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Activity Number: 126 - SPEED: New Methods in Statistical Genomics and Genetics Part 1
Type: Contributed
Date/Time: Monday, July 29, 2019 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #307220 Presentation
Title: Comparing Methods for Familial Relationship Inference in Populations with Complex Demographic History
Author(s): Daniel Yorgov*
Companies: Purdue University Fort Wayne
Keywords: population structure; admixed populations; Latinos; sequence resolution; relationship inference; kinship

Estimating more distant familial relationships from dense genotype data is particularly challenging in samples from ethnically complex populations like recently admixed Latinos or African Americans. With the growing emphasis on such populations in genetic studies, producing relatedness or kinship coefficient estimates that are robust to different types of population structure is increasingly important. We evaluate existing approaches for inferring familial relatedness from dense genetic markers that can accommodate complex population structure. Starting from 1000 Genomes Phase 3 Latino samples we construct simulated Latino dataset with allele frequencies and linkage disequilibrium patterns similar to that of contemporary Latino populations after only one additional generation of random mating. The 3500 samples are with complex population structure, including recent admixture, distinct sub-populations, and distant but known familial-like relatedness. Several recent relationship inference methods are compared on this challenging dataset starting from the 25,235,037 markers with minor allele frequency of at least 0.01.

Authors who are presenting talks have a * after their name.

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