IPED: Inheritance Path-based Pedigree Reconstruction Algorithm Using Genotype Data

He, Dan; Wang, Zhanyong; Han, Buhm; Parida, Laxmi; Eskin, Eleazar

doi:10.1089/cmb.2013.0080

Cited by 11 publications

(18 citation statements)

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“…But they are either limited in the number of markers that can be 33 analyzed [20,25]; do not support polygamous pedigrees [23,24]; assume a complete 34 sample (i.e. every member in the pedigree is sampled) [21,22,26]; or assume all sampled 35 individuals belong to a single generation [23,24]. The state-of-the-art method, 36 PRIMUS [27], is the most flexible of the existing methods; it accommodates missing 37 data and is able to infer multi-generational, polygamous pedigrees.…”

Section: Introductionmentioning

confidence: 99%

“…The parentage inference methods for two generations find the 30 best parent-offspring combinations from a set of offspring and candidate parents [16][17][18]. 31 Several methods that can support more than two generations have been 32 developed [19][20][21][22][23][24][25]. But they are either limited in the number of markers that can be 33 analyzed [20,25]; do not support polygamous pedigrees [23,24]; assume a complete 34 sample (i.e.…”

Section: Introductionmentioning

confidence: 99%

“…31 Several methods that can support more than two generations have been 32 developed [19][20][21][22][23][24][25]. But they are either limited in the number of markers that can be 33 analyzed [20,25]; do not support polygamous pedigrees [23,24]; assume a complete 34 sample (i.e. every member in the pedigree is sampled) [21,22,26]; or assume all sampled 35 individuals belong to a single generation [23,24].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Composite Likelihood Method for Inferring Local Pedigrees

Nielsen

2017

Preprint

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Pedigrees contain information about the genealogical relationships among individuals and are of fundamental importance in many areas of genetic studies. However, pedigrees are often unknown and must be inferred from genetic data. Despite the importance of pedigree inference, existing methods are limited to inferring only close relationships or analyzing a small number of individuals or loci. We present a simulated annealing method for estimating pedigrees in large samples of otherwise seemingly unrelated individuals using genome-wide SNP data. The method supports complex pedigree structures such as polygamous families, multi-generational families, and pedigrees in which many of the member individuals are missing. Computational speed is greatly enhanced by the use of a composite likelihood function which approximates the full likelihood. We validate our method on simulated data and show that it can infer distant relatives more accurately than existing methods. Furthermore, we illustrate the utility of the method on a sample of Greenlandic Inuit. Author SummaryPedigrees contain information about the genealogical relationships among individuals. This information can be used in many areas of genetic studies such as disease association studies, conservation efforts, and learning about the demographic history and social structure of a population. Despite their importance, pedigrees are often unknown and must be estimated from genetic information. However, pedigree inference remains a difficult problem due to the high cost of likelihood computation and the enormous number of possible pedigrees we must consider. These difficulties limit existing methods in their ability to infer pedigrees when the sample size or the number of markers is large, or when the sample contains only distant relatives. In this report, we present a method that circumvents these computational barriers in order to infer pedigrees of complex structure for a large number of individuals. From our simulation studies, we found that our method can infer distant relatives much more accurately than existing methods. Our ability to infer pedigrees with a greater accuracy opens up possibilities for developing or improving pedigree-based methods in many areas research such as linkage analysis, demographic inference, association studies, and conservation.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Composite Likelihood Method for Inferring Local Pedigrees

Nielsen

2017

Preprint

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“…The problem studied here is different from pedigree reconstruction, where genetic information is used to reconstruct (previously unknown) family relationships. See [20,21,23,26,39,47] for discussions of pedigree reconstruction.…”

Section: Introductionmentioning

confidence: 99%

Ancestral Haplotype Reconstruction in Endogamous Populations using Identity-By-Descent

Finke

Kourakos

Brown

et al. 2020

Preprint

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In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies or compute polygenic risk scores for the reconstructed individuals.The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between finding a source for each IBD segment and assembling IBD segments placed within each ancestral individual. After each iteration we perform conflict resolution to remove IBD segments that do not align with wellreconstructed haplotypes and upweight the probability that these segments should be placed in other individuals. We repeat this process until we are no longer successfully reconstructing additional ancestral haplotypes. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs.We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to the United States from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 10 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 230 ancestral individuals per autosome. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families.

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“…To address this problem, many methods have been developed to estimate pedigrees from genetic data. Existing methods fall broadly into two categories: those that estimate pairwise relationships only (Thompson 1975;McPeek and Sun 2000;Smith et al 2001;Sun et al 2001;Milligan 2003;Sun and Dimitromanolakis 2014) and those that aim to reconstruct the entire pedigree (Thomas and Hill 2000;Almudevar 2003;Wang 2004;Hadfield et al 2006;Gasbarra et al 2007;Cowell 2009;Riester et al 2009;Wang and Santure 2009;Kirkpatrick et al 2011;Almudevar and Anderson 2012;Wang 2012;Cowell 2013;He et al 2013;Cussens et al 2013;Staples et al 2014;Anderson and Ng 2016;Staples et al 2016;Ko and Nielsen 2017;Ramstetter et al 2018). Although pairwise methods are computationally fast, estimated pairwise relationships do not necessarily translate to the correct pedigree, as piecing together pairwise relationships may not produce a valid pedigree.…”

Section: Introductionmentioning

confidence: 99%

Joint Estimation of Pedigrees and Effective Population Size Using Markov Chain Monte Carlo

Nielsen

2018

Preprint

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Pedigrees provide the genealogical relationships among individuals at a fine resolution and serve an important function in many areas of genetic studies. One such use of pedigree information is in the estimation of the short-term effective population size (N e ), which is of great relevance in fields such as conservation genetics. Despite the usefulness of pedigrees, however, they are often an unknown parameter and must be inferred from genetic data. In this study, we present a Bayesian method to jointly estimate pedigrees and N e from genetic markers using Markov Chain Monte Carlo. Our method supports analysis of a large number of markers and individuals with the use of a composite likelihood, which significantly increases computational efficiency. We show on simulated data that our method is able to jointly estimate relationships up to first cousins and N e with high accuracy. We also apply the method on a real dataset of house sparrows to reconstruct their previously unreported pedigree.

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IPED: Inheritance Path-based Pedigree Reconstruction Algorithm Using Genotype Data

Cited by 11 publications

References 18 publications

Composite Likelihood Method for Inferring Local Pedigrees

Composite Likelihood Method for Inferring Local Pedigrees

Ancestral Haplotype Reconstruction in Endogamous Populations using Identity-By-Descent

Joint Estimation of Pedigrees and Effective Population Size Using Markov Chain Monte Carlo

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