Genome-wide analysis using network-based meta-analysis

OData support
Supervisor:
Dr. Antal Péter
Department of Measurement and Information Systems

Genome-wide analysis of common genetic variants produces hierarchy of results about variants, genes, pathway related to the investigated disease or trait. Meta-analysis of these results is motivated by the hardness of accessing the original genetic data, by the complexity of the analysis workflow and its high computational burden. Further reasons for post-processing such statistical results are the investigation of the robustness and sensitivitiy of the analysis, especially in the case multimorbidity.

Main activities in my research were as follows:

• I overviewed the workflow of genome-wide genetic data analyis, especially application of network propagation methods.

• I summarized the reasons and strategies for using multiple workflows, especially to explore shared mechanisms of multimorbidities.

• I developed a software system to support the automation of the data analysis workflow.

• I developed methods to support the intepretation of the results, especially in multimorbidity analysis.

• I investigated the applicability of the developed methods

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