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IRIDA: Canada’s federated platform
for genomic epidemiology
William Hsiao, Ph.D.
William.hsiao@bccdc.ca
@wlhsiao
BC Public Health Microbiology and Reference Laboratory
and University of British Columbia
ABPHM 2015
Genome Canada Bioinformatics Competition: Large-Scale Project
“A Federated Bioinformatics Platform for
Public Health Microbial Genomics”
Our Goal
The IRIDA platform
(Integrated Rapid Infectious Disease Analysis)
An open source, standards compliant, high quality genomic epidemiology
analysis platform to support real-time (food-borne) disease outbreak
investigations
2 www.IRIDA.ca
3
Each year, one in eight Canadians (or
four million people)
get sick with a domestically acquired
food-borne illness.
Partnership among public health agencies and academic institutes to bridge the gaps
between advancements in genomic epidemiology and application to real-life and real-
time use cases in public health agencies
- Project Team has direct access to state of the art research in academia
- Project Team is directly embedded in user organization
Interviews with key personnel to identify
barriers to implement genomic epidemiology in
public health agencies
5
GAP 1: PUBLIC HEALTH PERSONNEL
LACK TRAINING IN GENOMICS
Solution 1a: Build a User Friendly, high quality
analysis platform to process genomics data
• Carefully designed and engineered software platform is
just the starting point… User
Interface
Security
File system
Metadata
Storage
Application
logic
REST API
Workflow Execution Manager
Continuous Integration Documentation
• Easy to use interface hiding the technical details
Solution 1a: Build a User Friendly, high quality
analysis platform to process genomics data
Solution 1a: Build a User Friendly, high quality
analysis platform to process genomics data
Solution 1b: Build Portable and Transparent
Pipelines
• Use Galaxy as workflow engine – large
community support
• Retools to address usability, security, and
other limitations
• Version Controlled Pipeline Templates
• Input files, parameters, and workflow are
sent to IRIDA-specific Galaxy for execution
• Results and provenance information are
copied from Galaxy
1. Input
files sent to
Galaxy
3. Results
downloaded
from Galaxy
IRIDA UI/DB
Galaxy
Assembly Tools
Variant Calling Tools
…
REST API
Shared File System
Worker Worker
2. Tools executed
on Galaxy workers
Solution 1c: Start the training NOW!
• Canada’s National Microbiology Laboratory has hosted
genomic workshops for partners and collaborators
• IRIDA Project has dedicated funding for hosting workshops in
4Q of 2015 and 2016
• We would like to hear about other training initiatives and
share experience and training material
GAP 2: INFORMATION SHARING IS
INEFFICIENT AND AD-HOC
Many Players in surveillance and outbreak –
ineffective information sharing
Source: M. Taylor, BCCDC
Provincial public
health dept.
National laboratory
Local public
health dept.
Provincial
laboratory
Cases
Physicians Frontline lab
Information
BioinformaticsandAnalyticalCapacities
Many Systems used in Reporting Diseases –
require data re-entry and re-coding
National Ministry of
Health
Provincial public
health dept.
National laboratory
Local public
health dept.
Provincial
laboratory
Cases
Physicians Local laboratory
Fax/Electronic
Fax
Phone/Fax
Electronic/Paper
Electronic/Fax/Phone
Mailing of
Samples/Fax/Eelctroni
c
Source: M. Taylor, BCCDC
IRIDA is designed with these dilemma in mind
• Solutions:
– 2a: Localized Instance of federated databases
– 2b: Permission Control – authentication /authorization for
information sharing
– 2c: User role-based display of information
Solution 2a: Local/Cloud Instances and Data
Federation
• Data processing capacity pushed to data generating
labs
• Allow data sharing securely for enhanced analysis
• Eventually cultivating a culture of openness of data
sharing and collaborative development of tools
16
Authorization
Solution 2b: Security
• Local authorization per instance.
• Method-level authorization.
• Object-level authorization.
• Allow secure, fine grained and
flexible information sharing
Solution 2c: Role-based Dynamic Display driven
by Ontology
• Ontologies often lack a content management system (CMS)
• An Interface Model Ontology (IFM) can define a CMS for an
ontology
IFM Interface View Permissions
Detailed View Restricted View
E.g. User role permissions control visibility and editing of content
GAP 3: INFORMATION
REPRESENTATION IS INCONSISTENT
Solution 3a: Use Ontology
• Ontology: a way to describe types of entities
and relations between them
• Why use ontology
– Ontology is flexible and expandable
– Lower levels of expressivity (e.g. controlled vocabulary,
data dictionary) are heavy handed and show low level of
compliance and adoption
– Free text used as an alternative that are not computing
friendly
– Ontology and semantic web technologies may be a
solution
Many Domains of Knowledge are needed to describe
an outbreak investigation Build On, Work With:
OBI
TypON
NGSOnto
NIAID-GSC-BRC core metadata
MIxS Ontology
NCBI Biosample etc
TRANS – Pathogen Transmission
EPO
Exposure Ontology
Infectious Disease Ontology
CARD, ARO for AMR
USDA Nutrient DB
EFSA Comp. Food Consump. DB
Example gaps to be filled:
Expand food ontology; expand CARD
AMR data with others.
Lab Checklist/Ontology
• Currently finishing a lab/genomics checklist and
starting an epidemiology checklist
• Metadata Domains:
– Sample Collection
– Sample Source
– Environmental
– Lab Analytics
– Sequencing Process /QC
– Sequencing Run /QC
– Assembly Process / QC
– Others overlapping with Epi: Demographic / Geographic /
etc.
GAP 4: GENOMIC DATA
INTERPRETATION IS COMPLEX AND
TECHNOLOGY IS EVOLVING
Solution 4a: Use of QA/QC in IRIDA
• Software Engineering
– High quality software that meets regulatory guidelines
– Open Source product to ensure “white box” testing
– Ontology driven software development
– Follow proper software development cycle
• Data Quality
– Built-in modules to check for input data quality
– Warnings and Feedbacks during pipeline execution to laboratory technologists
– Use of Ontology to check metadata (non-genomic) data quality
• Analytic Tool Quality
– Utilize validation datasets
– Use of abstract pipeline description – with version control
– Periodic analysis of exceptions and boundary cases to assess tool accuracy
Solution 4b: Generation of validation datasets
To Participate, Contact
Rene Hendriksen
rshe@food.dtu.dk
Or
Errol Strain
Errol.Strain@fda.hhs.gov
http://www.globalmicrobialidentifier.org/Workgroups#work-group-4
Solution 4c: Exploratory tools can access certain
data via REST API securely
27
http://pathogenomics.sfu.ca/islandviewer
IslandViewer
Dhillon and Laird et al. 2015, Nucleic Acids
Research
http://kiwi.cs.dal.ca/GenGIS
Parks et al. 2013, PLoS One
Availability
• Jun 1 2015: IRIDA 1.0 beta Internal Release
– Release to collaborators for installation and full test
• Jul 1 2015: IRIDA 1.0 beta1
– Announce Beta release, download, documentation
available on website – www.irida.ca
• Aug 1 2015: IRIDA 1.0 beta2
– Cloud installer, with documentation
– Additional pipelines as available
– Visualization as available
Acknowledgements
Project Leaders
Fiona Brinkman – SFU
Will Hsiao – PHMRL
Gary Van Domselaar – NML
University of Lisbon
Joᾶo Carriҫo
National Microbiology Laboratory (NML)
Franklin Bristow
Aaron Petkau
Thomas Matthews
Josh Adam
Adam Olson
Tarah Lynch
Shaun Tyler
Philip Mabon
Philip Au
Celine Nadon
Matthew Stuart-Edwards
Morag Graham
Chrystal Berry
Lorelee Tschetter
Aleisha Reimer
Laboratory for Foodborne Zoonoses (LFZ)
Eduardo Taboada
Peter Kruczkiewicz
Chad Laing
Vic Gannon
Matthew Whiteside
Ross Duncan
Steven Mutschall
Simon Fraser University (SFU)
Melanie Courtot
Emma Griffiths
Geoff Winsor
Julie Shay
Matthew Laird
Bhav Dhillon
Raymond Lo
BC Public Health Microbiology &
Reference Laboratory (PHMRL) and BC
Centre for Disease Control (BCCDC)
Judy Isaac-Renton
Patrick Tang
Natalie Prystajecky
Jennifer Gardy
Damion Dooley
Linda Hoang
Kim MacDonald
Yin Chang
Eleni Galanis
Marsha Taylor
Cletus D’Souza
Ana Paccagnella
University of Maryland
Lynn Schriml
Canadian Food Inspection Agency (CFIA)
Burton Blais
Catherine Carrillo
Dominic Lambert
Dalhousie University
Rob Beiko
Alex Keddy
29
McMaster University
Andrew McArthur
Daim Sardar
European Nucleotide Archive
Guy Cochrane
Petra ten Hoopen
Clara Amid
European Food Safety Agency
Leibana Criado Ernesto
Vernazza Francesco
Rizzi Valentina
30
30
IRIDA Annual General Meeting
Winnipeg, April 8-9, 2015
The IRIDA platform
(Integrated Rapid Infectious Disease Analysis)
An open source, standards compliant, high quality genomic epidemiology
analysis platform to support real-time (food-borne) disease outbreak
investigations
Contacts:
William.hsiao@bccdc.ca
@wlhsiao
31 www.IRIDA.ca

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IRIDA: Canada’s federated platform for genomic epidemiology, ABPHM 2015 WHsiao

  • 1. IRIDA: Canada’s federated platform for genomic epidemiology William Hsiao, Ph.D. William.hsiao@bccdc.ca @wlhsiao BC Public Health Microbiology and Reference Laboratory and University of British Columbia ABPHM 2015
  • 2. Genome Canada Bioinformatics Competition: Large-Scale Project “A Federated Bioinformatics Platform for Public Health Microbial Genomics” Our Goal The IRIDA platform (Integrated Rapid Infectious Disease Analysis) An open source, standards compliant, high quality genomic epidemiology analysis platform to support real-time (food-borne) disease outbreak investigations 2 www.IRIDA.ca
  • 3. 3 Each year, one in eight Canadians (or four million people) get sick with a domestically acquired food-borne illness.
  • 4. Partnership among public health agencies and academic institutes to bridge the gaps between advancements in genomic epidemiology and application to real-life and real- time use cases in public health agencies - Project Team has direct access to state of the art research in academia - Project Team is directly embedded in user organization
  • 5. Interviews with key personnel to identify barriers to implement genomic epidemiology in public health agencies 5
  • 6. GAP 1: PUBLIC HEALTH PERSONNEL LACK TRAINING IN GENOMICS
  • 7. Solution 1a: Build a User Friendly, high quality analysis platform to process genomics data • Carefully designed and engineered software platform is just the starting point… User Interface Security File system Metadata Storage Application logic REST API Workflow Execution Manager Continuous Integration Documentation
  • 8. • Easy to use interface hiding the technical details Solution 1a: Build a User Friendly, high quality analysis platform to process genomics data
  • 9. Solution 1a: Build a User Friendly, high quality analysis platform to process genomics data
  • 10. Solution 1b: Build Portable and Transparent Pipelines • Use Galaxy as workflow engine – large community support • Retools to address usability, security, and other limitations • Version Controlled Pipeline Templates • Input files, parameters, and workflow are sent to IRIDA-specific Galaxy for execution • Results and provenance information are copied from Galaxy 1. Input files sent to Galaxy 3. Results downloaded from Galaxy IRIDA UI/DB Galaxy Assembly Tools Variant Calling Tools … REST API Shared File System Worker Worker 2. Tools executed on Galaxy workers
  • 11. Solution 1c: Start the training NOW! • Canada’s National Microbiology Laboratory has hosted genomic workshops for partners and collaborators • IRIDA Project has dedicated funding for hosting workshops in 4Q of 2015 and 2016 • We would like to hear about other training initiatives and share experience and training material
  • 12. GAP 2: INFORMATION SHARING IS INEFFICIENT AND AD-HOC
  • 13. Many Players in surveillance and outbreak – ineffective information sharing Source: M. Taylor, BCCDC Provincial public health dept. National laboratory Local public health dept. Provincial laboratory Cases Physicians Frontline lab Information BioinformaticsandAnalyticalCapacities
  • 14. Many Systems used in Reporting Diseases – require data re-entry and re-coding National Ministry of Health Provincial public health dept. National laboratory Local public health dept. Provincial laboratory Cases Physicians Local laboratory Fax/Electronic Fax Phone/Fax Electronic/Paper Electronic/Fax/Phone Mailing of Samples/Fax/Eelctroni c Source: M. Taylor, BCCDC
  • 15. IRIDA is designed with these dilemma in mind • Solutions: – 2a: Localized Instance of federated databases – 2b: Permission Control – authentication /authorization for information sharing – 2c: User role-based display of information
  • 16. Solution 2a: Local/Cloud Instances and Data Federation • Data processing capacity pushed to data generating labs • Allow data sharing securely for enhanced analysis • Eventually cultivating a culture of openness of data sharing and collaborative development of tools 16
  • 17. Authorization Solution 2b: Security • Local authorization per instance. • Method-level authorization. • Object-level authorization. • Allow secure, fine grained and flexible information sharing
  • 18. Solution 2c: Role-based Dynamic Display driven by Ontology • Ontologies often lack a content management system (CMS) • An Interface Model Ontology (IFM) can define a CMS for an ontology
  • 19. IFM Interface View Permissions Detailed View Restricted View E.g. User role permissions control visibility and editing of content
  • 21. Solution 3a: Use Ontology • Ontology: a way to describe types of entities and relations between them • Why use ontology – Ontology is flexible and expandable – Lower levels of expressivity (e.g. controlled vocabulary, data dictionary) are heavy handed and show low level of compliance and adoption – Free text used as an alternative that are not computing friendly – Ontology and semantic web technologies may be a solution
  • 22. Many Domains of Knowledge are needed to describe an outbreak investigation Build On, Work With: OBI TypON NGSOnto NIAID-GSC-BRC core metadata MIxS Ontology NCBI Biosample etc TRANS – Pathogen Transmission EPO Exposure Ontology Infectious Disease Ontology CARD, ARO for AMR USDA Nutrient DB EFSA Comp. Food Consump. DB Example gaps to be filled: Expand food ontology; expand CARD AMR data with others.
  • 23. Lab Checklist/Ontology • Currently finishing a lab/genomics checklist and starting an epidemiology checklist • Metadata Domains: – Sample Collection – Sample Source – Environmental – Lab Analytics – Sequencing Process /QC – Sequencing Run /QC – Assembly Process / QC – Others overlapping with Epi: Demographic / Geographic / etc.
  • 24. GAP 4: GENOMIC DATA INTERPRETATION IS COMPLEX AND TECHNOLOGY IS EVOLVING
  • 25. Solution 4a: Use of QA/QC in IRIDA • Software Engineering – High quality software that meets regulatory guidelines – Open Source product to ensure “white box” testing – Ontology driven software development – Follow proper software development cycle • Data Quality – Built-in modules to check for input data quality – Warnings and Feedbacks during pipeline execution to laboratory technologists – Use of Ontology to check metadata (non-genomic) data quality • Analytic Tool Quality – Utilize validation datasets – Use of abstract pipeline description – with version control – Periodic analysis of exceptions and boundary cases to assess tool accuracy
  • 26. Solution 4b: Generation of validation datasets To Participate, Contact Rene Hendriksen rshe@food.dtu.dk Or Errol Strain Errol.Strain@fda.hhs.gov http://www.globalmicrobialidentifier.org/Workgroups#work-group-4
  • 27. Solution 4c: Exploratory tools can access certain data via REST API securely 27 http://pathogenomics.sfu.ca/islandviewer IslandViewer Dhillon and Laird et al. 2015, Nucleic Acids Research http://kiwi.cs.dal.ca/GenGIS Parks et al. 2013, PLoS One
  • 28. Availability • Jun 1 2015: IRIDA 1.0 beta Internal Release – Release to collaborators for installation and full test • Jul 1 2015: IRIDA 1.0 beta1 – Announce Beta release, download, documentation available on website – www.irida.ca • Aug 1 2015: IRIDA 1.0 beta2 – Cloud installer, with documentation – Additional pipelines as available – Visualization as available
  • 29. Acknowledgements Project Leaders Fiona Brinkman – SFU Will Hsiao – PHMRL Gary Van Domselaar – NML University of Lisbon Joᾶo Carriҫo National Microbiology Laboratory (NML) Franklin Bristow Aaron Petkau Thomas Matthews Josh Adam Adam Olson Tarah Lynch Shaun Tyler Philip Mabon Philip Au Celine Nadon Matthew Stuart-Edwards Morag Graham Chrystal Berry Lorelee Tschetter Aleisha Reimer Laboratory for Foodborne Zoonoses (LFZ) Eduardo Taboada Peter Kruczkiewicz Chad Laing Vic Gannon Matthew Whiteside Ross Duncan Steven Mutschall Simon Fraser University (SFU) Melanie Courtot Emma Griffiths Geoff Winsor Julie Shay Matthew Laird Bhav Dhillon Raymond Lo BC Public Health Microbiology & Reference Laboratory (PHMRL) and BC Centre for Disease Control (BCCDC) Judy Isaac-Renton Patrick Tang Natalie Prystajecky Jennifer Gardy Damion Dooley Linda Hoang Kim MacDonald Yin Chang Eleni Galanis Marsha Taylor Cletus D’Souza Ana Paccagnella University of Maryland Lynn Schriml Canadian Food Inspection Agency (CFIA) Burton Blais Catherine Carrillo Dominic Lambert Dalhousie University Rob Beiko Alex Keddy 29 McMaster University Andrew McArthur Daim Sardar European Nucleotide Archive Guy Cochrane Petra ten Hoopen Clara Amid European Food Safety Agency Leibana Criado Ernesto Vernazza Francesco Rizzi Valentina
  • 30. 30 30 IRIDA Annual General Meeting Winnipeg, April 8-9, 2015
  • 31. The IRIDA platform (Integrated Rapid Infectious Disease Analysis) An open source, standards compliant, high quality genomic epidemiology analysis platform to support real-time (food-borne) disease outbreak investigations Contacts: William.hsiao@bccdc.ca @wlhsiao 31 www.IRIDA.ca