Error tolerant sibship reconstruction in wild populations.

Saad I Sheikh, Tanya Y Berger-Wolf, Mary V Ashley, Isabel C Caballero, Wanpracha Chaovalitwongse, Bhaskar DasGupta
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Abstract

Kinship analysis using genetic data is important for many biological applications, including many in conservation biology. Wide availability of microsatellites has boosted studies in wild populations that rely on the knowledge of kinship, particularly sibling relationships (sibship). While there exist many methods for reconstructing sibling relationships, almost none account for errors and mutations in microsatellite data, which are prevalent and affect the quality of reconstruction. We present an error-tolerant method for reconstructing sibling relationships based on the concept of consensus methods. We test our approach on both real and simulated data, with both pre-existing and introduced errors. Our method is highly accurate on almost all simulations, giving over 90% accuracy in most cases. Ours is the first method designed to tolerate errors while making no assumptions about the population or the sampling.

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野生种群的容错兄弟姐妹重建。
利用遗传数据进行亲缘关系分析对许多生物学应用都很重要,包括保护生物学中的许多应用。微型卫星的广泛使用促进了对依赖亲属关系,特别是兄弟姐妹关系的野生种群的研究。虽然有许多重建兄弟关系的方法,但几乎没有一种方法能考虑到微卫星数据中普遍存在的误差和突变,这些误差和突变影响了重建的质量。基于共识方法的概念,提出了一种重构兄弟关系的容错方法。我们在真实和模拟数据上测试了我们的方法,包括预先存在的和引入的错误。我们的方法在几乎所有的模拟中都非常准确,在大多数情况下准确率超过90%。我们的方法是第一个在不对总体或抽样做任何假设的情况下允许误差的方法。
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