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PPPA: Push and Pull Pedigree Analyzer for large and complex pedigree databases


Mazeika, Arturas; Peterson, Janis; Böhlen, Michael H (2006). PPPA: Push and Pull Pedigree Analyzer for large and complex pedigree databases. In: 10th East-European Conference on Advances in Databases and Information Systems, Tessaloniki, Greece, 3 September 2006 - 7 September 2006, 339-352.

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.

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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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:7 September 2006
Deposited On:29 May 2012 09:15
Last Modified:12 Aug 2017 15:46
Publisher:Springer
Series Name:Lecture Notes in Computer Science
Number:4152
ISSN:0302-9743
Publisher DOI:https://doi.org/10.1007/11827252_26
Related URLs:http://delab.csd.auth.gr/adbis2006/
Other Identification Number:merlin-id:6165

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