An Ontology-Based Approach for Computational Phenomics: Application to Autism Spectrum Disorder. Stanford Center for Biomedical Informatics Research

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1 An Ontology-Based Approach for Computational Phenomics: Application to Autism Spectrum Disorder Stanford Center for Biomedical Informatics Research

3 Psychiatric Genetics Phenotyping Terminology Ontology Logic

4 Hasler G,et al. Toward constructing an endophenotype strategy for bipolar disorders. Biological Psychiatry (2006) Represent findings and their links using structured knowledge

5 Freimer & Sabatti, Nature Genetics (2003)

7 Mailman, M.D. Nature Genetics (2007)

18 NDAR System Clinical Assessments (OpenClinica) Neuroimaging Genomics BIRN Services & Resources Subject Tracking & Management Image Analysis Security Common Measures Image Processing Genomics data access Portal Study Management Image data access Grid Computing Data Integration Collaboration Query and Reporting User Management Data Integration Tools Auditing Data Storage Management

24 Tu, S. W. AMIA Annual Proceedings (2008)

26 Clinical Research Study Case Study Clinical Trial Study Controlled Case Study Study Arms

30 Subject hasresult isbearerof Genotype mutin- RELN Macroencephaly Phenotype

Terms cover neuroanatomy, molecular species, behavioral and

31 A controlled terminology for annotation of BIRN data sources, focusing on imaging data from human subjects and mouse models Terms cover neuroanatomy, molecular species, behavioral and cognitive processes, subject information, experimental practice and design

34 RELATI ON TO TIM E CONTINU ANT OCCURRENT GRAN ULAR ITY INDE PENDENT DEPENDENT ORGAN AN D ORGAN ISM CELL AND CELLUL AR COMP ONENT Orga nism (NCBI Taxonomy) Cell (CL) Anatomical Entit y (FMA, CARO) Cellular Compo nent (FMA,GO) Organ Function (FMP, CPR O) Cellular Function (GO) Phenot ypic Quality (PaTO ) Orga nism - Level Process (GO) Cellular Process (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) Chris Mungall, PATO

36 hasparent(?x,?y) ^ hasbrother(?y,?z) hasuncle(?x,?z)

37 Person(Amar) ^ hassibling(amar,?s) ^ Woman(?s) hassister(amar,?s)

38 Person(?p) ^ hasage(?p,?age) ^ swrlb:lessthan(?age,17) Child(?p)

42 Figure 1. The representation of data collected through the ADI-2003 autism assessment instrument as part of the autism ontology.

43 Figure 2. The representation of the Status of age of words phentotype group as a OWL class partition by the possible statuses.

44 ADI_2003_result(?assessment) ^ acqorlossoflang_aword(?assessment,?wordage) ^ swrlb:greaterthan(?wordage, 24) ^ subject_id(?assessment,?subjectid) ^ orgtax:human(?subject) ^ subject_id(?subject,?subjectid) birn_obo_ubo:bearer_of(?subject, Delayed_word)

46 Young, L. IEEE CBMS (2009)

47 Develop an ontology of endophenotypes that maps brain connectivity, neural deficits, and genetic markers into a subject domain theory Develop logic-based methods to encode and classify endophenotypes based on multi-scale measurements Create tools to acquire new endophenotypes and annotate phenotype-genotype findings in online resources such as published literature Develop query-elicitation methods that can evaluate hypotheses about the subject domain theory of endophenotypes using deductive inference

48 Query Dat abase Catalog Phenot ype Def init ions New Associat ions Analysis

Using an Integrated Ontology and Information Model for Querying and Reasoning about Phenotypes: The Case of Autism

Using an Integrated Ontology and Information Model for Querying and Reasoning about Phenotypes: The Case of Autism Samson W. Tu, MS, Lakshika Tennakoon, RMP, MSC, MPhil, Martin O'Connor, MS, Ravi Shankar,