BioData World Basel 2018
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Introduction to Jackson Labs, JMCRS, Clinical Services and Scientific Services at the Jackson Labs. Differences between long and short read sequencing. FAIR Data Action Plan. Metadata needs. Data Commons and the need to capture sample specific gene models discovered.
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BioData World Basel 2018
- 1. NGS: How what we are measuring impacts data models and implications for data commons Anne Deslattes Mays, PhD Principal Computational Scientist
- 2. How to handle the disruption of new measurement technologies in our data ecosystem?
- 3. What does this mean for data science?
- 4. How do we become better data stewards?
- 5. 11/29/2018 BioDataWorld Congress - Basel This presentation was prepared by Anne Deslattes Mays, PhD in her personal capacity. The opinions expressed in this presentation are the author's own and not necessarily the views and opinions of the Jackson Laboratory Disclaimer
- 6. Introduction to the Jackson Laboratory What is Next Generation Sequencing Data used for today? How do we handle disruptions new measurement technologies bring? What is Proper Data Stewardship for Data Science? What does this mean for Data Commons ? How does we capture the context and precision of measurements? 11/29/2018 BioDataWorld Congress - Basel Talk Overview 1 2 3 4 5 6
- 7. 11/29/2018 BioDataWorld Congress - Basel The Jackson Laboratory (https://www.jax.org/) To discover precise genomic solutions for disease and empower the global biomedical community in the shared quest to improve human health.
- 8. 11/29/2018 BioDataWorld Congress - Basel The Jackson Laboratory (https://www.jax.org/)
- 9. 11/29/2018 BioDataWorld Congress - Basel Recent News
- 10. JAX® Mice, Clinical and Research Services 11/29/2018 BioDataWorld Congress - Basel > 10,000 mice strains supporting biomedical research > 80% research publications citing mice strains use JAX® Mice > 30,000 peer-reviewed publications cite use of JAX® Mice > 22,000 genetically diverse background strains cryopreserved > 2,500 strains successfully cryorecovered by JAX each year > 75 new models CRISPR created on different genetic backgrounds Every month hundreds publications reference JAX® Mice strains 1 2 3 4 5 6 7
- 11. JAX Clinical Genomics Laboratory (CGL) Offerings: SampleTypesValidated forTesting FFPE: Formalin Fixed Paraffin Embedded tissue (SOLID TUMORS) Cell Free DNA Whole Blood Buccal Swab Saliva CancerInheritedDisorders Honey Reddi, PhD, FACMG Clinical Lab Director
- 12. Who DoWe Serve? Clinicians Pharma + Academia Biotech + JAX PIs - CLIA validated tests - CLIA validated tests - Research Assays - Research Assays - Custom Assay Development
- 13. Assays for Confirmation of variants Types of variants Confirmatory Technology Nucleic Acid Research or Orthogonal technology Variant(s) Identified DNA ddPCR ($570/sample) SNPs, CNVs Sanger ($400/sample) SNPs, InDels RNA RT-PCR ($342/sample) Fusions 48-60 samples/run, TAT of ~6 days if primer/probes available in-house
- 14. Research Assays: PDX A suite of assays for mutational and expression analysis of PDX tissue, includes PDX filtering
- 15. Clinical Knowledge Base 11/29/2018 BioDataWorld Congress - Basel
- 16. Scientific Services at JAX 11/29/2018 BioDataWorld Congress - Basel JAX-GM Cellular Engineering Microbial Genomics Single Cell Biology Genome Technologies Center for Biometric Analysis PDX Research and Development Microscopy Services Flow Cytometry Mass Spectrometry and Protein Chemistry Monoclonal Antibody Services 1 2 3 4 5 6 7 8 9 10
- 17. Scientific Services at JAX 11/29/2018 BioDataWorld Congress - Basel JAX-GM Cellular Engineering ✔️ Microbial Genomics Single Cell Biology Genome Technologies Center for Biometric Analysis PDX Research and Development Microscopy Services Flow Cytometry Mass Spectrometry and Protein Chemistry Monoclonal Antibody Services 1 2 3 4 5 6 7 8 9 10 ✔️- Using NGSTechnologies
- 18. Gordon Bell Prize Super Computing 2018 11/29/2018 BioDataWorld Congress - Basel
- 19. Gordon Bell Prize Super Computing 2018 11/29/2018 BioDataWorld Congress - Basel 750,000 human genome types, associated with more than a billion medical records over a 20-year period.
- 20. 11/29/2018 BioDataWorld Congress - Basel
- 21. 11/29/2018 BioDataWorld Congress - Basel
- 22. 11/29/2018 BioDataWorld Congress - Basel
- 23. 11/29/2018 BioDataWorld Congress - Basel
- 24. 11/29/2018 BioDataWorld Congress - Basel Oxford Nanopore Offerings
- 25. 11/29/2018 BioDataWorld Congress - Basel Workman, Rachael E., et al. "Nanopore native RNA sequencing of a human poly (A) transcriptome." bioRxiv (2018): 459529. Human poly (A) transcriptome
- 26. 11/29/2018 BioDataWorld Congress - Basel Workman, Rachael E., et al. "Nanopore native RNA sequencing of a human poly (A) transcriptome." bioRxiv (2018): 459529. Human poly (A) transcriptome
- 27. 11/29/2018 BioDataWorld Congress - Basel https://blog.genohub.com/2017/06/16/pacbio-vs- oxford-nanopore-sequencing/ PacBio vs Oxford Nanopore Sequencing
- 28. 11/29/2018 BioDataWorld Congress - Basel PacBio Concensus Accuracy > 99% raw PacBio reads also differ in error types (more indels than mismatches) and have a much higher abundance (∼13–15%,Table 1), though they are spread randomly across the reads (25,26).This randomness enables highly accurate consensuses (>99%) to be build up rapidly by sequencing multiple times the same molecule (CCS reads) Simon Ardui,AdamAmeur, Joris RVermeesch, Matthew S Hestand; Single molecule real-time (SMRT) sequencing comes of age: applications and utilities for medical diagnostics, NucleicAcids Research,Volume 46, Issue 5, 16 March 2018, Pages 2159–2168, https://doi.org/10.1093/nar/gky066
- 29. 11/29/2018 BioDataWorld Congress - Basel All measurements taken on biological samples are made within the context of instrument limitations, procedures followed in preparing samples for measurement and the condition and the context of the samples being measured. Raw result data, quality data, metadata and procedures used to transform measurement data from the instrument and/or the experimental procedures are best captured at the time of experimental design to aid in primary and secondary processing. Biological Samples Details Need Metadata Library Construction Details Need Metadata Instrument Details Need Metadata
- 30. 11/29/2018 BioDataWorld Congress - Basel How do we handle disruptions new measurement technologies bring? Long Reads Sequence unfragmented cDNA libraries Short Reads are sequenced on fragmented cDNA libraries Capturing the full length (5’ UTR to 3’ UTR) open reading frames at the transcript level Measuring theTranscriptome allows us to peer into the Proteome Validation can occur with peptides This Sample SpecificTranscriptome containsAlternatively SplicedTranscripts Specific to the SampleCollected – altering the gene model for that sample We need to capture the gene model in Data Commons for future reuse
- 31. FAIR Data Action Plan (Preliminary Steps) Interim recommendations and actions from the European Commission Expert Group on FAIR data 11/29/2018 BioDataWorld Congress - Basel
- 32. FAIR Data Action Plan (Preliminary Steps) Interim recommendations and actions from the European Commission Expert Group on FAIR data 11/29/2018 BioDataWorld Congress - Basel Define and apply FAIR appropriately Develop and support a sustainable FAIR data ecosystem Ensure FAIR data and certified services to support FAIR 1 2 3
- 33. 11/29/2018 BioDataWorld Congress - Basel FAIR Data Object (Core Bits)
- 34. BioDataWorld Congress - Basel11/29/2018 Genome Technologies Imaging Services Single Cell Services Grant Award Data Analysis Repeat Google Cloud Platform Docker TCGA JAX Pipelines API Analysis Program URL RESULTS ISB-CGC /mnt/input /mnt/output - ISB-CGC - JAX-pipelines - Analysis Program - Google Cloud ATypical Researcher’s Path Paper Writing & Acceptance TIER 1 TIER 3 TIER 2 SRA GEO
- 35. BioDataWorld Congress - Basel11/29/2018 Genome Technologies Imaging Services Single Cell Services Grant Award Data Analysis Repeat Google Cloud Platform Docker TCGA JAX Pipelines API Analysis Program URL RESULTS ISB-CGC /mnt/input /mnt/output - ISB-CGC - JAX-pipelines - Analysis Program - Google Cloud Where is the metadata and where is it captured? Paper Writing & Acceptance TIER 1 TIER 3 TIER 2 SRA GEO BioProject: What was the question being asked? Experimental Design: What tissue is being measured? How was the library constructed? At what time points were the data collected? SRA: BioSample: Raw FASTQ files stored - controlled access data? Matrices: Junction Count by Sample Instrument Details: which version of the instrument? What chemistries Sample Collection Details – affects quality – when and where were the samples collected Library Construction Details: fragmented or unfragmented libraries?
- 36. NCI Cancer Research Data Commons 11/29/2018 Data Stewardship | 36
- 37. 11/29/2018 BioDataWorld Congress - Basel #datagovernancematters
- 38. Data management plans needed for data produced We need metadata (data about our data) including instruments We need to adhere to W3C standards, RDF, data catalogs, publish data Ontologies should be used everywhere More metadata need to be captured Data need to be FAIR by man and machine 11/29/2018 Data Stewardship Data Commons Data Management for Data Stewardship: 1 2 3 4 5 6 | 38
- 39. THANK YOU!
Hinweis der Redaktion
- To discover precise genomic solutions for disease and empower the global biomedical community in the shared quest to improve human health. Founded in 1929, The Jackson Laboratory (JAX) is an independent, nonprofit biomedical research institution with more than 2,200 employees who are passionate about our mission. The Laboratory is a world leader in mammalian genetics and human genomics and is developing scientific breakthroughs and improved therapies with ever-greater precision and speed. We also educate current and future scientists and provide critical resources, data, tools, and services to researchers worldwide. JAX has its mammalian genetics headquarters in Bar Harbor, Maine including a National Cancer Institute-designated Cancer Center; a genomic medicine facility in Farmington, Conn. enabling translation of fundamental research into the clinic; and facilities in Ellsworth, Maine and Sacramento, Calif.
- Although both PacBio and Oxford Nanopore generate longer reads compared to short read Illumina or Ion sequencing, the higher error rate of both the PacBio and Oxford Nanopore sequencers remain an issue needs addressing. Whereas PacBio reads a molecule multiple times to generate high-quality consensus data, Oxford Nanopore can only sequence a molecule twice. As a result, PacBio generates data with lower error rates compared to Oxford Nanopore. PacBio has a slightly better overall performance for applications such as the discovery of transcriptome complexity and sensitive identification of isoforms. On the other hand, MinION provides higher throughput as nanopores can sequence multiple molecules simultaneously. Hence, it is best suited for applications that require a larger amount of data9
- Although both PacBio and Oxford Nanopore generate longer reads compared to short read Illumina or Ion sequencing, the higher error rate of both the PacBio and Oxford Nanopore sequencers remain an issue needs addressing. Whereas PacBio reads a molecule multiple times to generate high-quality consensus data, Oxford Nanopore can only sequence a molecule twice. As a result, PacBio generates data with lower error rates compared to Oxford Nanopore. PacBio has a slightly better overall performance for applications such as the discovery of transcriptome complexity and sensitive identification of isoforms. On the other hand, MinION provides higher throughput as nanopores can sequence multiple molecules simultaneously. Hence, it is best suited for applications that require a larger amount of data9
- The European Union FAIR data action plan published June 2018 outlines the core bits of information that should be collected on data to make data meaningful. These include the need for persistent and unique identifiers, open and documented formats for the transformation of that data, using data object identifiers (DOIs) or unique resource identifiers, to enable stable links to objects and support for citations and reuse. Authors should be identified with unique identifiers (such as ORCIDs), projects (RAIDs), funders and associated research resources (RRIDs). The action plan goes on to state that open and documented formats for standards and code should employed and that while minimum metadata and documentation is necessary to accompany these core data bits, enabling basic data discovery, richer information and provenance is necessary to understand why, when and by whom the data were created and accompanied with an appropriate data usage license
- One researchers path Get a grant – order data generating services, PDX, Single Cell, Other Genomic Technology services, do some data analysis, you might do some analysis in the cloud, the data are archived, likely with metadata embedded in the filestructure of the data – usually, project, sample, sequencing data, upon paper acceptance or ahead of that, your sequencing data, along with appropriate metadata may need to be uploaded to the Sequence Read Archive (SRA) or to the Geomnibus (GEO) which then loads it up to the SRA and then this process is repeated. Repeating this process, different Researchers arrange their work in different ways, the data and the metadata may be embedded in the directory structure, or there maybe different MySQL databases around that contain each of the individual projects It could be that the data is arranged in a way that all a researchers project information is available to the researcher, sharing it with others is laborious and time consuming To be data driven, we need to access data across silos
- One researchers path Get a grant – order data generating services, PDX, Single Cell, Other Genomic Technology services, do some data analysis, you might do some analysis in the cloud, the data are archived, likely with metadata embedded in the filestructure of the data – usually, project, sample, sequencing data, upon paper acceptance or ahead of that, your sequencing data, along with appropriate metadata may need to be uploaded to the Sequence Read Archive (SRA) or to the Geomnibus (GEO) which then loads it up to the SRA and then this process is repeated. Repeating this process, different Researchers arrange their work in different ways, the data and the metadata may be embedded in the directory structure, or there maybe different MySQL databases around that contain each of the individual projects It could be that the data is arranged in a way that all a researchers project information is available to the researcher, sharing it with others is laborious and time consuming To be data driven, we need to access data across silos
- RDF Ontologies Data Catalogs Unique Identifiers for protective Name Spaces SPARQL allows for a query to consist of triple patterns, conjunctions, disjunctions, and optional patterns. We will build a Linked Data Layer - using tools where they make sense SPARQL - SPARQL (pronounced "sparkle", a recursive acronym[2] for SPARQL Protocol and RDF Query Language) is an RDF query language, that is, a semantic query language for databases, able to retrieve and manipulate data stored in Resource Description Framework (RDF) format.[3][4]