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Combining clinical and genomics queries using i2b2 – Three methods

View Article: PubMed Central - PubMed

ABSTRACT

We are fortunate to be living in an era of twin biomedical data surges: a burgeoning representation of human phenotypes in the medical records of our healthcare systems, and high-throughput sequencing making rapid technological advances. The difficulty representing genomic data and its annotations has almost by itself led to the recognition of a biomedical “Big Data” challenge, and the complexity of healthcare data only compounds the problem to the point that coherent representation of both systems on the same platform seems insuperably difficult. We investigated the capability for complex, integrative genomic and clinical queries to be supported in the Informatics for Integrating Biology and the Bedside (i2b2) translational software package. Three different data integration approaches were developed: The first is based on Sequence Ontology, the second is based on the tranSMART engine, and the third on CouchDB. These novel methods for representing and querying complex genomic and clinical data on the i2b2 platform are available today for advancing precision medicine.

No MeSH data available.


Classical i2b2 user interface for use case 1.Which individuals with a lower mode of HLA-DQB1 protein levels (i.e., HLA-DQB1 log protein ratio < 0) have missense or nonsense mutations in that gene? The available ontologies are displayed on the left side and the phenotypic and genotypic concepts used to build the query are shown on the right.
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pone.0172187.g002: Classical i2b2 user interface for use case 1.Which individuals with a lower mode of HLA-DQB1 protein levels (i.e., HLA-DQB1 log protein ratio < 0) have missense or nonsense mutations in that gene? The available ontologies are displayed on the left side and the phenotypic and genotypic concepts used to build the query are shown on the right.

Mentions: Upon logging onto i2b2, the researcher is presented with demographic, phenotypic and genomic characteristics on the left and a query panel on the right. Concepts of interest are dragged from left to right to generate a query. A query is composed by constructing a Venn Diagram out of the square groups on the query panel, where items placed in the same group are logically ORed together and items placed in different groups are logically ANDed together [14]. The query composition for the Common Task Use Case 1 is shown in Fig 2. It shows the HLA-DQ1 protein level placed in panel one with the value specified as <1, genomic variant functions in panel two that modify the SNVs on the gene of interest in panel three. Panels two and three are specified to occur in the same observational instance, that is, to be part of the same n-tuple, i.e. all regarding the same patient variant. From here the query can be expanded for use cases 2–4 by adding to a panel the Polyphen scores, population demographics and/or dbSNP concepts specified with RS number values.


Combining clinical and genomics queries using i2b2 – Three methods
Classical i2b2 user interface for use case 1.Which individuals with a lower mode of HLA-DQB1 protein levels (i.e., HLA-DQB1 log protein ratio < 0) have missense or nonsense mutations in that gene? The available ontologies are displayed on the left side and the phenotypic and genotypic concepts used to build the query are shown on the right.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5384666&req=5

pone.0172187.g002: Classical i2b2 user interface for use case 1.Which individuals with a lower mode of HLA-DQB1 protein levels (i.e., HLA-DQB1 log protein ratio < 0) have missense or nonsense mutations in that gene? The available ontologies are displayed on the left side and the phenotypic and genotypic concepts used to build the query are shown on the right.
Mentions: Upon logging onto i2b2, the researcher is presented with demographic, phenotypic and genomic characteristics on the left and a query panel on the right. Concepts of interest are dragged from left to right to generate a query. A query is composed by constructing a Venn Diagram out of the square groups on the query panel, where items placed in the same group are logically ORed together and items placed in different groups are logically ANDed together [14]. The query composition for the Common Task Use Case 1 is shown in Fig 2. It shows the HLA-DQ1 protein level placed in panel one with the value specified as <1, genomic variant functions in panel two that modify the SNVs on the gene of interest in panel three. Panels two and three are specified to occur in the same observational instance, that is, to be part of the same n-tuple, i.e. all regarding the same patient variant. From here the query can be expanded for use cases 2–4 by adding to a panel the Polyphen scores, population demographics and/or dbSNP concepts specified with RS number values.

View Article: PubMed Central - PubMed

ABSTRACT

We are fortunate to be living in an era of twin biomedical data surges: a burgeoning representation of human phenotypes in the medical records of our healthcare systems, and high-throughput sequencing making rapid technological advances. The difficulty representing genomic data and its annotations has almost by itself led to the recognition of a biomedical &ldquo;Big Data&rdquo; challenge, and the complexity of healthcare data only compounds the problem to the point that coherent representation of both systems on the same platform seems insuperably difficult. We investigated the capability for complex, integrative genomic and clinical queries to be supported in the Informatics for Integrating Biology and the Bedside (i2b2) translational software package. Three different data integration approaches were developed: The first is based on Sequence Ontology, the second is based on the tranSMART engine, and the third on CouchDB. These novel methods for representing and querying complex genomic and clinical data on the i2b2 platform are available today for advancing precision medicine.

No MeSH data available.