example recipe of how to deal with such a problem: If you get a message like make: *** [cl.Makefile:84: oort] Error 255 you might have a OORT error. To debug this, in your terminal enter sh run.sh make IMP=false PAT=false oort -B (assuming you are already in the ontology folder in your directory) This should show you where the error is in the log (eg multiple different definitions) WARNING: THE FIX BELOW IS NOT IDEAL, YOU SHOULD ALWAYS TRY TO FIX UPSTREAM IF POSSIBLE Open upheno-edit.owl in Prot\u00e9g\u00e9 and find the offending term and delete all offending issue (e.g. delete ALL definition, if the problem was \"multiple def tags not allowed\") and save. *While this is not idea, as it will remove all definitions from that term, it will be added back again when the term is fixed in the ontology it was imported from and added back in. Rerun sh run.sh make IMP=false PAT=false oort -B and if it all passes, commit your changes to a branch and make a pull request as usual.","title":"Problems when using OBO format based tools"},{"location":"odk-workflows/RepoManagement/","text":"Managing your ODK repository Updating your ODK repository Your ODK repositories configuration is managed in src/ontology/upheno-odk.yaml . Once you have made your changes, you can run the following to apply your changes to the repository: sh run.sh make update_repo There are a large number of options that can be set to configure your ODK, but we will only discuss a few of them here. NOTE for Windows users: You may get a cryptic failure such as Set Illegal Option - if the update script located in src/scripts/update_repo.sh was saved using Windows Line endings. These need to change to unix line endings. In Notepad++, for example, you can click on Edit->EOL Conversion->Unix LF to change this. Managing imports You can use the update repository workflow described on this page to perform the following operations to your imports: Add a new import Modify an existing import Remove an import you no longer want Customise an import We will discuss all these workflows in the following. Add new import To add a new import, you first edit your odk config as described above , adding an id to the product list in the import_group section (for the sake of this example, we assume you already import RO, and your goal is to also import GO): import_group: products: - id: ro - id: go Note: our ODK file should only have one import_group which can contain multiple imports (in the products section). Next, you run the update repo workflow to apply these changes. Note that by default, this module is going to be a SLME Bottom module, see here . To change that or customise your module, see section \"Customise an import\". To finalise the addition of your import, perform the following steps: Add an import statement to your src/ontology/upheno-edit.owl file. We suggest to do this using a text editor, by simply copying an existing import declaration and renaming it to the new ontology import, for example as follows: ... Ontology(Authors:
+ +Last update: 27.03.2024.
+Authors:
+ +Last update: 27.03.2024.
+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.
+| Category | +Example datasets | +Example phenotype | +
|---|---|---|
| Gene to phenotype associations | +Online Mendelian Inheritance in Man (OMIM), Human Phenotype Ontology (HPO), Gene Ontology (GO) | +Achondroplasia (associated with FGFR3 gene mutations) | +
| Gene to disease associations | +The Cancer Genome Atlas (TCGA), Online Mendelian Inheritance in Man (OMIM), GWAS Catalog | +Breast invasive carcinoma (associated with BRCA1/BRCA2 mutations) | +
| Phenotype-phenotype semantic similarity | +Human Phenotype Ontology (HPO), Unified Medical Language System (UMLS), Disease Ontology (DO) | +Cardiac abnormalities (semantic similarity with congenital heart defects) | +
| Quantified trait data (QTL etc) | +NHGRI-EBI GWAS Catalog, Genotype-Tissue Expression (GTEx), The Human Protein Atlas | +Height (quantified trait associated with SNPs in genomic regions) | +
| Electronic health records | +Medical Information Mart for Intensive Care III (MIMIC-III), UK Biobank, IBM Watson Health | +Acute kidney injury (recorded diagnosis during ICU stay) | +
| Epidemiological datasets | +Framingham Heart Study, National Health and Nutrition Examination Survey (NHANES), Global Burden of Disease Study (GBD) | +Cardiovascular disease (epidemiological study of risk factors and disease incidence) | +
| Clinical trial datasets | +ClinicalTrials.gov, European Union Clinical Trials Register (EUCTR), International Clinical Trials Registry Platform (ICTRP) | +Treatment response (clinical trial data on efficacy and safety outcomes) | +
| Environmental exposure datasets | +Environmental Protection Agency Air Quality System (EPA AQS), Global Historical Climatology Network (GHCN), National Centers for Environmental Information Climate Data Online (NCEI CDO) | +Respiratory diseases (association with air pollutant exposure) | +
| Population surveys e.g., UK Biobank | +UK Biobank, National Health Interview Survey (NHIS), National Health and Nutrition Examination Survey (NHANES) | +Chronic diseases (population-based study on disease prevalence and risk factors) | +
| Behavioral observation datasets | +National Survey on Drug Use and Health (NSDUH), Add Health, British Cohort Study (BCS) | +Substance abuse disorders (survey data on drug consumption and addiction) | +
