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17 results for “Neutrality Test”
Simulated Neutral Landscape Models and Scaling Results for Testing of Multi-Dimensional Grid-Point Scaling Algorithm
<p>The data package contains (1) simulations of neutral landscape models of categorical data for benchmark testing of scaling algorithms, and (2) scaling results for testing consistency and sensitivity of the newly developed Multi-Dimensional Grid-Point (MDGP) scaling algorithm.</p> <p>Neutral landscapes were generated using the "nlmpy" python module. The MDGP scaling algorithm and the test framework were implemented in R (https://github.com/gannd/landscapeScaling). </p>
Validation of a SARS-CoV-2 surrogate neutralization test detecting neutralizing antibodies against the major variants of concern
<p>SARS-CoV-2 infection and/or vaccination elicit a broad range of neutralizing antibody responses against the different variants of concern (VOC). We established a new variant-adapted surrogate neutralization test (sVNT) and assessed the neutralization activity against the ancestral B.1 (WT) as well as VOC Delta, Omicron BA.1, BA.2 and BA.5. Performances were compared to the reference virus neutralization test (VNT) against the respective VOC using three different cohorts collected during the COVID waves. Pre-COVID samples confirmed 100% specificity of the sVNT. Correlation analyses showed moderate to strong correlation for Omicron sub-variants (Spearman’s r=0.7081 for BA.1, r=0.7205 for BA.2 and r=0.6042 for BA.5), and for WT (r=0.8458) and Delta-sVNT (r=0.8158), respectively. Comparison of the WT-sVNT performance with two CE-IVD commercial kits “Icosagen SARS-CoV-2 Neutralizing Antibody ELISA kit” and “Genscript cPass kit” revealed an overall good correlation ranging from 0.8673 to -0.8773 and a midway profile between both commercial kits with 87.76% sensitivity and 90.48% clinical specificity resulting in a Youden Index of 78.24. This midway trend was further confirmed on 100 double-vaccinated individuals. The BA.2-sVNT performance was similar to that of the Genscript test. Finally, sVNT ability to assess neutralizing antibodies against Omicron BA.5 was validated on a double-vaccinated cohort (n=100) and an Omicron-breakthrough infection cohort (n=91). Correlation analysis revealed a strong association (r=0.8583) between BA.5-sVNT and VNT. Accurate classification was confirmed by receiving operating characteristic (ROC) analysis reporting an area under the curve (AUC) of 0.9543. In conclusion, the sVNT allows for efficient prediction of immune protection against the various VOCs.</p>
A test of island biogeographic theory applied to estimates of gene flow in a Fijian bird is largely consistent with neutral expectations
<p>Islands were key to the development of allopatric speciation theory because they are a natural laboratory of repeated barriers to gene flow caused by open water gaps. Despite their proclivity for promoting divergence, little empirical work has quantified the extent of gene flow among island populations. Following classic island biogeographic theory, two metrics of interest are relative island size and distance. Fiji presents an ideal system for studying these dynamics, with four main islands that form two large-small pairs. We sequenced thousands of ultraconserved elements (UCEs) of the Fiji bush-warbler<i> Horornis ruficapilla</i>, a passerine distributed on these four Fijian islands, and performed a demographic analysis to test hypotheses of the effects of island size and distance on rates of gene flow. Our demographic analysis inferred low levels of gene flow from each large island to its small counterpart and little or none in the opposite direction. The difference in the distance between these two island pairs manifested itself in lower levels of gene flow between more distant islands. Both findings are generally concordant with classic island biogeography. The amount of reduction in gene flow based on distance was consistent with predictions from island biogeographic equations, while the reduction from small to large islands was possibly greater than expected. These findings offer a hypothesis and framework to guide future study of inter-island gene flow in archipelagos as the study of island biogeography progresses into the genomic era.</p>
Data from: Screening test for neutralizing antibodies against yellow fever virus, based on a flavivirus pseudotype
Given the possibility of yellow fever virus reintroduction in epidemiologically receptive geographic areas, the risk of vaccine supply disruption is a serious issue. New strategies to reduce the doses of injected vaccines should be evaluated very carefully in terms of immunogenicity. The plaque reduction test for the determination of neutralizing antibodies (PRNT) is particularly time-consuming and requires the use of a confinement laboratory. We have developed a new test based on the use of a non-infectious pseudovirus (WN/YF17D). The presence of a reporter gene allows sensitive determination of neutralizing antibodies by flow cytometry. This WN/YF17D test was as sensitive as PRNT for the follow-up of yellow fever vaccinees. Both tests lacked specificity with sera from patients hospitalized for acute Dengue virus infection. Conversely, both assays were strictly negative in adults never exposed to flavivirus infection or vaccination, and in patients sampled some time after acute Dengue infection. This WN/YF17D test will be particularly useful for large epidemiological studies and for screening for neutralizing antibodies against yellow fever virus.
A test of island biogeographic theory applied to estimates of gene flow in a Fijian bird is largely consistent with neutral expectations
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Data from: Comparative tests of the species-genetic diversity correlation at neutral and non-neutral loci in four species of stream insect
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Data from: Generation of a neutral FST baseline for testing local adaptation on gill-raker number within and between European whitefish ecotypes in the Baltic Sea basin
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Data from: Screening test for neutralizing antibodies against yellow fever virus, based on a flavivirus pseudotype
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Data and Code for Publication "Testing the Utility of Dental Morphological Trait Combinations for Inferring Human Neutral Genetic Variation"
<p>Data and code for publication: H. Rathmann, H. Reyes-Centeno, Testing the utility of dental morphological trait combinations for inferring human neutral genetic variation. <em>Proc. Natl. Acad. Sci. U.S.A.</em> 117, 10769-10777 (2020). DOI: 10.1073/pnas.1914330117</p> <p>The repository contains:</p> <ul> <li>“R-code.txt”: R code for an exhaustive search algorithm testing the utility of dental morphological traits and trait combinations for inferring human neutral genetic variation.</li> <li>“dental trait frequencies.csv”: Data set with 27 dental morphological trait frequencies for 20 modern human populations worldwide used for analysis. Data from G. R. Scott, C. G. Turner, G. C. Townsend, M. Martinón-Torres, <em>The Anthropology of Modern Human Teeth</em> (Cambridge University Press, 2018). DOI: 10.1017/ 9781316795859</li> <li>“microsatellite loci mean sizes.csv”: Data set with 645 microsatellite mean allele sizes for 20 modern human populations worldwide used for analysis. Data from T. J. Pemberton, M. DeGiorgio, N. A. Rosenberg, Population structure in a comprehensive genomic data set on human microsatellite variation. <em>G3: Genes Genom. Genet.</em> 3, 891–907 (2013). DOI: 10.1534/g3.113.005728</li> <li>“utility estimates for 134217727 trait combinations.txt”: A large table with utility estimates for 27 dental morphological traits and all 134,217,700 possible trait combinations.</li> </ul> <p>Abbreviations for the 20 population names (rows) in “dental trait frequencies.csv” and “microsatellite loci mean sizes.csv” as follows:</p> <ul> <li>AUS = Australia</li> <li>CAS = Central Asia</li> <li>EAF = Eastern Africa</li> <li>EAS = East Asia</li> <li>EEU = Eastern Europe</li> <li>IND = India</li> <li>MAM = Mesoamerica</li> <li>MEL = Melanesia</li> <li>MIC = Micronesia</li> <li>NAF = North Africa</li> <li>NAM = North America</li> <li>NESI = Northeast Siberia</li> <li>NGU = New Guinea</li> <li>NWAM = Na-Dene</li> <li>POL = Polynesia</li> <li>SAM = South America</li> <li>SAN = San</li> <li>SEAS = Southeast Asia</li> <li>WEU = Western Europe</li> <li>WSAF = Sub-Saharan Africa</li> </ul> <p>Abbreviations for the 27 dental morphological trait names (columns) in “dental trait frequencies.csv” as follows:</p> <ul> <li>T1 = Winging (UI1)</li> <li>T2 = Shoveling (UI1)</li> <li>T3 = Double-Shoveling (UI1)</li> <li>T4 = Interruption Grooves (UI2)</li> <li>T5 = Tuberculum Dentale (UI2)</li> <li>T6 = Mesial Ridge (UC)</li> <li>T7 = Distal Accessory Ridge (UC)</li> <li>T8 = Hypocone (UM2)</li> <li>T9 = Carabelli Trait (UM1)</li> <li>T10 = Cusp 5 (UM1)</li> <li>T11 = Enamel Extensions (UM1)</li> <li>T12 = Peg-Reduced-Missing (UM3)</li> <li>T13 = Lingual Cusp Number (LP2)</li> <li>T14 = Groove Pattern (LM2)</li> <li>T15 = Cusp 6 (LM1)</li> <li>T16 = Cusp Number (LM2)</li> <li>T17 = Deflecting Wrinkle (LM1)</li> <li>T18 = Distal Trigonid Crest (LM1)</li> <li>T19 = Protostylid (LM1)</li> <li>T20 = Cusp 7 (LM1)</li> <li>T21 = Odontomes (UP-LP)</li> <li>T22 = Root Number (UP1)</li> <li>T23 = Root Number (UM2)</li> <li>T24 = Root Number (LC)</li> <li>T25 = Tomes’ Root (LP1)</li> <li>T26 = Root Number (LM1)</li> <li>T27 = Root Number (LM2)</li> </ul> <p>Abbreviations for the 645 microsatellite allele locus names (columns) in “microsatellite loci mean sizes.csv” as in T. J. Pemberton, M. DeGiorgio, N. A. Rosenberg, Population structure in a comprehensive genomic data set on human microsatellite variation. <em>G3: Genes Genom. Genet.</em> 3, 891–907 (2013). DOI: 10.1534/g3.113.005728</p>
Data from: Wolf in sheep's clothing: model misspecification undermines tests of the neutral theory for life histories
Understanding the processes behind change in reproductive state along life-history trajectories is a salient research program in evolutionary ecology. Two processes, state dependence and heterogeneity, can drive the dynamics of change among states. Both processes can operate simultaneously, begging the difficult question of how to tease them apart in practice. The Neutral Theory for Life Histories (NTLH) holds that the bulk of variations in life-history trajectories is due to state dependence and is hence neutral: Once previous (breeding) state is taken into account, variations are mostly random. Lifetime reproductive success (LRS), the number of descendants produced over an individual's reproductive life span, has been used to infer support for NTLH in natura. Support stemmed from accurate prediction of the population-level distribution of LRS with parameters estimated from a state dependence model. We show with Monte Carlo simulations that the current reliance of NTLH on LRS prediction in a null hypothesis framework easily leads to selecting a misspecified model, biased estimates and flawed inferences. Support for the NTLH can be spurious because of a systematic positive bias in estimated state dependence when heterogeneity is present in the data but ignored in the analysis. This bias can lead to spurious positive covariance between fitness components when there is in fact an underlying trade-off. Furthermore, neutrality implied by NTLH needs a clarification because of a probable disjunction between its common understanding by evolutionary ecologists and its translation into statistical models of life-history trajectories. Irrespective of what neutrality entails, testing hypotheses about the dynamics of change among states in life histories requires a multimodel framework because state dependence and heterogeneity can easily be mistaken for each other.
Data from: Evaluation of demographic history and neutral parameterization on the performance of Fst outlier tests
FST outlier tests are a potentially powerful way to detect genetic loci under spatially divergent selection. Unfortunately, the extent to which these tests are robust to non-equilibrium demographic histories has been under-studied. We developed a landscape-genetics simulator to test the effects of isolation by distance (IBD) and range expansion on FST outlier methods. We evaluated the two most commonly used methods for the identification of FST outliers (FDIST2 and BayeScan, which assume samples are evolutionarily independent) and two recent methods (FLK and Bayenv2, which estimate and account for evolutionary non-independence). Parameterization with a set of neutral loci ("neutral parameterization") always improved the performance of FLK and Bayenv2, while neutral parameterization caused FDIST2 to actually perform worse in the cases of IBD or range expansion. BayeScan was improved when the prior odds on neutrality was increased, regardless of the true odds in the data. On their best performance, however, the widely-used methods had high false-positive rates for IBD and range expansion and were outperformed by methods that accounted for evolutionary non-independence. In addition, default settings in FDIST2 and BayeScan resulted in many false positives under balancing selection. However, all methods did very well if a large set of neutral loci is available to create empirical p-values. We conclude that in species that exhibit IBD or have undergone range expansion, many of the published FST outliers based on FDIST2 and BayeScan are probably false positives, but FLK and Bayenv2 show great promise for accurately identifying loci under spatially-divergent selection.
Data from: Wolf in sheep's clothing: model misspecification undermines tests of the neutral theory for life histories
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Data from: Evaluation of demographic history and neutral parameterization on the performance of Fst outlier tests
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Pilot Test of Five Weight Neutral Interventions to Improve Health Among Adults of Higher Body Weight
ClinicalTrials.gov study NCT07363616. IPD Sharing: YES. Countries: 1. Publications: 0.
TekiTrust Tests to Determine the Level of SARS-COV-2/COVID-19 Neutralizing Antibodies in the Blood
ClinicalTrials.gov study NCT05338762. IPD Sharing: NO. Countries: 1. Publications: 0.
Performance of CAST (Cellular Antigen Stimulation Test) in Patients With Wasp Venom Allergy: Evaluation of Neutralizing IgG Subclasses
ClinicalTrials.gov study NCT00794287. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Pilot Trial to Elaborate a Cutaneous Antigen Neutralization Test in Patients Suffering From Rhinoconjunctivitis
ClinicalTrials.gov study NCT00461721. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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