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Abstract:
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Single nucleotide polymorphisms (SNPs) are molecular markers abundant in the genomes of most organisms. Because SNPs can be genotyped in a high-throughput setting with minimal genotyping error, they may be quite useful for parentage inference in large populations of intensively monitored or managed species. I review recent developments in importance sampling methods, allowing the calculation of false positive rates in large-scale, likelihood-based, parentage inference. Then, I present algorithms that combine exclusion and likelihood-based methods for performing parentage inference in very large problems involving billions of potential parent pairs and many thousands of offspring.
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