Mining phenotype databases to identify mouse models of clinical relevance
Phenotype Database and Data Mining at RGD
1
Phenotype Database and Data Mining at RGD Mary Shimoyama Rat Genome Database, Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, Wisconsin Strain Taxonomy Experimental Conditions Clinical Measurement Measurement Method Standardizing Phenotype Data with Ontologies 1 2 Data Mining Using Ontologies 3 4 Ontology/Vocabulary Sample Study Experiment Experimental Conditions Clinical Measurement Strain Ontology Experimental Condition Ontology Clinical Measurement Ontology Assay type Ontology Ontology/Vocabulary Sample Researcher Study Experiment Experimental Conditions Clinical Measurement Strain Ontology Strain Ontology Experimental Condition Ontology Experimental Condition Ontology Clinical Measurement Ontology Clinical Measurement Ontology Assay type Ontology Measurement Method Ontology Major components of phenotype data records 5 8 7 6 9 ABSTRACT: There has been an emergence of multiple large scale phenotype projects in the rat model organism community as well as renewed interest in the ongoing phenotype data generated by thousands of researchers using hundreds of rat strains. In order to provide ready access to such data, the Rat Genome Database (RGD), http://rgd.mcw.edu is developing a Rat Phenome Database, http://rgd.mcw.edu/phenotypes . To integrate data from multiple datasets and published literature, RGD is developing a Rat Strain Taxonomy and three ontologies to standardize the major aspects of phenotype records: Clinical Measurement Ontology Measurement Method Ontology and Experimental Conditions Ontology In a pilot study phenotype data from Physgen http://pga.mcw.edu the National BioResource Project for the Rat in Japan http://www.anim.med.kyoto-u.ac.jp/nbr/ and data from published literature were integrated. A data mining tool was developed to leverage the utility of the ontologies. Users may begin their search with any of the four components of the phenotype data. In the example, the user chooses a Clinical Measurement followed by a filter for Measurement Method and Experimental Conditions and finally limits the search by Strain The tool keeps track of the search parameters and provides a running count of records retrieved. Only filter choices applicable to set parameters and for which there is data are presented to the user. Results can be downloaded in both summary and expanded formats Development of the ontologies for use with rat phenotypes continues and expansions and modifications are being applied for use with the human clinical data from the Family Blood Pressure Project in conjunction with Washington University School of Medicine. 1 2 3 4 5 6 7 8 9 10 10 Users may choose to start from any of the 4 phenotype components The ontology is presented with number of associated records Tool keeps track of query and number of records returned. Second filter chosen Query parameters and record counts shown Query record maintained Results may be seen and downloaded in summary or expanded formats Only applicable choices for which there are data are presented RGD is funded by grant HL64541 from the National Heart, Lung, and Blood Institute on behalf of the NIH. 1%
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Transcript of Phenotype Database and Data Mining at RGD
Phenotype Database and Data Mining at RGDMary Shimoyama
Rat Genome Database, Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, Wisconsin
Strain Taxonomy Experimental Conditions
Clinical Measurement Measurement Method
Standardizing Phenotype Data with Ontologies
1 2
Data Mining Using Ontologies
3 4
Ontology/Vocabulary
Sample
Study
Experiment
Experimental Conditions
Clinical Measurement
Strain Ontology
Experimental Condition Ontology
Clinical Measurement Ontology
Assay type Ontology
Ontology/Vocabulary
Sample
Researcher
Study
Experiment
Experimental Conditions
Clinical Measurement
Strain OntologyStrain Ontology
Experimental Condition Ontology
Experimental Condition Ontology
Clinical Measurement Ontology
Clinical Measurement Ontology
Assay type OntologyMeasurementMethod
Ontology
Major components of phenotype data records
5
8
76
9
ABSTRACT: There has been an emergence of multiple large scale phenotype projects in the rat model organism community as well as renewed interest in the ongoing phenotype data generated by thousands of researchers using hundreds of rat strains. In order to provide ready access to such data, the Rat Genome Database (RGD), http://rgd.mcw.edu is developing a Rat Phenome Database, http://rgd.mcw.edu/phenotypes . To integrate data from multiple datasets and published literature, RGD is developing a Rat Strain Taxonomy and three ontologiesto standardize the major aspects of phenotype records: Clinical Measurement Ontology Measurement Method Ontology and Experimental Conditions Ontology In a pilot study phenotype data from Physgenhttp://pga.mcw.edu the National BioResource Project for the Rat in Japan http://www.anim.med.kyoto-u.ac.jp/nbr/ and data from published literature were integrated.
A data mining tool was developed to leverage the utility of the ontologies. Users may begin their search with any of the four components of the phenotype data. In the example, the user chooses a Clinical Measurement followed by a filter for Measurement Method and Experimental Conditions and finally limits the search by StrainThe tool keeps track of the search parameters and provides a running count of records retrieved. Only filter choices applicable to set parameters and for which there is data are presented to the user. Results can be downloaded in both summary and expanded formats
Development of the ontologies for use with rat phenotypes continues and expansions and modifications are being applied for use with the human clinical data from the Family Blood Pressure Project in conjunction with Washington University School of Medicine.
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Users may choose to start from any of the 4 phenotype components
The ontology is presented with number of associated records
Tool keeps track of query and number of records returned.
Second filter chosen
Query parameters and record counts shown
Query record maintained
Results may be seen and downloaded in summary or expanded formats
Only applicable choices for which there are data are presented
RGD is funded by grant HL64541 from the National Heart, Lung, and Blood Institute on behalf of the NIH.1%
