Tripal v3, the Collaborative Online Database Platform Supporting an International Community of Plant Genome Databases

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Talk given by Dr. Bradford Condon at the NSRP10 session of the Plant and Animal Genomes conference (PAG) 2019. Covers the basics of the biological database toolkit Tripal, and how Tripal enables FAIR data.

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Tripal v3, the Collaborative Online Database Platform
Supporting an International Community of Plant Genome
Databases
Bradford Condon, Stephen Ficklin, Meg Staton
Hardwood Genomics/University of Tennessee Knoxville, i5k NAL/USDA
@bradfordcondon

A web framework for genetic and genomic data
Goals:
• Simplify construction of websites that have biological
data
• Encourage high-quality, standards-based websites
for data sharing and collaboration
• Reuse code across databases
http://tripal.info
https://tripal.readthedocs.io/en/latest/user_guide.html

Tripal is a Drupal module
Content authoring
Security updates
Page routing
Layout
Ecosystem of modules
Highly customizable
Established community
https://www.drupal.org/about

Tripal Core Functions
● Load, Store, and Display
Chado Content
○ Organisms
○ Contacts
○ Analyses
○ Features
● Map Controlled Vocabularies
● Jobs Management
● Web Services
https://github.com/GMOD/Chado

Example Extension Modules
• Transcriptomes
• Functional annotation:
• BLAST
• KEGG
• InterPro
• Gene Ontology
• BLAST server
• Breeding API
• NCBI data Import
https://tripal.readthedocs.io/en/latest/extensions.html
• Genetic and Physical
Maps
• Jbrowse
• Apollo
• Galaxy
• Stocks/Germplasm
• Phenotypes
• Genotypes
• Phylogenies
• Gene expression data

Cooperative Database
Development
• Washington State University
• University of Saskatchewan
• University of Tennessee,
Knoxville
• Iowa State University
• University of Connecticut
• USDA National Agricultural
Library
• Bioversity International (France)
13 code
contributors
64 modules on
GitHub
electively
tagged as tripal
https://github.com/topics/tripal

Tripal s FAIR
Why do we care?
• FAIR emphasizes
helping machines to
find and reuse data
• Make your life easier
(biologist)
• Write new tools and
code that will work
with all data

Expression Module
Biological
Samples
RNA Libraries Gene Expression
Levels
Need a better way to store and visualize RNASeq differential gene
expression experiments.
https://github.com/tripal/tripal_analysis_expression

Easy administration and curation
Metadata

Individual genes across samples
Users choose
how to group and
color samples
SchlesserSparrow
Sparrow x Schlesser
Metadata

Expression Visualization Tool
• Paste a list of genes in to get a full heatmap across all
libraries.
• Javascript allows you to zoom, download, etc.

Module Sharing:
Gene Expression Works for GDV Too
https://www.vaccinium.org/node/854703

Elasticsearch Software
Open source search engine
• Features - autocomplete, fuzzy searching, “did you mean”
suggestions
Tripal Elasticsearch
• Full administrative control of content indexing
• Can search all content
• Much easier for software developers to use
• Easily build advanced search forms
• Preconfigured indices for Chado data
Findable

Conclusions
• Tripal 3 can make FAIR possible for
your data
• Tripal already has lots of modules to
support common data types
• Organism, feature, expression, search
• Tools - GMOD
• Tripal allows small communities to
“have their cake and eat it too”
• Sharing and reusing code
• Interoperability at database and site level
with other databases
• Customizable user experience

Abdullah Almsaeed
Research Associate
Stephen Ficklin
Dorrie Main
Jill Wegrzyn
Bert Abbott
Dana Nelson
Meg Staton
Abdullah Almsaeed
Chris Childers
Monica Poelchau
https://www.hardwoodgenomics.org/
http://tripal.info/
Tripal Session this afternoon!

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How fast can you modify your data collection to include a new field, make all the necessary changes in data processing and storage, and then use that field in analytics or product features? For many companies, the answer is a few quarters, whereas others do it in a day. This data agility latency has a direct impact on companies' ability to innovate with data. Schema-on-read has been a key strategy to lower that latency - as the community has shifted towards storing data outside relational databases, we no longer need to make series of schema changes through the whole data chain, coordinated between teams to minimise operational risk. Schema-on-read comes with a cost, however. Errors that we used to catch during testing or in early test deployments can now sneak into production undetected and surface as product errors or hard-to-debug data quality problems later than with schema-on-write solutions. In this presentation, we will show how we have rejected the tradeoff between slow schema change rate and quality to achieve the best of both worlds. By using metaprogramming and versioned pipelines that are tested end-to-end, we can achieve fast schema changes with schema-on-write and the protection of static typing. We will describe the tools in our toolbox - Scalameta, Chimney, Bazel, and custom tools. We will also show how we leverage them to take static typing one step further and differentiate between domain types that share representation, e.g. EmailAddress vs ValidatedEmailAddress or kW vs kWh, while maintaining harmony with data technology ecosystems.

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Tripal v3, the Collaborative Online Database Platform Supporting an International Community of Plant Genome Databases

1. Tripal v3, the Collaborative Online Database Platform Supporting an International Community of Plant Genome Databases Bradford Condon, Stephen Ficklin, Meg Staton Hardwood Genomics/University of Tennessee Knoxville, i5k NAL/USDA @bradfordcondon

2. A web framework for genetic and genomic data Goals: • Simplify construction of websites that have biological data • Encourage high-quality, standards-based websites for data sharing and collaboration • Reuse code across databases http://tripal.info https://tripal.readthedocs.io/en/latest/user_guide.html

5. Tripal is a Drupal module Content authoring Security updates Page routing Layout Ecosystem of modules Highly customizable Established community https://www.drupal.org/about

6. Tripal Core Functions ● Load, Store, and Display Chado Content ○ Organisms ○ Contacts ○ Analyses ○ Features ● Map Controlled Vocabularies ● Jobs Management ● Web Services https://github.com/GMOD/Chado

7. Example Extension Modules • Transcriptomes • Functional annotation: • BLAST • KEGG • InterPro • Gene Ontology • BLAST server • Breeding API • NCBI data Import https://tripal.readthedocs.io/en/latest/extensions.html • Genetic and Physical Maps • Jbrowse • Apollo • Galaxy • Stocks/Germplasm • Phenotypes • Genotypes • Phylogenies • Gene expression data

8. Cooperative Database Development • Washington State University • University of Saskatchewan • University of Tennessee, Knoxville • Iowa State University • University of Connecticut • USDA National Agricultural Library • Bioversity International (France) 13 code contributors 64 modules on GitHub electively tagged as tripal https://github.com/topics/tripal

9. Tripal s FAIR Why do we care? • FAIR emphasizes helping machines to find and reuse data • Make your life easier (biologist) • Write new tools and code that will work with all data

10. How does Tripal do FAIR? Metadata

11. Expression Module Biological Samples RNA Libraries Gene Expression Levels Need a better way to store and visualize RNASeq differential gene expression experiments. https://github.com/tripal/tripal_analysis_expression

12. Easy administration and curation Metadata

13. Individual genes across samples Users choose how to group and color samples SchlesserSparrow Sparrow x Schlesser Metadata

14. Expression Visualization Tool • Paste a list of genes in to get a full heatmap across all libraries. • Javascript allows you to zoom, download, etc.

15. Module Sharing: Gene Expression Works for GDV Too https://www.vaccinium.org/node/854703

16. Ontology Browser

17. Elasticsearch Software Open source search engine • Features - autocomplete, fuzzy searching, “did you mean” suggestions Tripal Elasticsearch • Full administrative control of content indexing • Can search all content • Much easier for software developers to use • Easily build advanced search forms • Preconfigured indices for Chado data Findable

18.

19. Cross Site Querying

20. Conclusions • Tripal 3 can make FAIR possible for your data • Tripal already has lots of modules to support common data types • Organism, feature, expression, search • Tools - GMOD • Tripal allows small communities to “have their cake and eat it too” • Sharing and reusing code • Interoperability at database and site level with other databases • Customizable user experience

21. Abdullah Almsaeed Research Associate Stephen Ficklin Dorrie Main Jill Wegrzyn Bert Abbott Dana Nelson Meg Staton Abdullah Almsaeed Chris Childers Monica Poelchau https://www.hardwoodgenomics.org/ http://tripal.info/ Tripal Session this afternoon!

Tripal v3, the Collaborative Online Database Platform Supporting an International Community of Plant Genome Databases

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