Genomic Ancestry Inference of Admixed Population by Identifying Approximate Boundaries of Ancestry Change

Document Type : Original Article

Authors

1 Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran

2 Department of Molecular and Cell Biology, Faculty of Science University of Mazandaran, Babolsar, Iran

3 School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW), Sydney, Australia

4 UNSW Data Science Hub, University of New South Wales (UNSW), Sydney, Australia

Abstract

Admixture is a common phenomenon in human populations, resulting from the mating of individuals from two or more previously isolated populations. This can lead to the formation of mosaic DNA segments, with each segment originating from a different ancestral population. Local ancestry inference methods are used to identify the ancestry of each segment, which can provide insights into the history of admixture in a population. Many local ancestry inference (LAI) methods require the determination of various parameters that may be difficult to obtain, which can hamper using LAI methods. In this paper, we present a novel method for identifying approximate boundaries of ancestry change (IABAC) in admixed haplotypes and then determining the ancestry between boundaries. Unlike many LAI methods, our method does not rely on many statistical or biological parameters, therefore more robust to variations in admixture patterns. We evaluate our method on human data, and show that it is more accurate than existing methods for ancestry detection. Our results suggest that IABAC is a promising new method for identifying ancestry boundaries in admixed haplotypes. This method could be used to study the history of admixture in human populations, and to identify genetic variants that are associated with different ancestral populations.

Graphical Abstract

Genomic Ancestry Inference of Admixed Population by Identifying Approximate Boundaries of Ancestry Change

Keywords

Main Subjects


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