An integrated optimization framework for inferring two generation kinships and parental genotypes from microsatellite samples

  • Authors:
  • Daehan Won;Chun-An Chou;W. Art Chaovalitwongse;Tanya Y. Berger-Wolf;Bhaskar Dasgupta;Ashfaq A. Khokhar;Marco Maggioni;Saad Sheikh;Mary V. Ashley;Jason Palagi

  • Affiliations:
  • University of Washington, Seattle, WA;University of Washington, Seattle, WA;University of Washington, Seattle, WA;University of Illinois at Chicago, Chicago, IL;University of Illinois at Chicago, Chicago, IL;University of Illinois at Chicago, Chicago, IL;University of Illinois at Chicago, Chicago, IL;University of Florida, Gainesville, FL;University of Illinois at Chicago, Chicago, IL;University of Illinois at Chicago, Chicago, IL

  • Venue:
  • Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
  • Year:
  • 2012

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Abstract

With the growing development and application of genetic data availability, it provides new possibilities in establishing the genealogical relationships of individual organisms such as sibling reconstruction, parentage inference, and inheritance investigation. We propose a new integrated optimization framework for parental reconstruction of a single-generation population using microsatellite data. Without prior information about the population, our optimization framework uses the combinatorial concepts of Mendel's laws of inheritance to reconstruct sibling groups and in turn identifies the associated parental genotypes. The effectiveness and robustness of our proposed approach were evaluated by both real biological and simulated data sets, covering different mating systems: monogamy, semi-monogamy, and polygamy. Additionally, we compared the results of the proposed approach with other state-of-the-art sibship reconstruction and parentage inference methods. The results demonstrate efficient and accurate inference for parental genotypes, and potentially suggest that our framework can provide an insightful roadmap for investigators to navigate fundamental ecological and evolutionary studies.