Inferring the ancestry of parents and grandparents from genetic data.
Inference of admixture proportions is a classical statistical problem in population genetics. Standard methods implicitly assume that both parents of an individual have the same admixture fraction. However, this is rarely the case in real data. In this paper we show that the distribution of admixtur...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2020-08-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1008065 |
| _version_ | 1818716771093315584 |
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| author | Jingwen Pei Yiming Zhang Rasmus Nielsen Yufeng Wu |
| author_facet | Jingwen Pei Yiming Zhang Rasmus Nielsen Yufeng Wu |
| author_sort | Jingwen Pei |
| collection | DOAJ |
| description | Inference of admixture proportions is a classical statistical problem in population genetics. Standard methods implicitly assume that both parents of an individual have the same admixture fraction. However, this is rarely the case in real data. In this paper we show that the distribution of admixture tract lengths in a genome contains information about the admixture proportions of the ancestors of an individual. We develop a Hidden Markov Model (HMM) framework for estimating the admixture proportions of the immediate ancestors of an individual, i.e. a type of decomposition of an individual's admixture proportions into further subsets of ancestral proportions in the ancestors. Based on a genealogical model for admixture tracts, we develop an efficient algorithm for computing the sampling probability of the genome from a single individual, as a function of the admixture proportions of the ancestors of this individual. This allows us to perform probabilistic inference of admixture proportions of ancestors only using the genome of an extant individual. We perform extensive simulations to quantify the error in the estimation of ancestral admixture proportions under various conditions. To illustrate the utility of the method, we apply it to real genetic data. |
| first_indexed | 2024-12-17T19:24:33Z |
| format | Article |
| id | doaj.art-764401046d504658b19e717cb11d9c4d |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-17T19:24:33Z |
| publishDate | 2020-08-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-764401046d504658b19e717cb11d9c4d2022-12-21T21:35:25ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582020-08-01168e100806510.1371/journal.pcbi.1008065Inferring the ancestry of parents and grandparents from genetic data.Jingwen PeiYiming ZhangRasmus NielsenYufeng WuInference of admixture proportions is a classical statistical problem in population genetics. Standard methods implicitly assume that both parents of an individual have the same admixture fraction. However, this is rarely the case in real data. In this paper we show that the distribution of admixture tract lengths in a genome contains information about the admixture proportions of the ancestors of an individual. We develop a Hidden Markov Model (HMM) framework for estimating the admixture proportions of the immediate ancestors of an individual, i.e. a type of decomposition of an individual's admixture proportions into further subsets of ancestral proportions in the ancestors. Based on a genealogical model for admixture tracts, we develop an efficient algorithm for computing the sampling probability of the genome from a single individual, as a function of the admixture proportions of the ancestors of this individual. This allows us to perform probabilistic inference of admixture proportions of ancestors only using the genome of an extant individual. We perform extensive simulations to quantify the error in the estimation of ancestral admixture proportions under various conditions. To illustrate the utility of the method, we apply it to real genetic data.https://doi.org/10.1371/journal.pcbi.1008065 |
| spellingShingle | Jingwen Pei Yiming Zhang Rasmus Nielsen Yufeng Wu Inferring the ancestry of parents and grandparents from genetic data. PLoS Computational Biology |
| title | Inferring the ancestry of parents and grandparents from genetic data. |
| title_full | Inferring the ancestry of parents and grandparents from genetic data. |
| title_fullStr | Inferring the ancestry of parents and grandparents from genetic data. |
| title_full_unstemmed | Inferring the ancestry of parents and grandparents from genetic data. |
| title_short | Inferring the ancestry of parents and grandparents from genetic data. |
| title_sort | inferring the ancestry of parents and grandparents from genetic data |
| url | https://doi.org/10.1371/journal.pcbi.1008065 |
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