Utilizing Graph Theory to Select the Largest Set of Unrelated Individuals for Genetic Analysis

Staples, Jeffrey; Nickerson, Deborah A.; Below, Jennifer E.

doi:10.1002/gepi.21684

Cited by 48 publications

(50 citation statements)

References 23 publications

(31 reference statements)

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“…37 An individual is only added to a family network if the sample is related to at least one other person in the network given a user-defined minimum coefficient of relatedness. For example, 0.1875, the midpoint between the mean expected IBD proportion for second-and third-degree relatives, is a threshold that will capture connections between most seconddegree relatives or closer.…”

Section: Family-network Identificationmentioning

confidence: 99%

“…37 Our method utilizes the power of SNP arrays or next-generation sequence data to evaluate genome-wide identity-bydescent (IBD) estimates generated by programs such as PLINK 14 or KING (Kinship-Based Inference for Genomewide Association Studies). 16 Our method assigns relationships by using the expected mean and variance for each relationship class and leverages all pairwise relationships within a family (as well as genetically determined sex) to reconstruct the possible pedigree structures in a manner consistent with the observed pairwise sharing.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

PRIMUS: Rapid Reconstruction of Pedigrees from Genome-wide Estimates of Identity by Descent

Staples

Qiao

Cho

et al. 2014

The American Journal of Human Genetics

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131

151

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Understanding and correctly utilizing relatedness among samples is essential for genetic analysis; however, managing sample records and pedigrees can often be error prone and incomplete. Data sets ascertained by random sampling often harbor cryptic relatedness that can be leveraged in genetic analyses for maximizing power. We have developed a method that uses genome-wide estimates of pairwise identity by descent to identify families and quickly reconstruct and score all possible pedigrees that fit the genetic data by using up to third-degree relatives, and we have included it in the software package PRIMUS (Pedigree Reconstruction and Identification of the Maximally Unrelated Set). Here, we validate its performance on simulated, clinical, and HapMap pedigrees. Among these samples, we demonstrate that PRIMUS can verify reported pedigree structures and identify cryptic relationships. Finally, we show that PRIMUS reconstructed pedigrees, all of which were previously unknown, for 203 families from a cohort collected in Starr County, TX (1,890 samples).

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Section: Family-network Identificationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

PRIMUS: Rapid Reconstruction of Pedigrees from Genome-wide Estimates of Identity by Descent

Staples

Qiao

Cho

et al. 2014

The American Journal of Human Genetics

Self Cite

131

151

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“…We next used the PRIMUS suite of analytical tools to evaluate and perform quality controls on this initial data (Staples et al 2013(Staples et al , 2014. The algorithms in PRIMUS that estimate allele sharing were used to infer genealogical relatedness among all pairs.…”

Section: Evaluation Of Initial Data Set Using Primusmentioning

confidence: 99%

The population genomics of rhesus macaques (Macaca mulatta) based on whole-genome sequences

et al. 2016

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Rhesus macaques (Macaca mulatta) are the most widely used nonhuman primate in biomedical research, have the largest natural geographic distribution of any nonhuman primate, and have been the focus of much evolutionary and behavioral investigation. Consequently, rhesus macaques are one of the most thoroughly studied nonhuman primate species. However, little is known about genome-wide genetic variation in this species. A detailed understanding of extant genomic variation among rhesus macaques has implications for the use of this species as a model for studies of human health and disease, as well as for evolutionary population genomics. Whole-genome sequencing analysis of 133 rhesus macaques revealed more than 43.7 million single-nucleotide variants, including thousands predicted to alter protein sequences, transcript splicing, and transcription factor binding sites. Rhesus macaques exhibit 2.5-fold higher overall nucleotide diversity and slightly elevated putative functional variation compared with humans. This functional variation in macaques provides opportunities for analyses of coding and noncoding variation, and its cellular consequences. Despite modestly higher levels of nonsynonymous variation in the macaques, the estimated distribution of fitness effects and the ratio of nonsynonymous to synonymous variants suggest that purifying selection has had stronger effects in rhesus macaques than in humans. Demographic reconstructions indicate this species has experienced a consistently large but fluctuating population size. Overall, the results presented here provide new insights into the population genomics of nonhuman primates and expand genomic information directly relevant to primate models of human disease.

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“…Moreover, it is often important to be able to verify stated pedigree relationships from the observed data and to check for errors. For example, the results of an association analysis on a case-control study could be seriously biased if some cases and controls were related and linkage analyses are sensitive to undeclared relationships between pedigree founders [11,23,51,56]. More recently, family-based designs have been recommended for association studies concerned with parent-of-origin effects and the control of population stratification [40].…”

Section: Introductionmentioning

confidence: 99%

On the use of dense SNP marker data for the identification of distant relative pairs

Sun

Jobling

Taliun

et al. 2016

Theoretical Population Biology

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There has been recent interest in the exploitation of readily available dense genome scan marker data for the identification of relatives. However, there are conflicting findings on how informative these data are in practical situations and, in particular, sets of thinned markers are often used with no concrete justification for the chosen spacing. We explore the potential usefulness of dense single nucleotide polymorphism (SNP) arrays for this application with a focus on inferring distant relative pairs. We distinguish between relationship estimation, as defined by a pedigree connecting the two individuals of interest, and estimation of general relatedness as would be provided by a kinship coefficient or a coefficient of relatedness. Since our primary interest is in the former case, we adopt a pedigree likelihood approach. We consider the effect of additional SNPs and data on an additional typed relative, together with choice of that relative, on relationship inference. We also consider the effect of linkage disequilibrium. When overall relatedness, rather than the specific relationship, would suffice, * Theoretical Population Biology. In Press. http://dx.doi.org/10.1016/j.tpb.2015.10 † Corresponding author. E-mail address: Nuala.Sheehan@leicester.ac.uk 1 we propose an approximate approach that is easy to implement and appears to compete well with a popular moment-based estimator and a recent maximum likelihood approach based on chromosomal sharing. We conclude that denser marker data are more informative for distant relatives. However, linkage disequilibrium cannot be ignored and will be the main limiting factor for applications to real data.

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Utilizing Graph Theory to Select the Largest Set of Unrelated Individuals for Genetic Analysis

Cited by 48 publications

References 23 publications

PRIMUS: Rapid Reconstruction of Pedigrees from Genome-wide Estimates of Identity by Descent

PRIMUS: Rapid Reconstruction of Pedigrees from Genome-wide Estimates of Identity by Descent

The population genomics of rhesus macaques (Macaca mulatta) based on whole-genome sequences

On the use of dense SNP marker data for the identification of distant relative pairs

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