The use of plasmodes as a supplement to simulations: A simple example evaluating individual admixture estimation methodologies

Vaughan, Laura K.; Divers, Jasmin; Padilla, Miguel A.; Redden, David T.; Tiwari, Hemant K.; Pomp, Daniel; Allison, David B.

doi:10.1016/j.csda.2008.02.032

Cited by 29 publications

(36 citation statements)

References 51 publications

(66 reference statements)

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“…Several articles (reviewed in Putman and Carbone ) have pointed out that the number of loci required for separating pure individuals from recent hybrids (F1, F2, backcrosses) is much higher than what is typically used in empirical studies (Fitzpatrick ; Vähä and Primmer ) and requires carefully designed sampling schemes including pure individuals (Vaughan et al. ). It is thus uncertain that the low level of nuclear introgression that goes with mitochondrial introgression in some of our simulations (

\overset{a}{true}

as low as 0.19–0.25) would be easily identified in all empirical studies where mito‐nuclear discordance have been reported.…”

Section: Discussionmentioning

confidence: 99%

A reassessment of explanations for discordant introgressions of mitochondrial and nuclear genomes

et al. 2017

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Hybridization is increasingly recognized as a significant evolutionary process, in particular because it can lead to introgression of genes from one species to another. A striking pattern of discordance in the amount of introgression between mitochondrial and nuclear markers exists such that substantial mitochondrial introgression is often found in combination with no or little nuclear introgression. Multiple mechanisms have been proposed to explain this discordance, including positive selection for introgressing mitochondrial variants, several types of sex-biases, drift, negative selection against introgression in the nuclear genome, and spatial expansion. Most of these hypotheses are verbal, and have not been quantitatively evaluated so far. We use individual-based, multilocus, computer simulations of secondary contact under a wide range of demographic and genetic scenarios to evaluate the ability of the different mechanisms to produce discordant introgression. Sex-biases and spatial expansions fail to produce substantial mito-nuclear discordance. Drift and nuclear selection can produce strong discordance, but only under a limited range of conditions. In contrast, selection on the mitochondrial genome produces strong discordance, particularly when dispersal rates are low. However, commonly used statistical tests have little power to detect this selection. Altogether, these results dismiss several popular hypotheses, and provide support for adaptive mitochondrial introgression.

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\overset{a}{true}

as low as 0.19–0.25) would be easily identified in all empirical studies where mito‐nuclear discordance have been reported.…”

Section: Discussionmentioning

confidence: 99%

A reassessment of explanations for discordant introgressions of mitochondrial and nuclear genomes

et al. 2017

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“…Vaughan et al. () examined an experimental cross of mice and found that 11 microsatellite loci were generally insufficient for correctly inferring admixture when individuals from the founding subpopulations were not included in the analysis. When a large proportion of individuals in the dataset are admixed, Pritchard et al.…”

Section: Population Structurementioning

confidence: 99%

“…The problem of too few loci can be particularly troublesome when inferring admixture. Vaughan et al (2009) examined an experimental cross of mice and found that 11 microsatellite loci were generally insufficient for correctly inferring admixture when individuals from the founding subpopulations were not included in the analysis. When a large proportion of individuals in the dataset are admixed, Pritchard et al (2000) observed that estimates of ancestry coefficients may only be reliable for a large number of loci.…”

Section: Weak Structurementioning

confidence: 99%

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Putman

Carbone

2014

Ecology and Evolution

316

252

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Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (FST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.

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“…As an alternative to simulation, Vaughan et al (Vaughan et al, 2009) suggested creating “plasmode” datasets. A plasmode is a real dataset that is created from natural processes but has some aspect of the data-generating model known, for example, a “spike-in” experiment in microarray analysis of gene expression where a known amount of genome transcript is added to each sample.…”

Section: Introductionmentioning

confidence: 99%

Plasmode simulation for the evaluation of pharmacoepidemiologic methods in complex healthcare databases

Franklin

Schneeweiß

Polinski

et al. 2014

Computational Statistics & Data Analysis

101

121

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Longitudinal healthcare claims databases are frequently used for studying the comparative safety and effectiveness of medications, but results from these studies may be biased due to residual confounding. It is unclear whether methods for confounding adjustment that have been shown to perform well in small, simple nonrandomized studies are applicable to the large, complex pharmacoepidemiologic studies created from secondary healthcare data. Ordinary simulation approaches for evaluating the performance of statistical methods do not capture important features of healthcare claims. A statistical framework for creating replicated simulation datasets from an empirical cohort study in electronic healthcare claims data is developed and validated. The approach relies on resampling from the observed covariate and exposure data without modification in all simulated datasets to preserve the associations among these variables. Repeated outcomes are simulated using a true treatment effect of the investigator's choice and the baseline hazard function estimated from the empirical data. As an example, this framework is applied to a study of high versus low-intensity statin use and cardiovascular outcomes. Simulated data is based on real data drawn from Medicare Parts A and B linked with a prescription drug insurance claims database maintained by Caremark. Properties of the data simulated using this framework are compared with the empirical data on which the simulations were based. In addition, the simulated datasets are used to compare variable selection strategies for confounder adjustmentvia the propensity score, including high-dimensional approaches that could not be evaluated with ordinary simulation methods. The simulated datasets are found to closely resemble the observed complex data structure but have the advantage of an investigator-specified exposure effect.

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The use of plasmodes as a supplement to simulations: A simple example evaluating individual admixture estimation methodologies

Cited by 29 publications

References 51 publications

A reassessment of explanations for discordant introgressions of mitochondrial and nuclear genomes

A reassessment of explanations for discordant introgressions of mitochondrial and nuclear genomes

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Plasmode simulation for the evaluation of pharmacoepidemiologic methods in complex healthcare databases

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