genometrakr: perspectives on linking internationally - canada and irida.ca

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Perspec)ves on Linking Interna)onally – Canada and IRIDA.ca

Fiona Brinkman Professor, Department of Biochemistry and Molecular Biology

Adjunct, School of Compu>ng Science, and Faculty of Health Sciences

Simon Fraser University Greater Vancouver, BC, Canada

[email protected] GenomeTrakr -‐ Sept 23 2015 @fionabrinkman

Canada’s Integrated Rapid Infec>ous Disease Analysis PlaTorm for Genomic Epidemiology

Interac(ng with,

complemen(ng others Interna(onal resources

Integrated Rapid Infec4ous Disease Analysis informa4cs pla;orm suppor)ng real-‐)me infec)ous disease outbreak inves)ga)ons

Goal

Rich genomic epi analysis Public health agencies

Rapid, open genomic

data release Academia/Public

Genomics, Epidemiology, Clinical, Lab Data


Goal

User-‐friendly, web-‐accessible

User access control (e.g. public health workers vs public)

Automated assembly pipelines, Data analysis and visualiza(on

Standards compliant, rich ontologies

Open source


Goal

NationalPublic Health Agency

Provincial Public Health Agency Academic/Public

Will Hsiao Fiona Brinkman

Gary Van Domselaar

www.IRIDA.ca

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Project Leaders Fiona Brinkman – SFU Will Hsiao – PHMRL Gary Van Domselaar – NML Simon Fraser University (SFU) Emma Griffiths Geoff Winsor Julie Shay Matthew Laird Bhav Dhillon McMaster University Andrew McArthur Daim Sardar European Food Safety Agency Leibana Criado Ernesto Vernazza Francesco Rizzi Valentina

[email protected]

National Microbiology Laboratory (NML) Franklin Bristow Aaron Petkau Thomas Matthews Josh Adam Adam Olsen Tara Lynch Shaun Tyler Philip Mabon Philip Au Celine Nadon Matthew Stuart-Edwards Morag Graham Chrystal Berry Lorelee Tschetter Eduardo Toboada Peter Kruczkiewicz Chad Laing Vic Gannon Matthew Whiteside Ross Duncan Steven Mutschall University of Lisbon Joᾶo Carriҫo European Bioinformatics Institute Melanie Courtot Helen Parkinson

BC Public Health Microbiology & Reference Laboratory (PHMRL) and BC Centre for Disease Control (BCCDC) Judy Isaac-Renton Patrick Tang Natalie Prystajecky Jennifer Gardy Linda Hoang Kim MacDonald Yin Chang Eleni Galanis Marsha Taylor Damion Dooley Jennifer Law University of Maryland Lynn Schriml Canadian Food Inspection Agency (CFIA) Adam Koziol Burton Blais Catherine Carrillo Dalhousie University Rob Beiko Alex Keddy

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IRIDA Design: Carefully designed and engineered soHware plaIorm is just the star)ng point…

User Interface

Security

File system

Metadata Storage Applica)on

logic

REST API Workflow Execu)on Manager

Con)nuous Integra)on Documenta)on

Federated database model

Addressing ontology gaps Build On, Work With: OBI TypON NGSOnto NIAID-‐GSC-‐BRC core metadata MIxS Ontology NCBI Biosample etc TRANS – Pathogen Transmission EPO Exposure Ontology Infec)ous Disease Ontology CARD, ARO for AMR USDA Nutrient DB EFSA Comp. Food Consump. DB Example gaps to fill: Improve Food ontologies, AMR data

Ontology: Describes types of en((es and rela(ons between them

Analy)cal Tool

Quality Control Module

Quality Metrics

Quality Control

IRIDA’S QA/QC Model

IRIDA Workflows: Portable and Transparent Pipelines

Use Galaxy as workflow engine

Version Controlled Pipeline

Templates

1. Input files,

parameters 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

Example data analysis, visualiza)on tools IslandViewer/GenomeD3Plot – more flexible GI/VF/AMR visualiza)on

Dhillon BK et al 2015 Nucl Acids Res PMID: 25916842 Laird MR et al 2015 Bioinforma(cs PMID: 26093150 www.pathogenomics.sfu.ca/islandviewer/

github.com/brinkmanlab/GenomeD3Plot/

“SNVPhyl” SNV analysis Integra)ng genomics, geographic data (led by NML, Rob Beiko, Dalhousie U)

http://kiwi.cs.dal.ca/GenGIS

SNVPhyl Software Demo by Aaron Petkau and IRIDA poster by Emma Griffiths at #ASMNGS meeting

Example data analysis, visualization tools

Challenges

… for IRIDA … for interna)onal linkages

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Challenges


Biggest challenge is NOT bioinforma(cs/soPware development

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Challenges


Biggest challenge is NOT bioinforma(cs/soPware development

It’s sharing

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Canada’s Public Health System Challenges

Provincial public health dept.

National laboratory

Local public health dept.

Provincial laboratory

Cases

Physicians Frontline lab

Informa)on

Bioinforma)cs and Analy)cal

Capaci)es

Info lost as aggregate data from Frontline lab to national PH labs

$ Disease Reporting

Informa)on Sharing is Highly Complex

•  Variety of agreements, legisla)on

•  Lack of standards (metadata, legal requirements)

•  Fears of data release during ongoing inves)ga)ons, and IP concerns make provinces “risk averse”

Impact

•  Impacts data sharing na)onally, interna)onally

•  Also: Lack of rich example data impacts ontology, data standards development (ability for computers to share)

Must communicate to countries: Get data sharing arranged early – both na(onally and interna(onally

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Interna)onal data sharing

-‐  Get data sharing arranged early -‐  Ensure alloca(on of adequate resources to set it up

-‐  Share bioinforma(cs resources, code, parameters -‐  Share data examples

-‐  Start simple: Agree on minimal genome metadata for rapid release

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Interna)onal data sharing Pt. 2 -‐ Develop harmonized metadata for further data release

-‐ Interoperable systems

-‐ Current and well-‐maintained repositories

-‐ Valida4on datasets for pipeline calibra)on

-‐ User access control

Open access à Opens opportuni)es, discoveries

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A new hope… MLISA (Multilateral Information Sharing Agreement)

•  Canadian multi-jurisdictional legal agreement •  Establishes standards re sharing, usage, disclosure and

protection of PH info for infectious diseases and PH events •  Technical annexes (for example for WGS) can be developed to

clarify specifically data to be exchanged

PulseNet as a model for sharing (in part)

Can USA–Canada sharing be developed as a model?

Flight paths across North America. Outbreaks follow flight paths more closely than simple geographic distance.

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IRIDA’s Role in International Data Sharing

1. Application ontology for genomic epidemiology

2. Metadata standardization

3.  Interoperability

4. Sensitive field sharing secured via authorization

5. Privacy protection and data security

6. Compatible with International Health Regulations (2005)

7. Aims to support federated design, plus open data sharing

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Sharing – via computers, people Its all about communica(on Computers – ontologies, data standards are key Humans – gemng them together is key…

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Sharing – via computers, people Its all about communica(on Computers – ontologies, data standards are key Humans – gemng them together is key…

Brinkman Lab Kayaking Trip

Addi)onal key trainee funding and compu)ng infrastructure:

We’re hiring!