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PubMed2000

Estimation of sensitivity and specificity of diagnostic tests and disease prevalence when the true disease state is unknown.

The performance of a new diagnostic test is frequently evaluated by comparison to a perfect reference test (i.e. a gold standard). In many instances, however, a reference test is less than perfect. In this paper, we review methods for estimation of the accuracy of a diagnostic test when an imperfect reference test with known classification errors is available. Furthermore, we focus our presentation on available methods of estimation of test characteristics when the sensitivity and specificity of both tests are unknown. We present some of the available statistical methods for estimation of the accuracy of diagnostic tests when a reference test does not exist (including maximum likelihood estimation and Bayesian inference). We illustrate the application of the described methods using data from an evaluation of a nested polymerase chain reaction and microscopic examination of kidney imprints for detection of Nucleospora salmonis in rainbow trout.

Algorithms↗

PubMed1998

Reducing the incidence of epileptic seizures in the Belgian Tervuren through selection.

There is growing evidence that idiopathic epilepsy in the Belgium Tervuren has a genetic foundation. Reducing the incidence of this disorder, which may afflict as much as 17% of the breed, will rely upon the wise selection of parents. Seizure data on 997 dogs from the American Belgian Tervuren Club were collected through questionnaires in which animals were classified into one of four mutually exclusive categories: 1) no seizures observed, 2) one seizure observed, 3) two to five seizures, and 4) more than five seizures. The analysis of this ordered data made use of a threshold model of Bayesian inference. Integration of posterior densities was accomplished through Gibbs sampling. Through this analysis we are able to predict that the offspring of the mating of two non-epileptic dogs has a probability of 0.99 of never suffering from a seizure. The offspring of the mating of two dogs who have each had 1 seizure has a predicted probability 0.58 of never suffering from a seizure. Prevention of this disease is best prescribed through the selection of non-epileptic dogs as parents of future generations.

Animals↗

PubMed1998

Mixed graphical models for simultaneous model identification and control applied to the glucose-insulin metabolism.

In this paper a method for model identification of biological systems described by stochastic linear differential equations using a new computational technique for statistical Bayesian inference, namely mixed graphical models in the sense of Lauritzen and Wermuth, is presented. The model is identified in terms of biological model parameters and noise parameters. This non-linear estimation problem is solved by means of an exact inference algorithm. The parameter estimates are given as a-posteriori distributions which can be interpreted as fuzzy possibility distributions. For model-based simulations of the underlying biological system the model parameters are represented as uncertain parameters with the distributions obtained from the estimation procedure. We apply the presented methods to a model for the glucose-insulin metabolism: the Karlsburg model for type I diabetes.

Bayes Theorem↗

PubMed2000

Statistical analysis of domino chemical accidents.

A set of chemical accidents is retrieved from the literature and classified with regard to the substance involved and whether domino effects are present. This set of accidents and each of the classes defined are statistically analyzed with respect to its severity and comparison is made between domino and non-domino accidents. The analysis reveals that each accident category shows characteristic patterns in terms of fatalities caused and domino effects likelihood. Moreover, chemical accidents severity frequencies are described by using a two-parameter, revised form of the Pareto probability density function. The range within which the values of the parameters lie is investigated using Bayesian inference.

Accidents, Occupational↗

PubMed2002

Phylogeny of the Gyalectales and Ostropales (Ascomycota, Fungi): among and within order relationships based on nuclear ribosomal RNA small and large subunits.

Despite various morphological and anatomical similarities, the two orders Gyalectales (lichenized ascomycetes) and Ostropales (lichenized and non-lichenized ascomycetes) have been considered to be distantly related to each other and their position within the Ascomycota was unsettled. To estimate relationships within these groups and their respective phylogenenetic placement within the Ascomycota, we analyzed DNA sequences from the nuclear small and large subunit ribosomal RNA genes using Maximum Parsimony, Maximum Likelihood, and Bayesian statistics with Markov chain Monte Carlo algorithms. Support for internal branches estimated with bootstrap was compared to Bayesian posterior probabilities. We report here that the Ostropales, in their current circumscription, are paraphyletic, and that the Ostropales s.l. include the Gyalectales and Trapeliaceae. The Unitunicate Ascohymenials are redelineated to include the Ostropales s.l., as defined here, and the Baeomycetaceae. Dimerella and Coenogonium are congeneric, and Petractis thelotremella and P. hypoleuca are reunited with members of the genus Gyalecta. In addition to requiring less computational time, Bayesian inference of phylogeny recovered the same topology as a conventional heuristic search using Maximum Likelihood as the optimization criterion and seems superior to bootstrapping in estimating support for short internal branches.

Ascomycota↗

PubMed2002

Snake phylogeny: evidence from nuclear and mitochondrial genes.

We constructed phylogenies of snakes from the c-mos and cytochrome b genes using conventional phylogenetic methods as well as the relatively new method of Bayesian inference. For all methods, there was excellent congruence between the c-mos and cytochrome b genes, implying a high level of support for the shared clades. Our results agree with previous studies in two important respects: first, that the scolecophidians and alethinophidians are monophyletic sister clades; and second, that the Colubroidea is a monophyletic group with the Acrochordidae as its sister clade. However, our results differ from previous studies in the finding that Loxocemus and Xenopeltis cluster with pythons. An additional noteworthy result from our data is that the genera Exiliboa and Ungaliophis, often placed with Tropidophis (and Trachyboa, not included in the present study) in the Tropidophiidae, are in reality boids.

Animals↗

PubMed2003

Phylogeny of Passerida (Aves: Passeriformes) based on nuclear and mitochondrial sequence data.

Passerida is a monophyletic group of oscine passerines that includes almost 3500 species (about 36%) of all bird species in the world. The current understanding of higher-level relationships within Passerida is based on DNA-DNA hybridizations [C.G. Sibley, J.E. Ahlquist, Phylogeny and Classification of Birds, 1990, Yale University Press, New Haven, CT]. Our results are based on analyses of 3130 aligned nucleotide sequence data obtained from 48 ingroup and 13 outgroup genera. Three nuclear genes were sequenced: c-myc (498-510 bp), RAG-1 (930 bp), and myoglobin (693-722 bp), as well one mitochondrial gene; cytochrome b (879 bp). The data were analysed by parsimony, maximum-likelihood, and Bayesian inference. The African rockfowl and rockjumper are found to constitute the deepest branch within Passerida, but relationships among the other taxa are poorly resolved--only four major clades receive statistical support. One clade corresponds to Passeroidea of [C.G. Sibley, B.L. Monroe, Distribution and Taxonomy of Birds of the World, 1990, Yale University Press, New Haven, CT] and includes, e.g., flowerpeckers, sunbirds, accentors, weavers, estrilds, wagtails, finches, and sparrows. Starlings, mockingbirds, thrushes, Old World flycatchers, and dippers also group together in a clade corresponding to Muscicapoidea of Sibley and Monroe [op. cit.]. Monophyly of their Sylvioidea could not be corroborated--these taxa falls either into a clade with wrens, gnatcatchers, and nuthatches, or one with, e.g., warblers, bulbuls, babblers, and white-eyes. The tits, penduline tits, and waxwings belong to Passerida but have no close relatives among the taxa studied herein.

Animals↗

PubMed2003

Phylogeny and evolution of reproductive modes in Autolytinae (Syllidae, Annelida).

The phylogeny of 31 autolytine taxa (Syllidae, Polychaeta, and Annelida) was estimated based on 16S rDNA and 18S rDNA sequences. Outgroups included 12 non-autolytine syllids and four other annelids from related groups. The phylogeny was used to trace the evolution of the various reproductive strategies (i.e., epigamy, anterior and posterior scissiparity, and gemmiparity) within the group, and it will also serve as a basis for a forthcoming revision of autolytine taxonomy. The two genes were analysed both separately and in combination using parsimony, maximum likelihood, and Bayesian inference. Regardless of method used the combined analysis supported a division of Autolytinae into three major clades: one with epigamous Autolytus; a second comprising Autolytus and Myrianida with posterior scissiparity and gemmiparity; and a third containing Proceraea, Procerastea, and Virchowia with anterior scissiparity. The relationship between these three groups is uncertain. Ancestral reproductive states were reconstructed with parsimony and maximum likelihood, and the results unequivocally support epigamy as the plesiomorphic reproductive mode in Syllidae, and that schizogamy in Syllinae and Autolytinae are separate events. The evolution of reproductive traits is ambiguous within Autolytinae, and either of the different reproductive modes could represent the ancestral state.

Animals↗

PubMedDate not supplied

Setting bounds for the likelihood ratio when multiple hypotheses are postulated.

The interpretation of mixtures of DNA in the forensic context presents particular challenges. The only logical means available for dealing with them is through Bayesian inference, which leads to the formulation, in most cases, of a likelihood ratio which weighs the evidence in favour of two competing hypotheses. However, situations can arise in which additional hypotheses are proposed and the authors discuss one such situation--that where the number of contributors to the mixture is in dispute. A way of dealing with the problem is presented.

Body Fluids↗

PubMedDate not supplied

A model for case assessment and interpretation.

The authors describe a new approach to decision-making in an operational forensic science organization based on a model, embodying the principles of Bayesian inference, which has been developed through workshops run within the Forensic Science Service for forensic science practitioners. Issues which arise from the idea of pre-assessment of cases are explored by means of a case example.

Bayes Theorem↗

PubMed1999

Motion transparency: making models of motion perception transparent.

In daily life our visual system is bombarded with motion information. We see cars driving by, flocks of birds flying in the sky, clouds passing behind trees that are dancing in the wind. Vision science has a good understanding of the first stage of visual motion processing, that is, the mechanism underlying the detection of local motions. Currently, research is focused on the processes that occur beyond the first stage. At this level, local motions have to be integrated to form objects, define the boundaries between them, construct surfaces and so on. An interesting, if complicated case is known as motion transparency: the situation in which two overlapping surfaces move transparently over each other. In that case two motions have to be assigned to the same retinal location. Several researchers have tried to solve this problem from a computational point of view, using physiological and psychophysical results as a guideline. We will discuss two models: one uses the traditional idea known as 'filter selection' and the other a relatively new approach based on Bayesian inference. Predictions from these models are compared with our own visual behaviour and that of the neural substrates that are presumed to underlie these perceptions.

Journal Article↗

PubMed2003

Molecular study of Dermatocarpon miniatum (Verrucariales) and allied taxa.

The phylogeny of the Dermatocarpon miniatum-complex (Verrucariales, lichenized Ascomycota) was studied using nuclear ITS sequence data by both parsimony and Bayesian inference of phylogeny. The ITS region contains a substantial amount of variation which resolves the relationships of terminal groups, while the more basal clades have low support in the analyses. D. miniatum var. miniatum and var. complicatum are polyphyletic, while var. cirsodes is monophyletic but located within the complex, as are both D. leptophyllum and D. linkolae. The variation within the D. miniatum-complex is significantly greater than that between some transatlantic species such as D. luridum and D. meiophyllizum. The new names D. taminium sp. nov. from the Greater Sonoran area, and D. tenue comb. nov. (syn. D. muehlenbergii var. tenue) are introduced.

Ascomycota↗

PubMed2000

A comparison of frailty and other models for bivariate survival data.

Multivariate survival data arise when each study subject may experience multiple events or when study subjects are clustered into groups. Statistical analyses of such data need to account for the intra-cluster dependence through appropriate modeling. Frailty models are the most popular for such failure time data. However, there are other approaches which model the dependence structure directly. In this article, we compare the frailty models for bivariate data with the models based on bivariate exponential and Weibull distributions. Bayesian methods provide a convenient paradigm for comparing the two sets of models we consider. Our techniques are illustrated using two examples. One simulated example demonstrates model choice methods developed in this paper and the other example, based on a practical data set of onset of blindness among patients with diabetic Retinopathy, considers Bayesian inference using different models.

Bayes Theorem↗

PubMed2000

Assessing the impact of managed-care on the distribution of length-of-stay using Bayesian hierarchical models.

Hierarchical models provide a useful framework for the complexities encountered in policy-relevant research in which the impact of social programs is being assessed. Such complexities include multi-site data, censored data and over-dispersion. In this paper, Bayesian inference through Markov Chain Monte Carlo methods is used for the analysis of a complex hierarchical log-normal model that shows the impact of a managed care strategy aimed at limiting length of hospital stays. Parameters in this model allow for variability in baseline length-of-stay as well as the program effect across hospitals. The authors demonstrate elicitation and sensitivity analysis with respect to prior distributions. All calculations for the posterior and predictive distributions were obtained using the software BUGS.

Bayes Theorem↗

PubMed2002

Bayesian methods for missing covariates in cure rate models.

We propose methods for Bayesian inference for missing covariate data with a novel class of semiparametric survival models with a cure fraction. We allow the missing covariates to be either categorical or continuous and specify a parametric distribution for the covariates that is written as a sequence of one dimensional conditional distributions. We assume that the missing covariates are missing at random (MAR) throughout. We propose an informative class of joint prior distributions for the regression coefficients and the parameters arising from the covariate distributions. The proposed class of priors are shown to be useful in recovering information on the missing covariates especially in situations where the missing data fraction is large. Properties of the proposed prior and resulting posterior distributions are examined. Also, model checking techniques are proposed for sensitivity analyses and for checking the goodness of fit of a particular model. Specifically, we extend the Conditional Predictive Ordinate (CPO) statistic to assess goodness of fit in the presence of missing covariate data. Computational techniques using the Gibbs sampler are implemented. A real data set involving a melanoma cancer clinical trial is examined to demonstrate the methodology.

Bayes Theorem↗

PubMed2002

Sorting signals from protein NMR spectra: SPI, a Bayesian protocol for uncovering spin systems.

Grouping of spectral peaks into J-connected spin systems is essential in the analysis of macromolecular NMR data as it provides the basis for disentangling chemical shift degeneracies. It is a mandatory step before resonance and NOESY cross-peak identities can be established. We have developed SPI, a computational protocol that scrutinizes peak lists from homo- and hetero-nuclear multidimensional NMR spectra and progressively assembles sets of resonances into consensus J- and/or NOE-connected spin systems. SPI estimates the likelihood of nuclear spin resonances appearing at defined frequencies given sets of cross-peaks measured from multi-dimensional experiments. It quantifies spin system matching probabilities via Bayesian inference. The protocol takes advantage of redundancies in the number of connectivities revealed by suites of diverse NMR experiments, systematically tracking the adequacy of each grouping hypothesis. SPI was tested on 2D homonuclear and 2D/3D(15)N-edited data recorded from two protein modules, the col 2 domain of matrix metalloproteinase-2 (MMP-2) and the kringle 2 domain of plasminogen, of 60 and 83 amino acid residues, respectively. For these protein domains SPI identifies approximately 95% unambiguous resonance frequencies, a relatively good performance vis-à-vis the reported 'manual' (interactive) analyses. Abbreviations and Acronyms: SPI, SPin Identification; BMRB, BioMagResBank (Madison, WI).

Amino Acid Sequence↗

PubMed2003

Molecular phylogenetic analysis of the Microphalloidea Ward, 1901 (Trematoda: Digenea).

Phylogenetic interrelationships of 32 species belonging to 18 genera and four families of the superfamily Microphalloidea were studied using partial sequences of nuclear lsrDNA analysed by Bayesian inference and maximum parsimony. The resulting trees were well resolved at most nodes and demonstrated that the Microphalloidea, as represented by the present data-set, consists of three main clades corresponding to the families Lecithodendriidae, Microphallidae and Pleurogenidae + Prosthogonimidae. Interrelationships of taxa within each clade are considered; as a result of analysis of molecular and morphological data, Floridatrema Kinsella & Deblock, 1994 is synonymised with Maritrema Nicoll, 1907, Candidotrema Dollfus, 1951 with Pleurogenes Looss, 1896, and Schistogonimus Lühe, 1909 with Prosthogonimus Lühe, 1899. The taxonomic value of some morphological features, used traditionally for the differentiation of genera within the Lecithodendriidae and Prosthogonimidae, is reconsidered. Previous systematic schemes are discussed from the viewpoint of present results, and perspectives of future studies are outlined.

Animals↗

PubMed1999

A general approach to single-nucleotide polymorphism discovery.

Single-nucleotide polymorphisms (SNPs) are the most abundant form of human genetic variation and a resource for mapping complex genetic traits. The large volume of data produced by high-throughput sequencing projects is a rich and largely untapped source of SNPs (refs 2, 3, 4, 5). We present here a unified approach to the discovery of variations in genetic sequence data of arbitrary DNA sources. We propose to use the rapidly emerging genomic sequence as a template on which to layer often unmapped, fragmentary sequence data and to use base quality values to discern true allelic variations from sequencing errors. By taking advantage of the genomic sequence we are able to use simpler yet more accurate methods for sequence organization: fragment clustering, paralogue identification and multiple alignment. We analyse these sequences with a novel, Bayesian inference engine, POLYBAYES, to calculate the probability that a given site is polymorphic. Rigorous treatment of base quality permits completely automated evaluation of the full length of all sequences, without limitations on alignment depth. We demonstrate this approach by accurate SNP predictions in human ESTs aligned to finished and working-draft quality genomic sequences, a data set representative of the typical challenges of sequence-based SNP discovery.

Algorithms↗