Abstract
In this paper we introduce a novel push and pull technique to analyze pedigree data. We present the Push and Pull Pedigree Analyzer (PPPA) to organize large and complex pedigrees and investigate the development of genetic diseases. PPPA receives as input a pedigree (ancestry information) of different families. For each person the pedigree contains information about the occurrence of a specific genetic disease. We propose a new solution to arrange and visualize the individuals of the pedigree based on the relationships between individuals and information about the disease. PPPA starts with random positions of the individuals, and iteratively pushes apart non-relatives with opposite diseases patterns and pulls together relatives with identical disease patterns. The goal is a visualization that groups families with homogeneous disease patterns.
We investigate our solution experimentally with genetic data from peoples from South Tyrol, Italy. We show that the algorithm converges independent of the number of individuals n and the complexity of the relationships. The runtime of the algorithm is super-linear wrt n. The space complexity of the algorithm is linear wrt n. The visual analysis of the method confirms that our push and pull technique successfully deals with large and complex pedigrees.
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Mazeika, A., Petersons, J., Böhlen, M.H. (2006). PPPA: Push and Pull Pedigree Analyzer for Large and Complex Pedigree Databases. In: Manolopoulos, Y., Pokorný, J., Sellis, T.K. (eds) Advances in Databases and Information Systems. ADBIS 2006. Lecture Notes in Computer Science, vol 4152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11827252_26
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DOI: https://doi.org/10.1007/11827252_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37899-0
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