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Research Infrastructures
H3ABioNet case study
Prof Nicola Mulder
H3ABioNet PI
Head of Computational Biology
University of Cape Town
Outline
• Introduction to H3Africa and H3ABioNet
• H3Africa data
• Data sharing policy
• Building infrastructure
• Computing infrastructure
• Human capacity
• Data harmonization & curation
• Facilitating data access
H3Africa: Human Heredity & Health in
Africa
• H3frica Vision: “To facilitate an Africa-based
contemporary research approach to the study of
genomics and environmental determinants of
common diseases with the goal of improving the
health of African populations”
• Funding: NIH, Wellcome Trust/AESA
The H3Africa Consortium
14
Collaborative
Centers
13 Research
Projects
3 Pilot
Biorepositories
8 Ethics Grants
The H3Africa
Consortium
Bioinformatics
Network
4 Global Health
Bioinformatics
Training Programs
H3ABioNet
H3ABioNet Informatics network
• H3ABioNet is a Pan African Informatics Network, to provide
bioinformatics infrastructure and support for the H3Africa
consortium
• Round 1: 34 partners in 14 African countries
• Round 2: 28 partners in 17 countries
• Activities:
• Infrastructure
• User support
• Research
• Training
www.h3abionet.org
H3Africa data (Phase I)
• Phenotype data (associated with genotype data)
– Demographic information
– Anthropometric data
– Disease and health related phenotype data
• Genetic Variation data human and pathogen
– Sequence data (whole genome, exome, targeted)
• Genotyping chip array data
– ~55,000 samples to be run on an H3Africa African custom chip
• Microbiome sequence data
– Patient/sample phenotypes
– Non-human 16S rRNA sequence data for microbiome
– Non-human full genome sequence data for microbiome
– Possible human sequence contamination
• Biospecimens to be deposited at the H3Africa biorepositories
Image credits: National Human Genome Research Institute (https://www.genome.gov/imagegallery/)
Why share data?
• New era of open science
• Enables reproducible science
• Increases visibility and credibility of data generators
• Additional publications and citations
• New research questions can be asked of data
• New discoveries made of relevance to participants
• Increasing sample size
• Increases value of the data
• Funder requirement
Limits to sharing human genetic data
• Data can be stored indefinitely, biobank
specimens can be stored for up to 20 years –
secondary use -rapid innovation with ‘omics
technologies
• Blood sample collection and visits to clinics
associated with disease and treatment – even if a
healthy control
• Ethics consent: H3Africa- some projects have
broad consent, some used tiered consent or
specific consent
• History of vulnerable populations, low education
levels and exploitation
• Anonymized, but risk of identification
Ethical
considerations
Informed
consent
Participant
identification
Stigmatisation
Benefit
sharing
Human genetic data privacy
• Age & Sex
• Country of birth
• Current residence
• Native language
• Ethno-linguistic/tribal affiliation
• Country of birth of father and mother
• Native language of father and mother
• Ethno-linguistic/tribal affiliation of
mother and father
• Height
• Weight
• Current medications
• Smoking history
• Alcohol history
Image credits: National Human Genome Research Institute (https://www.genome.gov/imagegallery/)
• Combination of phenotype and genetic data makes it possible to
identify different populations and individuals – restricted access
H3Africa Data Sharing Access and
Release Policy
• Balance between ensuring that adequate safeguards to protect
participants while not being a barrier for scientists to advance
research
• Maximizing the availability of research data, in a timely and
responsible manner
• Protecting the rights and privacy of human subjects who
participated in research studies
• Recognizing the scientific contribution of researchers who
generated the data
• Considering the nature and ethics of the research proposed in
establishing the timely release of data, and mechanisms of data
sharing
• Promoting deposition of genomic data in existing community data
repositories whenever possible
H3Africa DSAR policy
• For genomic and phenotype data:
• Submit to H3Africa archive
• 9 months to submit to public repository
• 12 month publication embargo
• In EGA access controlled by DBAC
2 months
Research
site- QC
genomic &
phenotypic
data
9 months
H3ABioNet-
Genomic &
phenotypic
data stored
12 months
EGA- Genomic &
phenotypic data
available through
DBAC with publication
embargo
Long term
EGA- Genomic & phenotypic data
available through DBAC without
publication embargo
Research
site -Data
generation
23 months
Data and Biospecimen Access Committee
• Review and approve requests for data and/or biospecimens
• Biospecimens:
• first 3 years only access outside H3Africa for those collaborating in
Africa
• Use info on availability in biobanks
• Data generated must be submitted to EGA
• Scientific review/funding available
• Data
• DBAC will ensure requestor has expertise and resources
• Scientific review
• Evaluation criteria
• Scientific merit
• Institutional capacity for the research
• Potential for publication or translation, e.g. new therapies
Data access agreement
• H3Africa not liable for use of data
• Only use data for agreed purpose
• Maintain data confidentiality
• Make sure data is secure
• Acknowledge source of data
• Submit annual reports
• Project put onto website
• Access is granted for 1 year
What is required for sharing data?
• Consent from participants –varying consent within a study
is difficult
• Robust data sharing model with implementation strategy
for data access, transfer, etc
• Access agreements and MoUs
• Infrastructure for
• Data transfer
• Data storage & compute
• Training
• Data curation and harmonization
Infrastructure development & support
• Node server purchases
• Sys Admin “How to” documents
• Access to HPC, Cloud (Docker
containers)
• Internet connectivity
measurement -NetMap
• Data transfer –Globus online,
testing vs Aspera
• Data storage
• Training in IT, data management
and general bioinformatics use
H3ABioNet combined equipment: 512
cores, 2384 GB RAM, 120TB storage
Building human capacity for genomics
data management
• Need to train
• Bioinformaticians
• Data scientists
• Bioinformatics users
• Medical professionals
Specialised courses,
shadow teams,
internships
ISCB
EMBL-EBI
training team
Training Approaches
Face to face Workshops
Train-the-Trainer
Internships
Live Online Training
Hackathons/Data Jamborees
Access to training materials
Harmonizing H3Africa data
Harmonizing H3Africa data
Mapping biobank data to
OMIABIS ontology
Mapping CRFs to ontologies,
e.g. phenotype or disease
ontology
Mapping genomics
data to
Experimental
Factor ontology
PHWG has developed
set of core phenotypes,
standard CRF
Mapping ethics
consent info to Data
Use ontology
Harmonizing H3Africa data
Mapping biobank data to
OMIABIS ontology
Mapping CRFs to ontologies,
e.g. phenotype or disease
ontology
Mapping genomics
data to
Experimental
Factor ontology
PHWG has developed
set of core phenotypes,
standard CRF
Mapping ethics
consent info to Data
Use ontology
Biorepositories
Archive & EGA
Catalogue
Making data FAIR
• Findable, Accessible, Interoperable, and Re-usable
https://www.force11.org/group/fairgroup/fairprinciples
• To be Findable: identifier, metadata, indexed
• To be Accessible: find by identifier, clear rules for
access and authentication
• To be Interoperable: standardized and cross-
referenced
• To be Reusable: licensed, metadata with provenance,
standards
Making data FAIR
• Findable, Accessible, Interoperable, and Re-usable
https://www.force11.org/group/fairgroup/fairprinciples
• To be Findable: identifier, metadata, indexed
• To be Accessible: find by identifier, clear rules for
access and authentication
• To be Interoperable: standardized and cross-
referenced
• To be Reusable: licensed, metadata with provenance,
standards
H3Africa Data Archive
• Assist H3Africa projects as data coordination center:
TransferValidate
Store
Submit
to EGA
Obtain EGA accessions
for publications
0.5 petabytes storage size including offsite
replication
Local EGA feasibility?
Data and biospecimen catalogue
Beacons
…a simple public web service … designed
merely to accept a query of the form "Do you
have any genomes with an 'A' at position
100,735 on chromosome 3" (or similar data)
and responds with one of "Yes" or "No."
genomicsandhealth.org
• Advantages
• Locally hosted
• Minimal information (yes/no for a
given allele)
• Protection against “scraping”
https://goo.gl/Bkd0dx
Summary
• H3Africa is largest collection of human biomedical
data in Africa to date
• Human data is sensitive and needs to be shared
while protecting participants and researchers
• Need to build infrastructure for sharing:
• harmonized/curated metadata
• storage and transfer facilities
• human capacity -skills
• Need to provide access tools –web interface, public
repositories, database
• Trying to promote Open science –user groups,
sessions
Acknowledgements
The H3ABioNet Consortium
Funding: NIH
Common Fund,
NGHRI grant:
U41HG006941,
U24HG006941
H3ABioNet team at CBIO:
• Sumir Panji
• Gerrit Botha
• Ayton Meintjes
• Suresh Maslamoney
• Vicky Nembaware
• Ziyaad Parker
• Kim Gurwitz
• Mamana Mbiyavanga
• Katherine Johnston
Slides: Sumir
Panji, Michelle
Skelton

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Research Infrastructures H3ABioNet case study/Nicola Mulder

  • 1. Research Infrastructures H3ABioNet case study Prof Nicola Mulder H3ABioNet PI Head of Computational Biology University of Cape Town
  • 2. Outline • Introduction to H3Africa and H3ABioNet • H3Africa data • Data sharing policy • Building infrastructure • Computing infrastructure • Human capacity • Data harmonization & curation • Facilitating data access
  • 3. H3Africa: Human Heredity & Health in Africa • H3frica Vision: “To facilitate an Africa-based contemporary research approach to the study of genomics and environmental determinants of common diseases with the goal of improving the health of African populations” • Funding: NIH, Wellcome Trust/AESA
  • 4. The H3Africa Consortium 14 Collaborative Centers 13 Research Projects 3 Pilot Biorepositories 8 Ethics Grants The H3Africa Consortium Bioinformatics Network 4 Global Health Bioinformatics Training Programs H3ABioNet
  • 5. H3ABioNet Informatics network • H3ABioNet is a Pan African Informatics Network, to provide bioinformatics infrastructure and support for the H3Africa consortium • Round 1: 34 partners in 14 African countries • Round 2: 28 partners in 17 countries • Activities: • Infrastructure • User support • Research • Training www.h3abionet.org
  • 6. H3Africa data (Phase I) • Phenotype data (associated with genotype data) – Demographic information – Anthropometric data – Disease and health related phenotype data • Genetic Variation data human and pathogen – Sequence data (whole genome, exome, targeted) • Genotyping chip array data – ~55,000 samples to be run on an H3Africa African custom chip • Microbiome sequence data – Patient/sample phenotypes – Non-human 16S rRNA sequence data for microbiome – Non-human full genome sequence data for microbiome – Possible human sequence contamination • Biospecimens to be deposited at the H3Africa biorepositories Image credits: National Human Genome Research Institute (https://www.genome.gov/imagegallery/)
  • 7. Why share data? • New era of open science • Enables reproducible science • Increases visibility and credibility of data generators • Additional publications and citations • New research questions can be asked of data • New discoveries made of relevance to participants • Increasing sample size • Increases value of the data • Funder requirement
  • 8. Limits to sharing human genetic data • Data can be stored indefinitely, biobank specimens can be stored for up to 20 years – secondary use -rapid innovation with ‘omics technologies • Blood sample collection and visits to clinics associated with disease and treatment – even if a healthy control • Ethics consent: H3Africa- some projects have broad consent, some used tiered consent or specific consent • History of vulnerable populations, low education levels and exploitation • Anonymized, but risk of identification Ethical considerations Informed consent Participant identification Stigmatisation Benefit sharing
  • 9. Human genetic data privacy • Age & Sex • Country of birth • Current residence • Native language • Ethno-linguistic/tribal affiliation • Country of birth of father and mother • Native language of father and mother • Ethno-linguistic/tribal affiliation of mother and father • Height • Weight • Current medications • Smoking history • Alcohol history Image credits: National Human Genome Research Institute (https://www.genome.gov/imagegallery/) • Combination of phenotype and genetic data makes it possible to identify different populations and individuals – restricted access
  • 10. H3Africa Data Sharing Access and Release Policy • Balance between ensuring that adequate safeguards to protect participants while not being a barrier for scientists to advance research • Maximizing the availability of research data, in a timely and responsible manner • Protecting the rights and privacy of human subjects who participated in research studies • Recognizing the scientific contribution of researchers who generated the data • Considering the nature and ethics of the research proposed in establishing the timely release of data, and mechanisms of data sharing • Promoting deposition of genomic data in existing community data repositories whenever possible
  • 11. H3Africa DSAR policy • For genomic and phenotype data: • Submit to H3Africa archive • 9 months to submit to public repository • 12 month publication embargo • In EGA access controlled by DBAC 2 months Research site- QC genomic & phenotypic data 9 months H3ABioNet- Genomic & phenotypic data stored 12 months EGA- Genomic & phenotypic data available through DBAC with publication embargo Long term EGA- Genomic & phenotypic data available through DBAC without publication embargo Research site -Data generation 23 months
  • 12. Data and Biospecimen Access Committee • Review and approve requests for data and/or biospecimens • Biospecimens: • first 3 years only access outside H3Africa for those collaborating in Africa • Use info on availability in biobanks • Data generated must be submitted to EGA • Scientific review/funding available • Data • DBAC will ensure requestor has expertise and resources • Scientific review • Evaluation criteria • Scientific merit • Institutional capacity for the research • Potential for publication or translation, e.g. new therapies
  • 13. Data access agreement • H3Africa not liable for use of data • Only use data for agreed purpose • Maintain data confidentiality • Make sure data is secure • Acknowledge source of data • Submit annual reports • Project put onto website • Access is granted for 1 year
  • 14. What is required for sharing data? • Consent from participants –varying consent within a study is difficult • Robust data sharing model with implementation strategy for data access, transfer, etc • Access agreements and MoUs • Infrastructure for • Data transfer • Data storage & compute • Training • Data curation and harmonization
  • 15. Infrastructure development & support • Node server purchases • Sys Admin “How to” documents • Access to HPC, Cloud (Docker containers) • Internet connectivity measurement -NetMap • Data transfer –Globus online, testing vs Aspera • Data storage • Training in IT, data management and general bioinformatics use H3ABioNet combined equipment: 512 cores, 2384 GB RAM, 120TB storage
  • 16. Building human capacity for genomics data management • Need to train • Bioinformaticians • Data scientists • Bioinformatics users • Medical professionals Specialised courses, shadow teams, internships ISCB EMBL-EBI training team
  • 17. Training Approaches Face to face Workshops Train-the-Trainer Internships Live Online Training Hackathons/Data Jamborees Access to training materials
  • 19. Harmonizing H3Africa data Mapping biobank data to OMIABIS ontology Mapping CRFs to ontologies, e.g. phenotype or disease ontology Mapping genomics data to Experimental Factor ontology PHWG has developed set of core phenotypes, standard CRF Mapping ethics consent info to Data Use ontology
  • 20. Harmonizing H3Africa data Mapping biobank data to OMIABIS ontology Mapping CRFs to ontologies, e.g. phenotype or disease ontology Mapping genomics data to Experimental Factor ontology PHWG has developed set of core phenotypes, standard CRF Mapping ethics consent info to Data Use ontology Biorepositories Archive & EGA Catalogue
  • 21. Making data FAIR • Findable, Accessible, Interoperable, and Re-usable https://www.force11.org/group/fairgroup/fairprinciples • To be Findable: identifier, metadata, indexed • To be Accessible: find by identifier, clear rules for access and authentication • To be Interoperable: standardized and cross- referenced • To be Reusable: licensed, metadata with provenance, standards
  • 22. Making data FAIR • Findable, Accessible, Interoperable, and Re-usable https://www.force11.org/group/fairgroup/fairprinciples • To be Findable: identifier, metadata, indexed • To be Accessible: find by identifier, clear rules for access and authentication • To be Interoperable: standardized and cross- referenced • To be Reusable: licensed, metadata with provenance, standards
  • 23. H3Africa Data Archive • Assist H3Africa projects as data coordination center: TransferValidate Store Submit to EGA Obtain EGA accessions for publications 0.5 petabytes storage size including offsite replication Local EGA feasibility?
  • 24. Data and biospecimen catalogue
  • 25. Beacons …a simple public web service … designed merely to accept a query of the form "Do you have any genomes with an 'A' at position 100,735 on chromosome 3" (or similar data) and responds with one of "Yes" or "No." genomicsandhealth.org • Advantages • Locally hosted • Minimal information (yes/no for a given allele) • Protection against “scraping” https://goo.gl/Bkd0dx
  • 26. Summary • H3Africa is largest collection of human biomedical data in Africa to date • Human data is sensitive and needs to be shared while protecting participants and researchers • Need to build infrastructure for sharing: • harmonized/curated metadata • storage and transfer facilities • human capacity -skills • Need to provide access tools –web interface, public repositories, database • Trying to promote Open science –user groups, sessions
  • 27. Acknowledgements The H3ABioNet Consortium Funding: NIH Common Fund, NGHRI grant: U41HG006941, U24HG006941 H3ABioNet team at CBIO: • Sumir Panji • Gerrit Botha • Ayton Meintjes • Suresh Maslamoney • Vicky Nembaware • Ziyaad Parker • Kim Gurwitz • Mamana Mbiyavanga • Katherine Johnston Slides: Sumir Panji, Michelle Skelton