Facioscapulohumeral dystrophy (FSHD) is a rare genetic disease that has been described more than a hundred years ago. The Miogen Lab has been able to collect a large amount of data on patients affected by FSHD and their relatives over the years, also extending the research to their ancestors. Collected data include molecular analysis, clinical information on health status, family pedigree and geographic origin. The challenge of FSHD Registry is to investigate these large amount of information, discover additional elements related to disease onset and better understand the clinical progression and genetic inheritance of the disease, exploiting data integration capabilities and Big Data techniques. In this paper we describe the tools we used to collect, integrate and display these data in a framework that allows users to search among clinical records to elaborate brief reports and discover new relations on collected data. The solution provides charts, maps and search tools customized on the specific needs that came to light during the collaboration between DataRiver and Miogen Lab, joining the clinical knowledge of the latter with the information technology expertise of the former. The framework offers a single entry point for all genomic and therapeutic studies.

The Italian FSHD registry: An enhanced data integration and analytics framework for smart health care

GAGLIARDELLI, LUCA;
2017-01-01

Abstract

Facioscapulohumeral dystrophy (FSHD) is a rare genetic disease that has been described more than a hundred years ago. The Miogen Lab has been able to collect a large amount of data on patients affected by FSHD and their relatives over the years, also extending the research to their ancestors. Collected data include molecular analysis, clinical information on health status, family pedigree and geographic origin. The challenge of FSHD Registry is to investigate these large amount of information, discover additional elements related to disease onset and better understand the clinical progression and genetic inheritance of the disease, exploiting data integration capabilities and Big Data techniques. In this paper we describe the tools we used to collect, integrate and display these data in a framework that allows users to search among clinical records to elaborate brief reports and discover new relations on collected data. The solution provides charts, maps and search tools customized on the specific needs that came to light during the collaboration between DataRiver and Miogen Lab, joining the clinical knowledge of the latter with the information technology expertise of the former. The framework offers a single entry point for all genomic and therapeutic studies.
2017
9781538639061
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11389/69816
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