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Bioinformatics 2007 23(13):i49-i56; doi:10.1093/bioinformatics/btm219
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© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reconstructing sibling relationships in wild populations

Tanya Y. Berger-Wolf 1,*, Saad I. Sheikh 1, Bhaskar DasGupta 1, Mary V. Ashley 2, Isabel C. Caballero 2, Wanpracha Chaovalitwongse 3 and S. Lahari Putrevu 1

1Department of Computer Science, 2Department of Biological Sciences, University of Illinois at Chicago, Chicago, IL 60607 and 3Department of Industrial and Systems Engineering, Rutgers University, Piscataway, NJ 08854

*To whom correspondence should be addressed.


  Abstract

Reconstruction of sibling relationships from genetic data is an important component of many biological applications. In particular, the growing application of molecular markers (microsatellites) to study wild populations of plant and animals has created the need for new computational methods of establishing pedigree relationships, such as sibgroups, among individuals in these populations. Most current methods for sibship reconstruction from microsatellite data use statistical and heuristic techniques that rely on a priori knowledge about various parameter distributions. Moreover, these methods are designed for data with large number of sampled loci and small family groups, both of which typically do not hold for wild populations. We present a deterministic technique that parsimoniously reconstructs sibling groups using only Mendelian laws of inheritance. We validate our approach using both simulated and real biological data and compare it to other methods. Our method is highly accurate on real data and compares favorably with other methods on simulated data with few loci and large family groups. It is the only method that does not rely on a priori knowledge about the population under study. Thus, our method is particularly appropriate for reconstructing sibling groups in wild populations.

Contact: tanyabw{at}uic.edu


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