SPEDE-sampler: An R Shiny application to assess how methodological choices and taxon sampling can affect Generalized Mixed Yule Coalescent output and interpretation.
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ABSTRACT:
SUBMITTER: van Steenderen CJM
PROVIDER: S-EPMC9306842 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:DNA barcoding-type studies assemble single-locus data from large samples of individuals and species, and have provided new kinds of data for evolutionary surveys of diversity. An important goal of many such studies is to delimit evolutionarily significant species units, especially in biodiversity surveys from environmental DNA samples. The Generalized Mixed Yule Coalescent (GMYC) method is a likelihood method for delimiting species by fitting within- and between-species branching models to reconstructed gene trees. Although the method has been widely used, it has not previously been described in detail or evaluated fully against simulations of alternative scenarios of true patterns of population variation and divergence between species. Here, we present important reformulations to the GMYC method as originally specified, and demonstrate its robustness to a range of departures from its simplifying assumptions. The main factor affecting the accuracy of delimitation is the mean population size of species relative to divergence times between them. Other departures from the model assumptions, such as varying population sizes among species, alternative scenarios for speciation and extinction, and population growth or subdivision within species, have relatively smaller effects. Our simulations demonstrate that support measures derived from the likelihood function provide a robust indication of when the model performs well and when it leads to inaccurate delimitations. Finally, the so-called single-threshold version of the method outperforms the multiple-threshold version of the method on simulated data: we argue that this might represent a fundamental limit due to the nature of evidence used to delimit species in this approach. Together with other studies comparing its performance relative to other methods, our findings support the robustness of GMYC as a tool for delimiting species when only single-locus information is available.
| S-EPMC3739884 | biostudies-other
Project description:Assessing the geographic structure of populations has relied heavily on Sewell Wright's F-statistics and their numerous analogues for many decades. However, it is well appreciated that, due to their nonlinear relationship with gene flow, F-statistics frequently fail to reject the null model of panmixia in species with relatively high levels of gene flow and large population sizes. Coalescent genealogy samplers instead allow a model-selection approach to the characterization of population structure, thereby providing the opportunity for stronger inference. Here, we validate the use of coalescent samplers in a high gene flow context using simulations of a stepping-stone model. In an example case study, we then re-analyze genetic datasets from 41 marine species sampled from throughout the Hawaiian archipelago using coalescent model selection. Due to the archipelago's linear nature, it is expected that most species will conform to some sort of stepping-stone model (leading to an expected pattern of isolation by distance), but F-statistics have only supported this inference in ~10% of these datasets. Our simulation analysis shows that a coalescent sampler can make a correct inference of stepping-stone gene flow in nearly 100% of cases where gene flow is ?100 migrants per generation (equivalent to F ST = 0.002), while F-statistics had mixed results. Our re-analysis of empirical datasets found that nearly 70% of datasets with an unambiguous result fit a stepping-stone model with varying population sizes and rates of gene flow, although 37% of datasets yielded ambiguous results. Together, our results demonstrate that coalescent samplers hold great promise for detecting weak but meaningful population structure, and defining appropriate management units.
| S-EPMC6346657 | biostudies-literature
Project description:Worldwide, crop production is intrinsically intertwined with biological, environmental and economic systems, all of which involve complex, inter-related and spatially-sensitive phenomena. Thus knowing the location of agriculture matters much for a host of reasons. There are several widely cited attempts to model the spatial pattern of crop production worldwide, not least by pixilating crop production statistics originally reported on an areal (administrative boundary) basis. However, these modeled measures have had little scrutiny regarding the robustness of their results to alternative data and modeling choices. Our research casts a critical eye over the nature and empirical plausibility of these types of datasets. To do so, we determine the sensitivity of the 2005 variant of the spatial production allocation model data series (SPAM2005) to eight methodological-cum-data choices in nine agriculturally-large and developmentally-variable countries: Brazil, China, Ethiopia, France, India, Indonesia, Nigeria, Turkey and the United States. We compare the original published estimates with those obtained from a series of robustness tests using various aggregations of the pixelized spatial production indicators (specifically, commodity-specific harvested area, production quantity and yield). Spatial similarity is empirically assessed using a pixel-level spatial similarity index (SSI). We find that the SPAM2005 estimates are most dependent on the degree of disaggregation of the underlying national and subnational production statistics. The results are also somewhat sensitive to the use of a simple spatial allocation method based solely on cropland proportions versus a cross-entropy allocation method, as well as the set of crops or crop aggregates being modeled, and are least sensitive to the inclusion of crude economic elements. Finally, we assess the spatial concordance between the SPAM2005 estimates of the area harvested of major crops in the United States and pixelated measures derived from remote-sensed data.
| S-EPMC6380596 | biostudies-literature
Project description:SummaryDIAgui is an R package to simplify the processing of the report file from the DIA-NN software thanks to a Shiny application. It returns the quantification of either the precursors, the peptides, the proteins, or the genes thanks to the MaxLFQ algorithm. In addition, the latest version provides the Top3 and iBAQ quantification and the number of peptides used for the quantification. In the end, DIAgui produces ready-to-interpret files from the results of DIA mass spectrometry analysis and provides visualization and statistical tools that can be used in a user-friendly way.Availability and implementationCode and documentation are available on GitHub at https://github.com/marseille-proteomique/DIAgui. The package is written in R and also uses C++ code. A vignette shows its use in an R command line workflow.
| S-EPMC10799745 | biostudies-literature
Project description:BACKGROUND: Species are considered the fundamental unit in many ecological and evolutionary analyses, yet accurate, complete, accessible taxonomic frameworks with which to identify them are often unavailable to researchers. In such cases DNA sequence-based species delimitation has been proposed as a means of estimating species boundaries for further analysis. Several methods have been proposed to accomplish this. Here we present a Bayesian implementation of an evolutionary model-based method, the general mixed Yule-coalescent model (GMYC). Our implementation integrates over the parameters of the model and uncertainty in phylogenetic relationships using the output of widely available phylogenetic models and Markov-Chain Monte Carlo (MCMC) simulation in order to produce marginal probabilities of species identities. RESULTS: We conducted simulations testing the effects of species evolutionary history, levels of intraspecific sampling and number of nucleotides sequenced. We also re-analyze the dataset used to introduce the original GMYC model. We found that the model results are improved with addition of DNA sequence and increased sampling, although these improvements have limits. The most important factor in the success of the model is the underlying phylogenetic history of the species under consideration. Recent and rapid divergences result in higher amounts of uncertainty in the model and eventually cause the model to fail to accurately assess uncertainty in species limits. CONCLUSION: Our results suggest that the GMYC model can be useful under a wide variety of circumstances, particularly in cases where divergences are deeper, or taxon sampling is incomplete, as in many studies of ecological communities, but that, in accordance with expectations from coalescent theory, rapid, recent radiations may yield inaccurate results. Our implementation differs from existing ones in two ways: it allows for the accounting for important sources of uncertainty in the model (phylogenetic and in parameters specific to the model) and in the specification of informative prior distributions that can increase the precision of the model. We have incorporated this model into a user-friendly R package available on the authors' websites.
| S-EPMC3503838 | biostudies-literature
Project description:Prospects for a comprehensive inventory of global biodiversity would be greatly improved by automating methods of species delimitation. The general mixed Yule-coalescent (GMYC) was recently proposed as a potential means of increasing the rate of biodiversity exploration. We tested this method with simulated data and applied it to a group of poorly known bats (Hipposideros) from the Philippines. We then used echolocation call characteristics to evaluate the plausibility of species boundaries suggested by GMYC. In our simulations, GMYC performed relatively well (errors in estimated species diversity less than 25%) when the product of the haploid effective population size (N(e)) and speciation rate (SR; per lineage per million years) was less than or equal to 10(5), while interspecific variation in N(e) was twofold or less. However, at higher but also biologically relevant values of N(e) × SR and when N(e) varied tenfold among species, performance was very poor. GMYC analyses of mitochondrial DNA sequences from Philippine Hipposideros suggest actual diversity may be approximately twice the current estimate, and available echolocation call data are mostly consistent with GMYC delimitations. In conclusion, we consider the GMYC model useful under some conditions, but additional information on N(e), SR and/or corroboration from independent character data are needed to allow meaningful interpretation of results.
| S-EPMC3415896 | biostudies-literature
Project description:Clinical evidence available for the assessment of medical devices (MDs) is frequently insufficient. New MDs should be subjected to high quality clinical studies to demonstrate their benefit to patients. The randomized controlled trial (RCT) is the study design reaching the highest level of evidence in order to demonstrate the efficacy of a new MD. However, the clinical context of some MDs makes it difficult to carry out a conventional RCT. The objectives of this review are to present problems related to conducting conventional RCTs and to identify other experimental designs, their limitations, and their applications. A systematic literature search was conducted for the period January 2000 to July 2012 by searching medical bibliographic databases. Problems related to conducting conventional RCTs of MDs were identified: timing the assessment, eligible population and recruitment, acceptability, blinding, choice of comparator group, and learning curve. Other types of experimental designs have been described. Zelen's design trials and randomized consent design trials facilitate the recruitment of patients, but can cause ethical problems to arise. Expertise-based RCTs involve randomization to a team that specializes in a given intervention. Sometimes, the feasibility of an expertise-based randomized trial may be greater than that of a conventional trial. Cross-over trials reduce the number of patients, but are not applicable when a learning curve is required. Sequential trials have the advantage of allowing a trial to be stopped early depending on the results of first inclusions, but they require an independent committee. Bayesian methods combine existing information with information from the ongoing trial. These methods are particularly useful in situations where the number of subjects is small. The disadvantage is the risk of including erroneous prior information. Other types of experimental designs exist when conventional trials cannot always be applied to the clinical development of MDs.
| S-EPMC4181748 | biostudies-other
Project description:BackgroundFoodborne and zoonotic diseases such as brucellosis present many challenges to public health and economic welfare. Increasingly, researchers and public health institutes use disability-adjusted life years (DALYs) to generate a comprehensive comparison of the population health impact of these conditions. DALYs calculations, however, entail a number of methodological choices and assumptions, with data gaps and uncertainties to accommodate. Thisreview identifies existing brucellosis burden of disease studies and analyzes their methodological choices, assumptions, and uncertainties. It supports the Global Burden of Animal Diseases programme in the development of a systematic methodology to describe the impact of animal diseases on society, including human health.Methods/principal findingsA systematic search for brucellosis burden of disease calculations was conducted in pre-selected international and grey literature databases. Using a standardized reporting framework, we evaluated each estimate on a variety of key methodological assumptions necessary to compute a DALY. Fourteen studies satisfied the inclusion criteria (human brucellosis and quantification of DALYs). One study reported estimates at the global level, the rest were national or subnational assessments. Data regarding different methodological choices were extracted, including detailed assessments of the adopted disease models. Most studies retrieved brucellosis epidemiological data from administrative registries. Incidence data were often estimated on the basis of laboratory-confirmed tests. Not all studies included mortality estimates (Years of Life Lost) in their assessments due to lack of data or the assumption that brucellosis is not a fatal disease. Only two studies used a model with variable health states and corresponding disability weights. The rest used a simplified singular health state approach. Wide variation was seen in the duration chosen for brucellosis, ranging from 2 weeks to 4.5 years, irrespective of the whether a chronic state was included.ConclusionAvailable brucellosis burden of disease assessments vary widely in their methodology and assumptions. Further research is needed to better characterize the clinical course of brucellosis and to estimate case-fatality rates. Additionally, reporting of methodological choices should be improved to enhance transparency and comparability of estimates. These steps will increase the value of these estimates for policy makers.
| S-EPMC9794075 | biostudies-literature
Project description:ObjectiveDisrupting thalamocortical activity patterns has proven to be a promising approach to stop generalized spike-and-wave discharges (GSWDs) characteristic of absence seizures. Here, we investigated to what extent modulation of neuronal firing in cerebellar nuclei (CN), which are anatomically in an advantageous position to disrupt cortical oscillations through their innervation of a wide variety of thalamic nuclei, is effective in controlling absence seizures.MethodsTwo unrelated mouse models of generalized absence seizures were used: the natural mutant tottering, which is characterized by a missense mutation in Cacna1a, and inbred C3H/HeOuJ. While simultaneously recording single CN neuron activity and electrocorticogram in awake animals, we investigated to what extent pharmacologically increased or decreased CN neuron activity could modulate GSWD occurrence as well as short-lasting, on-demand CN stimulation could disrupt epileptic seizures.ResultsWe found that a subset of CN neurons show phase-locked oscillatory firing during GSWDs and that manipulating this activity modulates GSWD occurrence. Inhibiting CN neuron action potential firing by local application of the γ-aminobutyric acid type A (GABA-A) agonist muscimol increased GSWD occurrence up to 37-fold, whereas increasing the frequency and regularity of CN neuron firing with the use of GABA-A antagonist gabazine decimated its occurrence. A single short-lasting (30-300 milliseconds) optogenetic stimulation of CN neuron activity abruptly stopped GSWDs, even when applied unilaterally. Using a closed-loop system, GSWDs were detected and stopped within 500 milliseconds.InterpretationCN neurons are potent modulators of pathological oscillations in thalamocortical network activity during absence seizures, and their potential therapeutic benefit for controlling other types of generalized epilepsies should be evaluated.
| S-EPMC5008217 | biostudies-literature
Project description:Aquatic larvae of many Rhithrogena mayflies (Ephemeroptera) inhabit sensitive Alpine environments. A number of species are on the IUCN Red List and many recognized species have restricted distributions and are of conservation interest. Despite their ecological and conservation importance, ambiguous morphological differences among closely related species suggest that the current taxonomy may not accurately reflect the evolutionary diversity of the group. Here we examined the species status of nearly 50% of European Rhithrogena diversity using a widespread sampling scheme of Alpine species that included 22 type localities, general mixed Yule-coalescent (GMYC) model analysis of one standard mtDNA marker and one newly developed nDNA marker, and morphological identification where possible. Using sequences from 533 individuals from 144 sampling localities, we observed significant clustering of the mitochondrial (cox1) marker into 31 GMYC species. Twenty-one of these could be identified based on the presence of topotypes (expertly identified specimens from the species' type locality) or unambiguous morphology. These results strongly suggest the presence of both cryptic diversity and taxonomic oversplitting in Rhithrogena. Significant clustering was not detected with protein-coding nuclear PEPCK, although nine GMYC species were congruent with well supported terminal clusters of nDNA. Lack of greater congruence in the two data sets may be the result of incomplete sorting of ancestral polymorphism. Bayesian phylogenetic analyses of both gene regions recovered four of the six recognized Rhithrogena species groups in our samples as monophyletic. Future development of more nuclear markers would facilitate multi-locus analysis of unresolved, closely related species pairs. The DNA taxonomy developed here lays the groundwork for a future revision of the important but cryptic Rhithrogena genus in Europe.
| S-EPMC3096624 | biostudies-other