Abstract
BackgroundLinking genotypic and phenotypic information is one of the greatest challenges of current genetics research. The definition of an Information Technology infrastructure to support this kind of studies, and in particular studies aimed at the analysis of complex traits, which require the definition of multifaceted phenotypes and the integration genotypic information to discover the most prevalent diseases, is a paradigmatic goal of Biomedical Informatics. This paper describes the use of Information Technology methods and tools to develop a system for the management, inspection and integration of phenotypic and genotypic data.ResultsWe present the design and architecture of the Phenotype Miner, a software system able to flexibly manage phenotypic information, and its extended functionalities to retrieve genotype information from external repositories and to relate it to phenotypic data. For this purpose we developed a module to allow customized data upload by the user and a SOAP-based communications layer to retrieve data from existing biomedical knowledge management tools. In this paper we also demonstrate the system functionality by an example application of the system in which we analyze two related genomic datasets.ConclusionIn this paper we show how a comprehensive, integrated and automated workbench for genotype and phenotype integration can facilitate and improve the hypothesis generation process underlying modern genetic studies.
Highlights
Linking genotypic and phenotypic information is one of the greatest challenges of current genetics research
In this paper we show how a comprehensive, integrated and automated workbench for genotype and phenotype integration can facilitate and improve the hypothesis generation process underlying modern genetic studies
In this paper we describe the overall architecture of the system, which exploits a distributed architecture based on Web Services to integrate the Phenotype miner with two additional modules that support automated hypothesis generation process as an integral part of modern translational research
Summary
Linking genotypic and phenotypic information is one of the greatest challenges of current genetics research. One of the most challenging goals of current biomedical research is to link the genotypic and phenotypic information generated by high-throughput experimental technologies [1]. The price to pay for this paradigmatic shift is that researchers will increasingly need to handle very large volumes of heterogeneous data, both generated by their own experiments and retrieved from publicly available repositories of genomic knowledge. New data storage and retrieval systems will need to be adopted in order to handle the unprecedented volumes of data and information being generated in an efficient and productive way. These tools, should be accessible to the broad research community, facilitating the discovery process by providing high usability and effective automation.
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