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Ontologies for Immunology

1991198283914738. Ontologies for Immunology . Barry Smith. https://immport.niaid.nih.gov/. NIAID Division of Allergy, Immunology and Transpantation (DAIT). Areas of Research Allergic Diseases Asthma Autoimmune Diseases Food Allergy Immune Tolerance

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Ontologies for Immunology

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  1. 1991198283914738 Ontologies for Immunology Barry Smith

  2. https://immport.niaid.nih.gov/

  3. NIAID Division of Allergy, Immunology and Transpantation (DAIT) Areas of Research • Allergic Diseases • Asthma • Autoimmune Diseases • Food Allergy • Immune Tolerance • Medical Countermeasures Against Radiological and Nuclear Threats • Transplantation

  4. DAIT-Funded ProjectsDepositing Data into ImmPort • Immune Tolerance Network (ITN) • Atopic Dermatitis and Vaccinia Network (ADVN) • Population Genetics Analysis Program • Immune Function and Biodefense in Children, Elderly, and Immunocompromised Populations • HLA Region Genetics in Immune-Mediated Diseases • Modeling Immunity for Biodefense

  5. Goals of ImmPort • Accelerate a more collaborative and coordinated research environment • Create an integrated database that broadens the usefulness of scientific data • Advance the pace and quality of scientific discovery while extending the value of scientific data in all areas of immunological research • Integrate relevant data sets from participating laboratories, public and government databases, and private data sources • Promote rapid availability of important findings • Provide analysis tools to advance immunological research

  6. Standards and ontologies needed to advance especially this • Integrate relevant data sets from participating laboratories, public and government databases, and private data sources

  7. SDY 165: Characterization of in vitro Stimulated B Cells from Human Subjects shared to Semi-Public Workspace (SPW) Proje

  8. SDY 165: Characterization of in vitro Stimulated B Cells from Human Subjects shared to Semi-Public Workspace (SPW) Project During the human B cell (Bc) recall response, rapid cell division results in multiple Bc subpopulations. RNA microarray and functional analyses showed that proliferating CD27lo cells are a transient pre-plasmablast population, expressing genes associated with Bc receptor editing. Undivided cells had an active transcriptional program of non-ASC B cell functions, including cytokine secretion and costimulation, suggesting a link between innate and adaptive Bc responses. Transcriptome analysis suggested a gene regulatory network for CD27lo and CD27hi Bc differentiation. 

  9. Functionally Distinct Subpopulations of CpG-Activated Memory B Cells, Alicia D. Henn … & Martin S. Zand, Pubmed 2246822 Figure 5: The Fate of CD27lo cells

  10. ImmPort Antibody Registry

  11. ImmPort Antibody Registry BD Lyoplate Screening Panels Human Surface Markers

  12. http://pir.georgetown.edu/cgi-bin/pro/entry_pro?id=PR:000001963http://pir.georgetown.edu/cgi-bin/pro/entry_pro?id=PR:000001963

  13. Discoverability • Find all ImmPort studies involving genes associated with B cell receptor editing • Find all data in public and government databases relating to B cell receptor editing

  14. GOPubMed: 179 documents

  15. (B cell receptor editing Zand) AND ("Zand"[au])

  16. SDY 165 Discoverability During the human B cell (Bc) recall response, rapid cell division results in multiple Bc subpopulations. RNA microarray and functional analyses showed that proliferating CD27lo cells are a transient pre-plasmablast population, expressing genes associated with Bc receptor editing. Undivided cells had an active transcriptional program of non-ASC B cell functions, including cytokine secretion and costimulation, suggesting a link between innate and adaptive Bc responses. Transcriptome analysis suggested a gene regulatory network for CD27lo and CD27hi Bc differentiation. 

  17. NIAID Sample Data Sharing Plan (Last Reviewed February 12, 2013) • Sharing of data generated by this project is an essential part of our proposed activities and will be carried out in several different ways. • Presentations at national scientific meetings.… it is expected that approximately four presentations at national meetings would be appropriate. … • Annual lectureship. A lectureship has brought to the University distinguished scientists and clinicians … • Newsletter. The [disease interest group] publishes a newsletter … • Web site of the Interest Group. The [interest group] currently maintains a Web site where information [about the disease] is posted. Summaries of the scientific presentation from the [quarterly project] meetings will be posted on this Web site, written primarily for a general audience. [Link to Web site] • Annual [Disease] Awareness wee k…. • SAGE Library Data.It is our explicit intention that these [Serial analysis of gene expression] data will be placed in a readily accessible public database. …

  18. Plan addressing Key Elements for a Data Sharing Plan under NIH Extramural Support (Last Reviewed August 09, 2012) What data that will be shared [sic]: I will share phenotypic data associated with the collected samples by depositing these data at _______which is an NIH-funded repository. ... Additional data documentation and de-identified data will be deposited for sharing along with phenotypic data, which includes demographics, family history of XXXXXX disease, and diagnosis, consistent with applicable laws and regulations. … Meta-analysis data and associated phenotypic data, along with data content, format, and organization, will be available at ___. Submitted data will confirm [sic] with relevant data and terminology standards. Who will have access to the data: …Where will the data be available: … When will the data be shared: … How will researchers locate and access the data: I agree that I will identify where the data will be available and how to access the data in any publications and presentations that I author or co-author about these data … repository has policies and procedures in place that will provide data access to qualified researchers, fully consistent with NIH data sharing policies and applicable laws and regulations.

  19. What should be required / recommended • LOINC • CDISC • BRIDG • SNOMED • Minimal Information Checklists • OBI • Immunology Ontologies

  20. Lab resources do not recommend use of LOINC http://www.niaid.nih.gov/LabsAndResources/resources/DAIDSClinRsrch/Documents/gclp.pdf

  21. Can some these be built into • LDMS • LIS • CTMS • EHRs

  22. need to explore relation of SDY data in ImmPort to CDISC

  23. From the Summary specification

  24. CDISC definitions • A study arm represents one planned path through the study. The path is composed of a study cell for each epoch in the study. • A study cell is the part of study design that describes what happens in a particular epoch for a particular arm. The cell describes how the purpose of its epoch is fulfilled for each arm.

  25. CDISC Structural Elements Building blocks of a study design: Epochs, Cells, Arms, Segments, Activities • A study arm represents a path • A path is composed of a cell • A cell is a part of a study design • A cell describes what happens in an epoch • An Activity represents a point in a study at which a specific action is to be taken.

  26. BRIDG • http://bridgmodel.nci.nih.gov/files/BRIDG_Model_3.2_html/index.htm

  27. BRIDG Adverse Event

  28. BRIDG Adverse Event

  29. Product Brief - Biomedical Research Integrated Domain Group (BRIDG) Implementations/ Case Studies (Actual Users) • The BRIDG Project is a collaborative effort engaging stakeholders from four organizations: • Clinical Data Interchange Standards Consortium (CDISC) • HL7 Regulated Clinical Research Information Management Working Group (HL7 RCRIM WG) • National Cancer Institute (NCI), including the Cancer Biomedical Informatics Grid (caBIG™) project • Food and Drug Administration (FDA)

  30. Does BRIDG have any users?

  31. What should be required / recommended • LOINC • CDISC • BRIDG • SNOMED • Minimal Information Checklists • OBI • Immunology Ontologies

  32. MIFLOWCYT: Minimal Information for a Flow Cytometry Experiment

  33. Minimal Information about a Cellular Assay Project Header Source: Contact details of researcher/person in charge of the project (name, affiliation/institution, department, address, Email, etc.). Project: Description (text) of the project within a larger context (biological process that is addressed; description of measured effect, controls, etc.). Application: Description (text) of the specific application of this project (abstract; reference to publication). Array(s): culturing and reaction container(s) that are used during the project (name; • identifier; type (e.g. 384, 96, 24 well, flask, glass slide for cell arrays); vendor or • manufacturer; order-number; surface area/feature size. CellLine(s): Description of cell lines employed (name; identifier; ATCC number (if applicable) or details: Species, tissue, organ, contact-details (when from different lab); • reference to publication; passage number; mycoplasma test (Y/N) and other validation; • modifications (optional, if any made, e.g. stably transfected, induced resistance, etc.). Reagents: Media, supplements, kits, buffers, and solutions (name, identifier, vendor or manufacturer, order number, lot number). Perturbator(s): Description of materials/conditions that are used in the project to perturb the cells (type - e.g. siRNA, cDNA, small chemical compound, name, external references - • gene/protein identifiers/order numbers, sequences if applicable). Instrument(s): Description of the data acquisition station and other instruments utilized in the project, e.g. for transfection (name, type, model, manufacturer).

  34. Minimal Information about a Cellular Assay Experimental modules Treatment(s): Description of the conditions that are applied to the cells during culturing (name, identifier, time-stamp, materials used, volume, actual passage number of cells, seeding density, temperature, CO2-content, humidity). Perturbation(s): Description of the perturbation, (special case of a treatment), which describes the application of ‘perturbator(s)’, e.g. transfection (siRNA, expression clone), treatment with small compound, temperature shift, etc. PostTreatment(s): Description of the conditions that are applied after culturing and prior to data acquisition, i.e. lysis, fixation, staining, antibody incubation, etc. DataAcquisition(s): Detection of the effect(s) induced by the perturbation (identifier, time stamp, reference to instrument above, instrument-settings, e.g. excitation and emission wavelengths with filter sets, lamp/Laser energy). DataProcessing Description of the processes applied to analyze the raw-data in order to generate a hit list. Reference to publication(s) describing the procedures and/or to software utilized (incl. version and settings). Links to the raw, the processed, and to the interpreted data.

  35. Minimal Information about a T-Cell Assay • Janetzki S, Britten CM, Kalos M, Levitsky HI, Maecker HT, Melief CJ, Old LJ, Romero P, Hoos A, Davis MM. 2009. "MIATA"-Minimal Information about T Cell Assays. Immunity. 31: 527-8

  36. http://www.miataproject.org/

  37. http://mibbi.sourceforge.net/portal.shtml

  38. MIBBI= Minimal Information about a Biological or Biomedical Investigation • How to make MIBBI checklists non-redundant, factorable, such as to support interoperability / sharing of data? • Need to use the same words for the same things and events in each checklist • OBI = Ontology for Biomedical Investigations

  39. OBI representation of a neuroscience study

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