Technological advancement in Genomics has propelled research in a new era, where methods of conducting experiments have completely been renovated. Riding the wave of Information Technology, equipped with statistical tools, Genomics provide a revolutionized perspective unthought-of in the past. With the completion of the Human Genome project, we have a common reference for analysis at the level of the complete genome. High throughput technologies for gene expression, genotyping and sequencing are propelling present research. Attempts are now being made for the incorporation of these methods in the health care in a structured format. Clinicians cherish the use of genomics for the assessment disease predisposition and realizing personalized medical care for a better health care. As genome sequencing is becoming swifter and its cost reducing, the public genomic data has increased many folds. Data from other high throughput technologies and annotations further increase the storage requirements. Laboratory management software, LIMS, is now becoming the limiting factor as automation and integration increases. Thus genomics now faces the challenge of management of this enormous data catering to varied needs, not limited only for the research laboratories, but extends also to health care institutions and individual clinicians. Further, there is a growing need for the analysis and visualization of the generated data to be integrated into the same platform for a continuous research experience and systematic supervision. Data security is of prime concern, especially in health care concerning human subjects. The interest of the clinicians adds another management requirement, a delivery system for the concerned subject. Hypertension is a complex disorder with world-wide prevalence. HYPERGENES project was centered on the objective of integrating biological data and processes with Hypertension as the disease model. The HYPERGENES project focuses on the definition of a comprehensive genetic epidemiological model of complex traits like Essential Hypertension (EH) and intermediate phenotypes of hypertension such as Target Organ Damage (TOD). During the HYPERGENES project, the above mentioned challenges were comprehended and evaluated, leading to the present work as an endeavor to provide a generalized integrated solution towards the management of genomic and clinical data for clinical genomic research. This PhD thesis represents the description of AD2BioDB, biological data management platform and SeqPipe, dynamic pipeline management software, in the path of meeting the challenges posed in the area of clinical genomics. AD2BioDB provides the platform where data generated using different technologies can be managed and analyzed with reporting and visualization modules for improved understanding of the results among all research collaborators. AD2BioDB is the management software environment in which the in-silico data can be shared and analyzed. The analysis software is connected within AD2BioDB through the plug-in system. SeqPipe software provides opportunity to dynamically create pipeline workflows for the multi-step analysis of data. The interactive graphical user interface provides the opportunity for coding free pipeline creation and analysis. This tool is especially useful in the dynamic NGS analysis, where multiple tools i with different versions are in use. SeqPipe can be used as independent software or as a plug-in analysis tool within an application like AD2BioDB. The key features of AD2BioDB can be summarized as:  Clinical genomics data management  Project management  Data security  Dynamic creation of graphical representation.  Distributed workflow analysis  Reporting and alert features.  Dynamic integration of high throughput technologies We developed AD2BioDB as a prototype in our laboratory for providing support to the increasing genomic data and complexity of analysis. The software aims at providing a continuous research experience with a versatile platform that supports data management, analysis and public knowledge integration. Through the integration of SeqPipe into AD2BioDB, the management system becomes robust in providing a distributed analysis environment.

CLINICAL GENOMIC RESEARCH MANAGEMENT / A. Bhattacharyya ; tutore: D. Cusi ; direttore della Scuola: M. Clerici. - : . DIPARTIMENTO DI FISIOPATOLOGIA MEDICO-CHIRURGICA E DEI TRAPIANTI, 2013 Feb 12. ((25. ciclo, Anno Accademico 2012. [10.13130/bhattacharyya-amitava_phd2013-02-12].

CLINICAL GENOMIC RESEARCH MANAGEMENT

A. Bhattacharyya
2013

Abstract

Technological advancement in Genomics has propelled research in a new era, where methods of conducting experiments have completely been renovated. Riding the wave of Information Technology, equipped with statistical tools, Genomics provide a revolutionized perspective unthought-of in the past. With the completion of the Human Genome project, we have a common reference for analysis at the level of the complete genome. High throughput technologies for gene expression, genotyping and sequencing are propelling present research. Attempts are now being made for the incorporation of these methods in the health care in a structured format. Clinicians cherish the use of genomics for the assessment disease predisposition and realizing personalized medical care for a better health care. As genome sequencing is becoming swifter and its cost reducing, the public genomic data has increased many folds. Data from other high throughput technologies and annotations further increase the storage requirements. Laboratory management software, LIMS, is now becoming the limiting factor as automation and integration increases. Thus genomics now faces the challenge of management of this enormous data catering to varied needs, not limited only for the research laboratories, but extends also to health care institutions and individual clinicians. Further, there is a growing need for the analysis and visualization of the generated data to be integrated into the same platform for a continuous research experience and systematic supervision. Data security is of prime concern, especially in health care concerning human subjects. The interest of the clinicians adds another management requirement, a delivery system for the concerned subject. Hypertension is a complex disorder with world-wide prevalence. HYPERGENES project was centered on the objective of integrating biological data and processes with Hypertension as the disease model. The HYPERGENES project focuses on the definition of a comprehensive genetic epidemiological model of complex traits like Essential Hypertension (EH) and intermediate phenotypes of hypertension such as Target Organ Damage (TOD). During the HYPERGENES project, the above mentioned challenges were comprehended and evaluated, leading to the present work as an endeavor to provide a generalized integrated solution towards the management of genomic and clinical data for clinical genomic research. This PhD thesis represents the description of AD2BioDB, biological data management platform and SeqPipe, dynamic pipeline management software, in the path of meeting the challenges posed in the area of clinical genomics. AD2BioDB provides the platform where data generated using different technologies can be managed and analyzed with reporting and visualization modules for improved understanding of the results among all research collaborators. AD2BioDB is the management software environment in which the in-silico data can be shared and analyzed. The analysis software is connected within AD2BioDB through the plug-in system. SeqPipe software provides opportunity to dynamically create pipeline workflows for the multi-step analysis of data. The interactive graphical user interface provides the opportunity for coding free pipeline creation and analysis. This tool is especially useful in the dynamic NGS analysis, where multiple tools i with different versions are in use. SeqPipe can be used as independent software or as a plug-in analysis tool within an application like AD2BioDB. The key features of AD2BioDB can be summarized as:  Clinical genomics data management  Project management  Data security  Dynamic creation of graphical representation.  Distributed workflow analysis  Reporting and alert features.  Dynamic integration of high throughput technologies We developed AD2BioDB as a prototype in our laboratory for providing support to the increasing genomic data and complexity of analysis. The software aims at providing a continuous research experience with a versatile platform that supports data management, analysis and public knowledge integration. Through the integration of SeqPipe into AD2BioDB, the management system becomes robust in providing a distributed analysis environment.
CUSI, DANIELE MARIA
CLERICI, MARIO SALVATORE
Settore MED/03 - Genetica Medica
CLINICAL GENOMIC RESEARCH MANAGEMENT / A. Bhattacharyya ; tutore: D. Cusi ; direttore della Scuola: M. Clerici. - : . DIPARTIMENTO DI FISIOPATOLOGIA MEDICO-CHIRURGICA E DEI TRAPIANTI, 2013 Feb 12. ((25. ciclo, Anno Accademico 2012. [10.13130/bhattacharyya-amitava_phd2013-02-12].
Doctoral Thesis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/217475
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