P R O T E C T I N G , M A I N T A I N I N G A N D I M P R O V I N G T H E H E A L T H O F A L L M I N N E S O T A N S

Dave Boxrud

2019 APHL Annual Meeting

Development of Bioinformatics Infrastructure in Minnesota

I am not a bioinformaticist

26/11/2019

In 2016

• Limited bioinformatics capacity at MDH

• No bioinformatics infrastructure

• Little bioinformatics expertise

• Hard to communicate with IT (speaking different languages)

• Linux not supported by MDH

• Did have knowledge of Minnesota Supercomputing Institute, did not know how to use it, did not know who to contact, even if we had access we had nobody that was trained in bioinformatics

36/11/2019

MDH Vision for Bioinformatics

• NGS is the future, the future is here

• Accumulating NGS data for multiple organisms, need to use the data

• Bionumerics for foodborne agents coming, won’t fulfill all our needs

• Flexible

• Sustainable

• Cost effective

• Accessible

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Three Approaches to Bioinformatics Infrastructure

NY-Wadsworth CenterCDC CO-PHL

Possible Solutions

Build own infrastructure Cloud Computing Use Existing System

APHL Bioinformatics Fellow to the Rescue

• Sean Wang start APHL Bioinformatics Fellowship August 2016

• PhD-U of MN

• Experience with MSI

• Able to be an IT/bioinformatics/PH translator

Minnesota Supercomputing Institute (MSI)

• Mission-To provide advanced research computing infrastructure and expertise to the U. of MN research and scholarly community and the State of Minnesota in order to advance and accelerate research…

• HPC, Interactive HPC, data storage, specialized hardware

• Can utilize open source software (pipelines)

• Consulting and expertise

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• No Linux, Mac OS systems were supported in the state• Cloud computing not viable option in MN at the time• MSI is partly funded by the State of Minnesota• MSI-provide services at cost• MSI-computing infrastructure, HPC consulting• Pre-installed a comprehensive list of bioinformatics tools

MSI-Most Appealing Option

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Hurdles during Bioinformatics infrastructure building:• Contract• IT regulation• Workforce

Building Bioinformatics Infrastructure Challenges

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• Contract renew• No root access -> Stratus “cloud computing”• Had to use VPN every time -> “white list” MDH IP cluster

On-going Issues

Cloud Computing for State Public Health Labs

• Advantages• No capital cost

• No maintenance cost

• Expand/contract resources as needed

• Portable

• Root access

• Disadvantages

• Variable ongoing cost

• Data security

• Still requires some expertise to setup

• Lack of support

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Regional Bioinformatics Support

ND

SD NE

IA

MO

AROK

KS

Regional Bioinformatician

Minnesota Cloud Platform for Bioinformatics

▪ Pre-configured virtual machines with common tools installed▪ Documentation with sample commands for running tools▪ Ongoing support provided by MSI personnel

WWW.HEALTH.MN.GOV

Dave.boxrud@state.mn.us651-201-5257

Thank you.

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The bioinformatics infrastructure and NGS data flow of MDH

5 Illumina Miseq

Local server(38 TB)

Minnesota Super

computing Institute

(MSI)

AIMS

CLC Genomic workbenc

h

GeneiousPro

Data flow1 TB = 1000 GB1 GB = 1000 MB1MB = 1000 kb1 MB = 1000 B

Linux (Cent OS) Web-based Galaxy 15 TB primary storage HPC (High performance

Computer) Access Dedicated node access Consulting

Illumina Base space

FDACDC

NY-PHL

Strep pneumo pipelineInfluenza pipeline

Data Sharing

Lord of Rings Sequencers

Stratus

Stratus cloud computing• 80vCPU• 10TB of ephemeral

storage• 160GB RAM• Root access• Amazon S3 access

MinION

Bionumerics

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Access approach

MSI white-listed Minnesota Department of Health IP address

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Data transfer

• Between MDH server and MSI rely on MNET (Minnesota’s Network for Enterprise Telecommunications)

• Sequencing files can also directly downloaded from Basespace to MSI HP-storage

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Current PHL IT setting cannot fulfill bioinformatics computing needs

An interdisciplinary study which combine Statistics, Computer Science and Biology

“Big data” of Genomics Translate meaningless millions of short sequences into meaningful and

actionable biological results Population level infectious disease surveillance will require massive

computing power to process the large amount of biological data The “soul” of bioinformatics is open-source computing platform

Linux system*Supercomputer “Mesabi” at UMN

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Three Approaches to Bioinformatics Infrastructure

NY-Wadsworth CenterCDC

MN-PHL MA-PHLVA-PHL IA-PHL

CO-PHL

Pro: • Configurable

computing resource;• Ready-to-use system• Pre-installed software

and dependencies• Dedicated consulting

Con: • No root access• IT security• Data transfer• University-

government contract

Pro: • Configurable

computing resource;• Portability• Development

environments

Con: • IT security;• Data transfer• Data ownership

Possible Solutions

Build own system Cloud Computing Use University System

ChallengesMNIT did not support LinuxMNIT did not support use of open source softwareCostExpertise