Nuts & Bolts of Informatics Infrastructure for Clinical Next Generation Sequencing (NGS)

Size: px

Start display at page:

Download "Nuts & Bolts of Informatics Infrastructure for Clinical Next Generation Sequencing (NGS)"

Kimberly Richards
5 years ago
Views:

1 Nuts & Bolts of Informatics Infrastructure for Clinical Next Generation Sequencing (NGS) Somak Roy, MD Director Molecular Informatics & Genetics Services Molecular & Genomic Pathology Department of Pathology UPMC, Pittsburgh, PA

3 Disclosure of Relevant Financial Relationships USCAP requires that all planners (Education Committee) in a position to influence or control the content of CME disclose any relevant financial relationship WITH COMMERCIAL INTERESTS which they or their spouse/partner have, or have had, within the past 12 months, which relates to the content of this educational activity and creates a conflict of interest. Dr. Somak Roy declares he has NO conflict(s) of interest to disclose.

4 Outline Next generation sequencing (NGS) data Challenges in clinical NGS data management Informatics infrastructure requirements & implementation Q & A

5 Personalized Medicine Diagnostic Management A Prognostic Management B Therapeutic Disease monitoring Management C Pharmacogenomics

6 Massively Parallel Sequencing High-throughput sequencing technology Backbone of personalized medicine Widespread adoption by clinical laboratories

7 Sequencing Data Throughput Stephens ZD, et al. (2015) PLoS Biol 13(7): e

characteristics (5Vs) Limited sequencing

50 per kilobase Interrogates one region of

8 Conventional Sequencing Next Generation Sequencing Throughput Big data characteristics (5Vs) Limited sequencing capability Read length up to 1,000 bp Per-base 'raw' accuracy: % Time consuming $0.50 per kilobase Interrogates one region of genome Massively parallel sequencing Read length bp High sensitivity Quantitative Interrogates multiple regions Rapid and cost effective Volume Velocity Variety Veracity Value

9 Implementing NGS in my clinical lab. What do I need to know about informatics? Know you DATA

10 Intended Clinical Use Simon R & Roychowdhady S. Nat Rev Drug Discov May;12(5): doi: /nrd3979.

11 Sequence Data Generation ATTGCGCTATTATAGCTCTAGGGAAAAGCAGCG ATTGCGCTATTATAGCTCTAGGGAAAAGCAGCG Robison. Nat Biotechnol 2011;29:805-7 Rothberg et al. Nature. 2011;475:348-52

12 Sequence Data Analysis DNA sequencing reaction & raw data acquisition Terabytes Signal processing Platform specific Platform independent Basecalling (FASTQ /unaligned BAM) Demultiplexing (optional) Sequence alignment (BAM files) Gigabytes SNV callers Local realignment Large structural variation (fusion) detection CNV callers (gene amplifications and deletions) Indel caller List of genomic variants (VCF files) Megabytes / Kilobytes Roy S, et al. Arch Pathol Lab Med Sep;140(9):958-75

13 Variant Interpretation Li MM, et al. J Mol Diagn 2017, 19: 4-23

14 NGS Data Management Data Analytics Data Storage Data Transfer Data Integrity Data Security Li MM, et al. J Mol Diagn 2017, 19: 4-23

15 NGS Data Management Clinical Laboratory Datacenter / cloud service provider Analytics High-bandwidth network Storage Analytics & storage

16 NGS Data Management Clinical Laboratory Lower initial capital investment More control over resources Analytics Storage Limited scalability Compute resource lockdown Limited backup No disaster recovery protocol Cost and effort of hardware management

17 NGS Data Management Datacenter / cloud service provider Scalable infrastructure Redundant backup Fault tolerance Disaster recovery protocols Minimal hardware management Analytics & storage Data security Higher initial capital investment High-bandwidth network

Physician request Other Data Sources Ordering interface CPOE / others Transmission to EMR

tumor load assessment Microdissection and DNA extraction Variant knowledgebase management

Sequencing reaction NGS test workflow cycle Signal processing and base calling Variant

18 Physician request Other Data Sources Ordering interface CPOE / others Transmission to EMR Receipt of test order and sample/testing material QM/QC Signout in LIS Target marking and % tumor load assessment Microdissection and DNA extraction Variant knowledgebase management Report generation Variant review and interpretation by pathologist Library preparation & QC Sequencing reaction NGS test workflow cycle Signal processing and base calling Variant calling Adapter trimming, Alignment and mapping QC Roy S, et al. J Mol Diagn Jan;16(1):11-22.

19 NGS Data Storage What to store? (Data type) How long to store? (Data retention)

NGS Data Storage DNA sequencing reaction & raw data acquisition Terabytes Signal processing Platform specific Platform independent Basecalling (FASTQ /unaligned BAM) Demultiplexing (optional)

20 NGS Data Storage DNA sequencing reaction & raw data acquisition Terabytes Signal processing Platform specific Platform independent Basecalling (FASTQ /unaligned BAM) Demultiplexing (optional) Sequence alignment (BAM files) Gigabytes SNV callers Local realignment Large structural variation (fusion) detection CNV callers (gene amplifications and deletions) Indel caller List of genomic variants (VCF files) Megabytes / Kilobytes Roy S, et al. Arch Pathol Lab Med Sep;140(9):958-75

21 NGS Data Storage What to store? (Data type) How long to store? (Data retention) How much storage space is needed? (Projection)

22 NGS Data Storage College of American Pathologist (CAP) - at least 2 years Additional recommendations / guidelines are yet to come. Baker M. Next-generation sequencing: adjusting to data overload. Nature Methods 7, (2010)

23 NGS Data Storage What to store? (Data type) How long to store? (Data retention) How much storage space is needed? (Projection) How reliable is the storage? (Disaster recovery) How can data be recovered? (Data availability)

cloud OS OS OS OS OS OS OS OS OS OS OS OS Hypervisor Hypervisor Hypervisor Hypervisor

24 Data Analytics - Virtualization Non-virtualized environment App App App Operating System (OS) Server Virtualized environment OS OS OS Hypervisor Server Virtualized environment in a cloud OS OS OS OS OS OS OS OS OS OS OS OS Hypervisor Hypervisor Hypervisor Hypervisor Server Server Server Server Server Server Roy S, et al. Arch Pathol Lab Med Sep;140(9):958-75

25 Cloud Computing

26 Data Analytics Cloud Infrastructure Software as a Service (SaaS) (e.g., services, web appbased LIS/LIMS hosted in the cloud) Platform as a Service (PaaS) (e.g., Google App Engine, Heroku, AWS Elastic Beanstalk) Infrastructure as a Service (IaaS) (e.g., Amazon EC2, Microsoft Azure, IBM cloud services) Roy S, et al. Arch Pathol Lab Med Sep;140(9):958-75

27 Data Analytics - Containers VM-based virtualization Container-based virtualization OS OS OS Lib Lib Lib Container engine Hypervisor Hardware infrastructure Operating System Hardware infrastructure

28 Data Transfer and Integrity High-bandwidth (1-10Gbps) network infrastructure is required for NGS data transfer. Ideally, high-bandwidth network should be exclusive from core hospital network. Large volume data transfers should be done after hours. Only secure network protocols (e.g. HTTPS, SFTP) should be used. Checksums (MD5, SHA) for file integrity.

29 Data Security & Cloud Computing Public domain Institutional (Private) domain Community (federated) Cloud Public Cloud Institutional firewall Private Cloud Computing resource Hybrid Cloud Genomic data and PHI Firewall Roy S, et al. Arch Pathol Lab Med Sep;140(9):958-75

30 HIPAA Omnibus Final Rule (2013) Data Security & Cloud Computing Genetic information is identifiable patient information (PHI) Risks Strategies for software and physical safeguard. Cloud-stacking Geographic distribution of hosted data Removal of data after termination of services / contract. Business Associate Agreement (BAA) with cloud service provider. Roy S, et al. Arch Pathol Lab Med Sep;140(9):958-75

31 Take Home Points Informatics infrastructure is critical to support clinical NGS-based testing. Know your sequencing data to make informed decision about storage and analytic requirements. High-bandwidth network is necessary to support reliable and efficient data transfer. Data security in compliance with federal and local regulations. Leveraging cloud computing resources is often efficient and cost effective. Thorough review and execution of a BAA with a cloud vendor is important.

32 Important Information Regarding CME/SAMs The Online CME/Evaluations/SAMs claim process will only be available on the USCAP website until September 30, No claims can be processed after that date! After September 30, 2017 you will NOT be able to obtain any CME or SAMs credits for attending this meeting.

Case Study BONUS CHAPTER 2

Case Study BONUS CHAPTER 2 BONUS CHAPTER 2 Case Study ABC is a large accounting firm with customers in five countries across North America and Europe. Its North American headquarters is located in Miami, Florida, where it hosts