Browsing by Subject "Bayes Theorem"
Now showing 1 - 20 of 38
Results Per Page
Sort Options
Item Open Access A Bayesian Approach to Inferring Rates of Selfing and Locus-Specific Mutation.(Genetics, 2015-11) Redelings, Benjamin D; Kumagai, Seiji; Tatarenkov, Andrey; Wang, Liuyang; Sakai, Ann K; Weller, Stephen G; Culley, Theresa M; Avise, John C; Uyenoyama, Marcy KWe present a Bayesian method for characterizing the mating system of populations reproducing through a mixture of self-fertilization and random outcrossing. Our method uses patterns of genetic variation across the genome as a basis for inference about reproduction under pure hermaphroditism, gynodioecy, and a model developed to describe the self-fertilizing killifish Kryptolebias marmoratus. We extend the standard coalescence model to accommodate these mating systems, accounting explicitly for multilocus identity disequilibrium, inbreeding depression, and variation in fertility among mating types. We incorporate the Ewens sampling formula (ESF) under the infinite-alleles model of mutation to obtain a novel expression for the likelihood of mating system parameters. Our Markov chain Monte Carlo (MCMC) algorithm assigns locus-specific mutation rates, drawn from a common mutation rate distribution that is itself estimated from the data using a Dirichlet process prior model. Our sampler is designed to accommodate additional information, including observations pertaining to the sex ratio, the intensity of inbreeding depression, and other aspects of reproduction. It can provide joint posterior distributions for the population-wide proportion of uniparental individuals, locus-specific mutation rates, and the number of generations since the most recent outcrossing event for each sampled individual. Further, estimation of all basic parameters of a given model permits estimation of functions of those parameters, including the proportion of the gene pool contributed by each sex and relative effective numbers.Item Open Access A framework for integrating the songbird brain.(J Comp Physiol A Neuroethol Sens Neural Behav Physiol, 2002-12) Jarvis, ED; Smith, VA; Wada, K; Rivas, MV; McElroy, M; Smulders, TV; Carninci, P; Hayashizaki, Y; Dietrich, F; Wu, X; McConnell, P; Yu, J; Wang, PP; Hartemink, AJ; Lin, SBiological systems by default involve complex components with complex relationships. To decipher how biological systems work, we assume that one needs to integrate information over multiple levels of complexity. The songbird vocal communication system is ideal for such integration due to many years of ethological investigation and a discreet dedicated brain network. Here we announce the beginnings of a songbird brain integrative project that involves high-throughput, molecular, anatomical, electrophysiological and behavioral levels of analysis. We first formed a rationale for inclusion of specific biological levels of analysis, then developed high-throughput molecular technologies on songbird brains, developed technologies for combined analysis of electrophysiological activity and gene regulation in awake behaving animals, and developed bioinformatic tools that predict causal interactions within and between biological levels of organization. This integrative brain project is fitting for the interdisciplinary approaches taken in the current songbird issue of the Journal of Comparative Physiology A and is expected to be conducive to deciphering how brains generate and perceive complex behaviors.Item Open Access A new trial design to accelerate tuberculosis drug development: the Phase IIC Selection Trial with Extended Post-treatment follow-up (STEP).(BMC Med, 2016-03-23) Phillips, Patrick PJ; Dooley, Kelly E; Gillespie, Stephen H; Heinrich, Norbert; Stout, Jason E; Nahid, Payam; Diacon, Andreas H; Aarnoutse, Rob E; Kibiki, Gibson S; Boeree, Martin J; Hoelscher, MichaelBACKGROUND: The standard 6-month four-drug regimen for the treatment of drug-sensitive tuberculosis has remained unchanged for decades and is inadequate to control the epidemic. Shorter, simpler regimens are urgently needed to defeat what is now the world's greatest infectious disease killer. METHODS: We describe the Phase IIC Selection Trial with Extended Post-treatment follow-up (STEP) as a novel hybrid phase II/III trial design to accelerate regimen development. In the Phase IIC STEP trial, the experimental regimen is given for the duration for which it will be studied in phase III (presently 3 or 4 months) and patients are followed for clinical outcomes of treatment failure and relapse for a total of 12 months from randomisation. Operating characteristics of the trial design are explored assuming a classical frequentist framework as well as a Bayesian framework with flat and sceptical priors. A simulation study is conducted using data from the RIFAQUIN phase III trial to illustrate how such a design could be used in practice. RESULTS: With 80 patients per arm, and two (2.5 %) unfavourable outcomes in the STEP trial, there is a probability of 0.99 that the proportion of unfavourable outcomes in a potential phase III trial would be less than 12 % and a probability of 0.91 that the proportion of unfavourable outcomes would be less than 8 %. With six (7.5 %) unfavourable outcomes, there is a probability of 0.82 that the proportion of unfavourable outcomes in a potential phase III trial would be less than 12 % and a probability of 0.41 that it would be less than 8 %. Simulations using data from the RIFAQUIN trial show that a STEP trial with 80 patients per arm would have correctly shown that the Inferior Regimen should not proceed to phase III and would have had a high chance (0.88) of either showing that the Successful Regimen could proceed to phase III or that it might require further optimisation. CONCLUSIONS: Collection of definitive clinical outcome data in a relatively small number of participants over only 12 months provides valuable information about the likelihood of success in a future phase III trial. We strongly believe that the STEP trial design described herein is an important tool that would allow for more informed decision-making and accelerate regimen development.Item Open Access A tutorial on Bayesian multi-model linear regression with BAS and JASP.(Behavior research methods, 2021-12) Bergh, Don van den; Clyde, Merlise A; Gupta, Akash R Komarlu Narendra; de Jong, Tim; Gronau, Quentin F; Marsman, Maarten; Ly, Alexander; Wagenmakers, Eric-JanLinear regression analyses commonly involve two consecutive stages of statistical inquiry. In the first stage, a single 'best' model is defined by a specific selection of relevant predictors; in the second stage, the regression coefficients of the winning model are used for prediction and for inference concerning the importance of the predictors. However, such second-stage inference ignores the model uncertainty from the first stage, resulting in overconfident parameter estimates that generalize poorly. These drawbacks can be overcome by model averaging, a technique that retains all models for inference, weighting each model's contribution by its posterior probability. Although conceptually straightforward, model averaging is rarely used in applied research, possibly due to the lack of easily accessible software. To bridge the gap between theory and practice, we provide a tutorial on linear regression using Bayesian model averaging in JASP, based on the BAS package in R. Firstly, we provide theoretical background on linear regression, Bayesian inference, and Bayesian model averaging. Secondly, we demonstrate the method on an example data set from the World Happiness Report. Lastly, we discuss limitations of model averaging and directions for dealing with violations of model assumptions.Item Open Access Abrupt deceleration of molecular evolution linked to the origin of arborescence in ferns.(Evolution; international journal of organic evolution, 2010-09) Korall, Petra; Schuettpelz, Eric; Pryer, Kathleen MMolecular rate heterogeneity, whereby rates of molecular evolution vary among groups of organisms, is a well-documented phenomenon. Nonetheless, its causes are poorly understood. For animals, generation time is frequently cited because longer-lived species tend to have slower rates of molecular evolution than their shorter-lived counterparts. Although a similar pattern has been uncovered in flowering plants, using proxies such as growth form, the underlying process has remained elusive. Here, we find a deceleration of molecular evolutionary rate to be coupled with the origin of arborescence in ferns. Phylogenetic branch lengths within the “tree fern” clade are considerably shorter than those of closely related lineages, and our analyses demonstrate that this is due to a significant difference in molecular evolutionary rate. Reconstructions reveal that an abrupt rate deceleration coincided with the evolution of the long-lived tree-like habit at the base of the tree fern clade. This suggests that a generation time effect may well be ubiquitous across the green tree of life, and that the search for a responsible mechanism must focus on characteristics shared by all vascular plants. Discriminating among the possibilities will require contributions from various biological disciplines,but will be necessary for a full appreciation of molecular evolution.Item Open Access Advances to Bayesian network inference for generating causal networks from observational biological data.(Bioinformatics, 2004-12-12) Yu, Jing; Smith, V Anne; Wang, Paul P; Hartemink, Alexander J; Jarvis, Erich DMOTIVATION: Network inference algorithms are powerful computational tools for identifying putative causal interactions among variables from observational data. Bayesian network inference algorithms hold particular promise in that they can capture linear, non-linear, combinatorial, stochastic and other types of relationships among variables across multiple levels of biological organization. However, challenges remain when applying these algorithms to limited quantities of experimental data collected from biological systems. Here, we use a simulation approach to make advances in our dynamic Bayesian network (DBN) inference algorithm, especially in the context of limited quantities of biological data. RESULTS: We test a range of scoring metrics and search heuristics to find an effective algorithm configuration for evaluating our methodological advances. We also identify sampling intervals and levels of data discretization that allow the best recovery of the simulated networks. We develop a novel influence score for DBNs that attempts to estimate both the sign (activation or repression) and relative magnitude of interactions among variables. When faced with limited quantities of observational data, combining our influence score with moderate data interpolation reduces a significant portion of false positive interactions in the recovered networks. Together, our advances allow DBN inference algorithms to be more effective in recovering biological networks from experimentally collected data. AVAILABILITY: Source code and simulated data are available upon request. SUPPLEMENTARY INFORMATION: http://www.jarvislab.net/Bioinformatics/BNAdvances/Item Open Access Age-related model for estimating the symptomatic and asymptomatic transmissibility of COVID-19 patients.(Biometrics, 2023-09) Tan, Jianbin; Shen, Ye; Ge, Yang; Martinez, Leonardo; Huang, HuiEstimation of age-dependent transmissibility of COVID-19 patients is critical for effective policymaking. Although the transmissibility of symptomatic cases has been extensively studied, asymptomatic infection is understudied due to limited data. Using a dataset with reliably distinguished symptomatic and asymptomatic statuses of COVID-19 cases, we propose an ordinary differential equation model that considers age-dependent transmissibility in transmission dynamics. Under a Bayesian framework, multi-source information is synthesized in our model for identifying transmissibility. A shrinkage prior among age groups is also adopted to improve the estimation behavior of transmissibility from age-structured data. The added values of accounting for age-dependent transmissibility are further evaluated through simulation studies. In real-data analysis, we compare our approach with two basic models using the deviance information criterion (DIC) and its extension. We find that the proposed model is more flexible for our epidemic data. Our results also suggest that the transmissibility of asymptomatic infections is significantly lower (on average, 76.45% with a credible interval (27.38%, 88.65%)) than that of symptomatic cases. In both symptomatic and asymptomatic patients, the transmissibility mainly increases with age. Patients older than 30 years are more likely to develop symptoms with higher transmissibility. We also find that the transmission burden of asymptomatic cases is lower than that of symptomatic patients.Item Open Access Assessing Bayesian Phylogenetic Information Content of Morphological Data Using Knowledge From Anatomy Ontologies.(Systematic biology, 2022-10) Porto, Diego S; Dahdul, Wasila M; Lapp, Hilmar; Balhoff, James P; Vision, Todd J; Mabee, Paula M; Uyeda, JosefMorphology remains a primary source of phylogenetic information for many groups of organisms, and the only one for most fossil taxa. Organismal anatomy is not a collection of randomly assembled and independent "parts", but instead a set of dependent and hierarchically nested entities resulting from ontogeny and phylogeny. How do we make sense of these dependent and at times redundant characters? One promising approach is using ontologies-structured controlled vocabularies that summarize knowledge about different properties of anatomical entities, including developmental and structural dependencies. Here, we assess whether evolutionary patterns can explain the proximity of ontology-annotated characters within an ontology. To do so, we measure phylogenetic information across characters and evaluate if it matches the hierarchical structure given by ontological knowledge-in much the same way as across-species diversity structure is given by phylogeny. We implement an approach to evaluate the Bayesian phylogenetic information (BPI) content and phylogenetic dissonance among ontology-annotated anatomical data subsets. We applied this to data sets representing two disparate animal groups: bees (Hexapoda: Hymenoptera: Apoidea, 209 chars) and characiform fishes (Actinopterygii: Ostariophysi: Characiformes, 463 chars). For bees, we find that BPI is not substantially explained by anatomy since dissonance is often high among morphologically related anatomical entities. For fishes, we find substantial information for two clusters of anatomical entities instantiating concepts from the jaws and branchial arch bones, but among-subset information decreases and dissonance increases substantially moving to higher-level subsets in the ontology. We further applied our approach to address particular evolutionary hypotheses with an example of morphological evolution in miniature fishes. While we show that phylogenetic information does match ontology structure for some anatomical entities, additional relationships and processes, such as convergence, likely play a substantial role in explaining BPI and dissonance, and merit future investigation. Our work demonstrates how complex morphological data sets can be interrogated with ontologies by allowing one to access how information is spread hierarchically across anatomical concepts, how congruent this information is, and what sorts of processes may play a role in explaining it: phylogeny, development, or convergence. [Apidae; Bayesian phylogenetic information; Ostariophysi; Phenoscape; phylogenetic dissonance; semantic similarity.].Item Restricted Association between DNA damage response and repair genes and risk of invasive serous ovarian cancer.(PLoS One, 2010-04-08) Schildkraut, Joellen M; Iversen, Edwin S; Wilson, Melanie A; Clyde, Merlise A; Moorman, Patricia G; Palmieri, Rachel T; Whitaker, Regina; Bentley, Rex C; Marks, Jeffrey R; Berchuck, AndrewBACKGROUND: We analyzed the association between 53 genes related to DNA repair and p53-mediated damage response and serous ovarian cancer risk using case-control data from the North Carolina Ovarian Cancer Study (NCOCS), a population-based, case-control study. METHODS/PRINCIPAL FINDINGS: The analysis was restricted to 364 invasive serous ovarian cancer cases and 761 controls of white, non-Hispanic race. Statistical analysis was two staged: a screen using marginal Bayes factors (BFs) for 484 SNPs and a modeling stage in which we calculated multivariate adjusted posterior probabilities of association for 77 SNPs that passed the screen. These probabilities were conditional on subject age at diagnosis/interview, batch, a DNA quality metric and genotypes of other SNPs and allowed for uncertainty in the genetic parameterizations of the SNPs and number of associated SNPs. Six SNPs had Bayes factors greater than 10 in favor of an association with invasive serous ovarian cancer. These included rs5762746 (median OR(odds ratio)(per allele) = 0.66; 95% credible interval (CI) = 0.44-1.00) and rs6005835 (median OR(per allele) = 0.69; 95% CI = 0.53-0.91) in CHEK2, rs2078486 (median OR(per allele) = 1.65; 95% CI = 1.21-2.25) and rs12951053 (median OR(per allele) = 1.65; 95% CI = 1.20-2.26) in TP53, rs411697 (median OR (rare homozygote) = 0.53; 95% CI = 0.35 - 0.79) in BACH1 and rs10131 (median OR( rare homozygote) = not estimable) in LIG4. The six most highly associated SNPs are either predicted to be functionally significant or are in LD with such a variant. The variants in TP53 were confirmed to be associated in a large follow-up study. CONCLUSIONS/SIGNIFICANCE: Based on our findings, further follow-up of the DNA repair and response pathways in a larger dataset is warranted to confirm these results.Item Open Access Associations of Alcohol and Tobacco Retail Outlet Rates with Neighborhood Disadvantage.(International journal of environmental research and public health, 2022-01-20) Wheeler, David C; Boyle, Joseph; Barsell, D Jeremy; Glasgow, Trevin; McClernon, F Joseph; Oliver, Jason A; Fuemmeler, Bernard FTobacco causes 29% of cancer-related deaths while alcohol causes 5.5% of cancer-related deaths. Reducing the consumption of these cancer-causing products is a special priority area for the National Cancer Institute. While many factors are linked to tobacco and alcohol use, the placement and density of retail outlets within neighborhoods may be one community-level risk factor contributing to greater use of these products. To elucidate associations between tobacco, alcohol, and tobacco and alcohol retail outlets (TRO, ARO, and TARO) and neighborhood disadvantage over a large geographic area, we employed a novel Bayesian index modeling approach to estimate a neighborhood disadvantage index (NDI) and its associations with rates of the three types of retailers across block groups in the state of North Carolina. We used a novel extension of the Bayesian index model to include a shared component for the spatial pattern common to all three types of outlets and NDI effects that varied by outlet type. The shared component identifies areas that are elevated in risk for all outlets. The results showed significant positive associations between neighborhood disadvantage and TROs (relative risk (RR) = 1.12, 95% credible interval (CI = 1.09, 1.14)) and AROs (RR = 1.15, 95% CI = 1.11, 1.17), but the association was greatest for TAROs (RR = 1.21, 95% CI = 1.18, 1.24). The most important variables in the NDI were percent renters (i.e., low home ownership), percent of homes built before 1940 (i.e., old housing stock), and percent without a high school diploma (i.e., low education).Item Open Access Automatic annotation of spatial expression patterns via sparse Bayesian factor models.(PLoS Comput Biol, 2011-07) Pruteanu-Malinici, Iulian; Mace, Daniel L; Ohler, UweAdvances in reporters for gene expression have made it possible to document and quantify expression patterns in 2D-4D. In contrast to microarrays, which provide data for many genes but averaged and/or at low resolution, images reveal the high spatial dynamics of gene expression. Developing computational methods to compare, annotate, and model gene expression based on images is imperative, considering that available data are rapidly increasing. We have developed a sparse Bayesian factor analysis model in which the observed expression diversity of among a large set of high-dimensional images is modeled by a small number of hidden common factors. We apply this approach on embryonic expression patterns from a Drosophila RNA in situ image database, and show that the automatically inferred factors provide for a meaningful decomposition and represent common co-regulation or biological functions. The low-dimensional set of factor mixing weights is further used as features by a classifier to annotate expression patterns with functional categories. On human-curated annotations, our sparse approach reaches similar or better classification of expression patterns at different developmental stages, when compared to other automatic image annotation methods using thousands of hard-to-interpret features. Our study therefore outlines a general framework for large microscopy data sets, in which both the generative model itself, as well as its application for analysis tasks such as automated annotation, can provide insight into biological questions.Item Open Access Bayesian inference for genomic data integration reduces misclassification rate in predicting protein-protein interactions.(PLoS Comput Biol, 2011-07) Xing, Chuanhua; Dunson, David BProtein-protein interactions (PPIs) are essential to most fundamental cellular processes. There has been increasing interest in reconstructing PPIs networks. However, several critical difficulties exist in obtaining reliable predictions. Noticeably, false positive rates can be as high as >80%. Error correction from each generating source can be both time-consuming and inefficient due to the difficulty of covering the errors from multiple levels of data processing procedures within a single test. We propose a novel Bayesian integration method, deemed nonparametric Bayes ensemble learning (NBEL), to lower the misclassification rate (both false positives and negatives) through automatically up-weighting data sources that are most informative, while down-weighting less informative and biased sources. Extensive studies indicate that NBEL is significantly more robust than the classic naïve Bayes to unreliable, error-prone and contaminated data. On a large human data set our NBEL approach predicts many more PPIs than naïve Bayes. This suggests that previous studies may have large numbers of not only false positives but also false negatives. The validation on two human PPIs datasets having high quality supports our observations. Our experiments demonstrate that it is feasible to predict high-throughput PPIs computationally with substantially reduced false positives and false negatives. The ability of predicting large numbers of PPIs both reliably and automatically may inspire people to use computational approaches to correct data errors in general, and may speed up PPIs prediction with high quality. Such a reliable prediction may provide a solid platform to other studies such as protein functions prediction and roles of PPIs in disease susceptibility.Item Restricted Delimiting species without nuclear monophyly in Madagascar's mouse lemurs.(PLoS One, 2010-03-31) Weisrock, David W; Rasoloarison, Rodin M; Fiorentino, Isabella; Ralison, José M; Goodman, Steven M; Kappeler, Peter M; Yoder, Anne DBACKGROUND: Speciation begins when populations become genetically separated through a substantial reduction in gene flow, and it is at this point that a genetically cohesive set of populations attain the sole property of species: the independent evolution of a population-level lineage. The comprehensive delimitation of species within biodiversity hotspots, regardless of their level of divergence, is important for understanding the factors that drive the diversification of biota and for identifying them as targets for conservation. However, delimiting recently diverged species is challenging due to insufficient time for the differential evolution of characters--including morphological differences, reproductive isolation, and gene tree monophyly--that are typically used as evidence for separately evolving lineages. METHODOLOGY: In this study, we assembled multiple lines of evidence from the analysis of mtDNA and nDNA sequence data for the delimitation of a high diversity of cryptically diverged population-level mouse lemur lineages across the island of Madagascar. Our study uses a multi-faceted approach that applies phylogenetic, population genetic, and genealogical analysis for recognizing lineage diversity and presents the most thoroughly sampled species delimitation of mouse lemur ever performed. CONCLUSIONS: The resolution of a large number of geographically defined clades in the mtDNA gene tree provides strong initial evidence for recognizing a high diversity of population-level lineages in mouse lemurs. We find additional support for lineage recognition in the striking concordance between mtDNA clades and patterns of nuclear population structure. Lineages identified using these two sources of evidence also exhibit patterns of population divergence according to genealogical exclusivity estimates. Mouse lemur lineage diversity is reflected in both a geographically fine-scaled pattern of population divergence within established and geographically widespread taxa, as well as newly resolved patterns of micro-endemism revealed through expanded field sampling into previously poorly and well-sampled regions.Item Open Access Detecting local haplotype sharing and haplotype association.(Genetics, 2014-07) Xu, Hanli; Guan, YongtaoA novel haplotype association method is presented, and its power is demonstrated. Relying on a statistical model for linkage disequilibrium (LD), the method first infers ancestral haplotypes and their loadings at each marker for each individual. The loadings are then used to quantify local haplotype sharing between individuals at each marker. A statistical model was developed to link the local haplotype sharing and phenotypes to test for association. We devised a novel method to fit the LD model, reducing the complexity from putatively quadratic to linear (in the number of ancestral haplotypes). Therefore, the LD model can be fitted to all study samples simultaneously, and, consequently, our method is applicable to big data sets. Compared to existing haplotype association methods, our method integrated out phase uncertainty, avoided arbitrariness in specifying haplotypes, and had the same number of tests as the single-SNP analysis. We applied our method to data from the Wellcome Trust Case Control Consortium and discovered eight novel associations between seven gene regions and five disease phenotypes. Among these, GRIK4, which encodes a protein that belongs to the glutamate-gated ionic channel family, is strongly associated with both coronary artery disease and rheumatoid arthritis. A software package implementing methods described in this article is freely available at http://www.haplotype.org.Item Open Access Dissecting the Domains of Parkinson's Disease: Insights from Longitudinal Item Response Theory Modeling.(Movement disorders : official journal of the Movement Disorder Society, 2022-09) Luo, Sheng; Zou, Haotian; Stebbins, Glenn T; Schwarzschild, Michael A; Macklin, Eric A; Chan, James; Oakes, David; Simuni, Tanya; Goetz, Christopher G; Parkinson Study Group SURE-PD3 InvestigatorsBackground
Longitudinal item response theory (IRT) models previously suggested that the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) motor examination has two salient domains, tremor and nontremor, that progress in time and in response to treatment differently.Objective
Apply longitudinal IRT modeling, separating tremor and nontremor domains, to reanalyze outcomes in the previously published clinical trial (Study of Urate Elevation in Parkinson's Disease, Phase 3) that showed no overall treatment effects.Methods
We applied unidimensional and multidimensional longitudinal IRT models to MDS-UPDRS motor examination items in 298 participants with Parkinson's disease from the Study of Urate Elevation in Parkinson's Disease, Phase 3 (placebo vs. inosine) study. We separated 10 tremor items from 23 nontremor items and used Bayesian inference to estimate progression rates and sensitivity to treatment in overall motor severity and tremor and nontremor domains.Results
The progression rate was faster in the tremor domain than the nontremor domain before levodopa treatment. Inosine treatment had no effect on either domain relative to placebo. Levodopa treatment was associated with greater slowing of progression in the tremor domain than the nontremor domain regardless of inosine exposure. Linear patterns of progression were observed. Despite different domain-specific progression patterns, tremor and nontremor severities at baseline and over time were significantly correlated.Conclusions
Longitudinal IRT analysis is a novel statistical method addressing limitations of traditional linear regression approaches. It is particularly useful because it can simultaneously monitor changes in different, but related, domains over time and in response to treatment interventions. We suggest that in neurological diseases with distinct impairment domains, clinical or anatomical, this application may identify patterns of change unappreciated by standard statistical methods. © 2022 International Parkinson and Movement Disorder Society.Item Open Access Do asexual polyploid lineages lead short evolutionary lives? A case study from the fern genus Astrolepis.(Evolution; international journal of organic evolution, 2011-11) Beck, JB; Windham, MD; Pryer, KMA life-history transition to asexuality is typically viewed as leading to a heightened extinction risk, and a number of studies have evaluated this claim by examining the relative ages of asexual versus closely related sexual lineages. Surprisingly, a rigorous assessment of the age of an asexual plant lineage has never been published, although asexuality is extraordinarily common among plants. Here, we estimate the ages of sexual diploids and asexual polyploids in the fern genus Astrolepis using a well-supported plastid phylogeny and a relaxed-clock dating approach. The 50 asexual polyploid samples we included were conservatively estimated to comprise 19 distinct lineages, including a variety of auto- and allopolyploid genomic combinations. All were either the same age or younger than the crown group comprising their maternal sexual-diploid parents based simply on their phylogenetic position. Node ages estimated with the relaxed-clock approach indicated that the average maximum age of asexual lineages was 0.4 My, and individual lineages were on average 7 to 47 times younger than the crown- and total-ages of their sexual parents. Although the confounding association between asexuality and polyploidy precludes definite conclusions regarding the effect of asexuality, our results suggest that asexuality limits evolutionary potential in Astrolepis.Item Open Access Estimation and validation of a multiattribute model of Alzheimer disease progression.(Med Decis Making, 2010-11) Stallard, Eric; Kinosian, Bruce; Zbrozek, Arthur S; Yashin, Anatoliy I; Glick, Henry A; Stern, YaakovOBJECTIVES: To estimate and validate a multiattribute model of the clinical course of Alzheimer disease (AD) from mild AD to death in a high-quality prospective cohort study, and to estimate the impact of hypothetical modifications to AD progression rates on costs associated with Medicare and Medicaid services. DATA AND METHODS: The authors estimated sex-specific longitudinal Grade of Membership (GoM) models for AD patients (103 men, 149 women) in the initial cohort of the Predictors Study (1989-2001) based on 80 individual measures obtained every 6 mo for 10 y. These models were replicated for AD patients (106 men, 148 women) in the 2nd Predictors Study cohort (1997-2007). Model validation required that the disease-specific transition parameters be identical for both Predictors Study cohorts. Medicare costs were estimated from the National Long Term Care Survey. RESULTS: Sex-specific models were validated using the 2nd Predictors Study cohort with the GoM transition parameters constrained to the values estimated for the 1st Predictors Study cohort; 57 to 61 of the 80 individual measures contributed significantly to the GoM models. Simulated, cost-free interventions in the rate of progression of AD indicated that large potential cost offsets could occur for patients at the earliest stages of AD. CONCLUSIONS: AD progression is characterized by a small number of parameters governing changes in large numbers of correlated indicators of AD severity. The analysis confirmed that the progression of AD represents a complex multidimensional physiological process that is similar across different study cohorts. The estimates suggested that there could be large cost offsets to Medicare and Medicaid from the slowing of AD progression among patients with mild AD. The methodology appears generally applicable in AD modeling.Item Open Access Evolution of the sex ratio and effective number under gynodioecy and androdioecy.(Theoretical population biology, 2017-12) Uyenoyama, Marcy K; Takebayashi, NaokiWe address the evolution of effective number of individuals under androdioecy and gynodioecy. We analyze dynamic models of autosomal modifiers of weak effect on sex expression. In our zygote control models, the sex expressed by a zygote depends on its own genotype, while in our maternal control models, it depends on the genotype of its maternal parent. Our analysis unifies full multi-dimensional local stability analysis with the Li-Price equation, which for all its heuristic appeal, describes evolutionary change over a single generation. We define a point in the neighborhood of a fixation state from which a single-generation step indicates the asymptotic behavior of the frequency of a modifier allele initiated at an arbitrary point near the fixation state. A concept of heritability appropriate for the evolutionary modification of sex emerges from the Li-Priceframework. We incorporate our theoretical analysis into our previously-developed Bayesian inference framework to develop a new method for inferring the viability of gonochores (males or females) relative to hermaphrodites. Applying this approach to microsatellite data derived from natural populations of the gynodioecious plant Schiedea salicaria and the androdioecious killifish Kryptolebias marmoratus, we find that while female and hermaphrodite S. salicaria appear to have similar viabilities, male K. marmoratus appear to survive to reproductive age at less than half the rate of hermaphrodites.Item Open Access Facility-based disease surveillance and Bayesian hierarchical modeling to estimate endemic typhoid fever incidence, Kilimanjaro Region, Tanzania, 2007-2018.(PLoS neglected tropical diseases, 2022-07-05) Cutting, Elena R; Simmons, Ryan A; Madut, Deng B; Maze, Michael J; Kalengo, Nathaniel H; Carugati, Manuela; Mbwasi, Ronald M; Kilonzo, Kajiru G; Lyamuya, Furaha; Marandu, Annette; Mosha, Calvin; Saganda, Wilbrod; Lwezaula, Bingileki F; Hertz, Julian T; Morrissey, Anne B; Turner, Elizabeth L; Mmbaga, Blandina T; Kinabo, Grace D; Maro, Venance P; Crump, John A; Rubach, Matthew PGrowing evidence suggests considerable variation in endemic typhoid fever incidence at some locations over time, yet few settings have multi-year incidence estimates to inform typhoid control measures. We sought to describe a decade of typhoid fever incidence in the Kilimanjaro Region of Tanzania. Cases of blood culture confirmed typhoid were identified among febrile patients at two sentinel hospitals during three study periods: 2007-08, 2011-14, and 2016-18. To account for under-ascertainment at sentinel facilities, we derived adjustment multipliers from healthcare utilization surveys done in the hospital catchment area. Incidence estimates and credible intervals (CrI) were derived using a Bayesian hierarchical incidence model that incorporated uncertainty of our observed typhoid fever prevalence, of healthcare seeking adjustment multipliers, and of blood culture diagnostic sensitivity. Among 3,556 total participants, 50 typhoid fever cases were identified. Of typhoid cases, 26 (52%) were male and the median (range) age was 22 (<1-60) years; 4 (8%) were aged <5 years and 10 (20%) were aged 5 to 14 years. Annual typhoid fever incidence was estimated as 61.5 (95% CrI 14.9-181.9), 6.5 (95% CrI 1.4-20.4), and 4.0 (95% CrI 0.6-13.9) per 100,000 persons in 2007-08, 2011-14, and 2016-18, respectively. There were no deaths among typhoid cases. We estimated moderate typhoid incidence (≥10 per 100 000) in 2007-08 and low (<10 per 100 000) incidence during later surveillance periods, but with overlapping credible intervals across study periods. Although consistent with falling typhoid incidence, we interpret this as showing substantial variation over the study periods. Given potential variation, multi-year surveillance may be warranted in locations making decisions about typhoid conjugate vaccine introduction and other control measures.Item Open Access Ignoring correlated activity causes a failure of retinal population codes.(Nature communications, 2020-09-14) Ruda, Kiersten; Zylberberg, Joel; Field, Greg DFrom starlight to sunlight, adaptation alters retinal output, changing both the signal and noise among populations of retinal ganglion cells (RGCs). Here we determine how these light level-dependent changes impact decoding of retinal output, testing the importance of accounting for RGC noise correlations to optimally read out retinal activity. We find that at moonlight conditions, correlated noise is greater and assuming independent noise severely diminishes decoding performance. In fact, assuming independence among a local population of RGCs produces worse decoding than using a single RGC, demonstrating a failure of population codes when correlated noise is substantial and ignored. We generalize these results with a simple model to determine what conditions dictate this failure of population processing. This work elucidates the circumstances in which accounting for noise correlations is necessary to take advantage of population-level codes and shows that sensory adaptation can strongly impact decoding requirements on downstream brain areas.