CDC s Advanced Molecular Detection (AMD) Sequence Data Analysis and Management
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1 CDC s Advanced Molecular Detection (AMD) Sequence Data Analysis and Management Scott Sammons Technology Officer Office of Advanced Molecular Detection National Center for Emerging and Zoonotic Infectious Diseases Office of Advanced Molecular Detection
2 Advanced Molecular Detection (AMD) 2011: Bioinformatics Blue Ribbon Panel 2014: Congress establishes AMD initiative 5-year, $30m-per-year modernization program Core goals: o Improving pathogen detection and characterization o Developing new diagnostics to meet public health needs o Supporting genomic and bioinformatics needs in the US public health system o Implementing enhanced, sustainable, integrated information systems o Developing tools for prediction, modeling and early recognition of emerging infectious threats 2016: AMD External Review
3 AMD s Focus NGS & bioinformatics: transforming pathogen detection and characterization At CDC In state and local health laboratories Other technologies: MALDI-TOF, optical mapping Infrastructure: storage, networking, high-performance computing, cloud Workforce development Collaboration
4 AMD: role with State Health Labs AMD Portal A centralized portal for the State Health Lab partners to gain access to CDC s infectious disease programs. In FY2016, AMD awarded more than $3 million to State Health Labs through the ELC for capacity building and workforce development in next generation sequencing, genomics, and bioinformatics.
5 APHL Implementation Guide and QA/QC Documentation blications/documents/id-ngs- Implementation-Guide pdf CDC Next Generation Sequencing Quality Team is working closely with APHL to provide QA/QC guideline documents to State Health Labs through APHL.org.
6 Sequencing and Analysis Workflows Sample Preparation Library Preparation Sufficient DNA quality and quantity Sufficient library quantity and proper size range Sequence Generation Sequence Analysis Instrument metrics, average read quality scores and metrics Minimum coverage of targeted regions Bioinformatics QC Result Reporting Updated mutation databases and interpretative guides Adapted from Gargis, Quality Assurance and Validation of Next-Generation Sequencing
7 Next Generation Sequence Analysis AMD sponsored/funded commercial products o o o o Others o o o o CLCbio Workbench Geneious LaserGene BioNumerics SeqScape, Sequencher, Freeware packages (windows): Mauve, MEGA, MEGAN, MrBayes, PHYLIP Open Source software: over 250 packages offered though our LINUX machines and high performance computing cluster In-house developed analysis pipelines
8 Analysis Workflow: Simple Metagenomics Example Trimmomatic: quality filtering and trimming RepeatMasker: removal of repetitive and low complexity sequences BLAST: remove hits to the human genome BLAST: keep hits to GenBank nr MEGAN: taxonomic classification based on blast hits
9 Analysis Workflow: wgmlst Example Quality filtering and trimming Spades: de novo assembly Reference Mapping: map raw reads against an allele database BLAST: contigs against an allele database Combine Results and create trees (minimum spanning)
10 Analysis Workflow: Newborn Screening Example Cutadapt: primer and adapter trimming BWA: Alignment of reads to a reference genome Variant Calling: GATK, FreeBayes, lofreq VCFintersect: report only variants in area of interest
11 Sequencing Instrument Data Management On-Boarded Sequencer (e.g., MiSeq) Instruments\Illumina-MiSeq-M70233\ Output Windows Share Average Miseq run generates 15G 20G of data. Most Miseqs ship with 500G hard drive. Storing runs on an external server is best option for long term and disaster recovery. SciComp Storage /scicomp/instruments/ Instrument Directories IonTorrent-S5-IT Illumina-MiniSeq-MN00367 Illumina-HiSeq-D00290 Illumina-NextSeq-NS PacBio-RSII-RS42135 Illumina-MiSeq-M70233 Run Directories Run 1 Run 2 Instrument directory access Read access managed for Linux & Windows users Write access from instrument Most instruments write directly to the shared storage Analysis pipelines read from shared storage minimize data duplication Run output for MiSeq (varies by instrument) Config/ Data/ Intensities/ BaseCalls/ Sample1 fastq.gz Sample2 fastq.gz RTA Logs/ Images/ Logs/ SampleSheet.csv
12 Group Data Management Group Working Area Read/write access to all group members for base directory Group Analysis Area Read/write access for Application-specific service accounts Read/write access for all group members Group Data Area Read/write access for data generators, e.g. Core Facility, OID Bioinformatics RFBS Results Read access to golden set of data Group Share Area Bi-directional share access for group collaboration SciComp Storage /scicomp/groups/ Group Directories CDC Organizational Hierarchy Shiny/ CLC/ Analysis/ NCBI-Submission/ BCFB/ OIDBIO/ in/ Data/ Share/ out/
13 Laboratory Workflow Data Management Clarity LIMS End to end sample and workflow tracking Stores metadata and complete sample history Instrument integration Reduces human error Built-In QC steps Allows for extensive customization (workflows/protocols + EPP) o Creating sample sheets for MiSeq o Kick off demultiplexing automatically o Starting a post-processing script
14 Clarity LIMS
15 Clarity LIMS Workflows/Protocols
16 Data Management: Food for Thought Evaluations/Pilots Epidemiologic and sequence data integration and analysis o Cloudera Hadoop influenza o Collaborative Advanced Analytics and Data Sharing (CAADS) HIV, tuberculosis Metadata and Sequence integration o CKAN, DSpace, Socrata
17 Bioinformatics Support Computing infrastructure: HPC, storage, virtual machines Central support team: bioinformaticians, sys admins, software developers Online forums: helpdesk, technical support, bioinformatics, programming, user groups GITLAB: code repository User groups: bioinformatics, R, sequencing, etc. Pipeline Development Tools: AGAVE, SciLuigi (eval) Workforce development: targeted to lab scientists, bioinformaticians, epidemiologists
18 AMD: Scientific Infrastructure Computing/ Virtualization Support for 250+ Linux applications Accommodates virtual LINUX boxes for researchers for development, testing, and deployment of scientist applications and pipelines High Performance Computing ~1800 core HPC cluster Support of multiple queues to accommodate different types of analysis Support for workflows directly coupled with scientific instrumentation Over 1 million jobs/month Storage 4 petabytes (1,000 terabytes) of networked attached storage (NAS) Supports all scientific instrument data, application data, and cluster data
19 The findings and conclusions in this presentation are those of the author and do not necessarily represent the official position of the Centers for Disease Control and Prevention. Use of trade names is for identification only and does not imply endorsement by the Centers for Disease Control and Prevention or by the U.S. Department of Health and Human Services. National Center for Emerging and Zoonotic Infectious Diseases Office of Advanced Molecular Detection
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