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Results for “Likelihood Functions”

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PubMed2001

Quantitative trait locus analysis in crosses between outbred lines with dominance and inbreeding.

We provide a theoretical framework for quantitative trait locus (QTL) analysis of a crossed population where parental lines may be outbred and dominance as well as inbreeding are allowed for. It can be applied to any pedigree. A biallelic QTL is assumed, and the QTL allele frequencies can be different in each breed. The genetic covariance between any two individuals is expressed as a nonlinear function of the probability of up to 15 possible identity modes and of the additive and dominance effects, together with the allelic frequencies in each of the two parental breeds. The probabilities of each identity mode are obtained at the desired genome positions using a Monte Carlo Markov chain method. Unbiased estimates of the actual genetic parameters are recovered in a simulated F(2) cross and in a six-generation complex pedigree under a variety of genetic models (allele fixed or segregating in the parental populations and additive or dominance action). Results from analyzing an F(2) cross between Meishan and Large White pigs are also presented.

Alleles↗

PubMed2000

Association analysis of the proneurotensin gene and bipolar disorder.

Neurotensin (NT) localizes within dopaminergic neurones in the mesocortical, mesolimbic and nigrostriatal systems, and it is now clear that NT can selectively modulate dopaminergic neurotransmission. It has therefore been proposed that altered NT function might contribute to the pathogenesis of neuropsychiatric disorders in which disordered dopaminergic neurotransmission is suspected. We have previously screened the gene encoding NT in a sample of schizophrenic and bipolar subjects, and identified three sequence variants. These have now been tested for association with bipolar disorder using a case-control sample of unrelated bipolar subjects and matched controls. No evidence for association was found, and our data therefore suggest that sequence variation in this gene does not make an important contribution to susceptibility to bipolar disorder.

Adult↗

PubMed1992

Determinants of need and unmet need among cancer patients residing at home.

De-hospitalization of cancer treatment, particularly for those with advanced disease, can complicate adjustment and strain the capacity of caregiver networks to meet patients' daily needs. Outpatient staff should be able to recognize patients who need help to meet their daily needs as well as those who are not getting enough help. This study describes the physiological and social determinants of need and unmet need for assistance among 629 cancer patients with advanced disease initiating a course of outpatient chemotherapy and/or radiation therapy. Areas of needs examined through telephone interviews with participating patients were: personal care, instrumental tasks (housework, shopping, and cooking), and transportation. Physiological factors (metastases, disease stage, and functional status) were associated with need for assistance in all three areas. Also, older age (over 65) and low income predicted need for help with personal care, and women were more likely than men to report illness-related need for assistance with instrumental tasks and transportation. Unmet need was primarily associated with patients' social support system (e.g., children living nearby and perceived resiliency of network helpers). These findings highlight the need for outpatient staff to evaluate patients' informal care resources as well as patients' symptoms and impairments in deciding who should be referred for home care services.

Activities of Daily Living↗

PubMed2004

Phylogenetic investigations of Antarctic notothenioid fishes (Perciformes: Notothenioidei) using complete gene sequences of the mitochondrial encoded 16S rRNA.

The Notothenioidei dominates the fish fauna of the Antarctic in both biomass and diversity. This clade exhibits adaptations related to metabolic function and freezing avoidance in the subzero Antarctic waters, and is characterized by a high degree of morphological and ecological diversity. Investigating the macroevolutionary processes that may have contributed to the radiation of notothenioid fishes requires a well-resolved phylogenetic hypothesis. To date published molecular and morphological hypotheses of notothenioids are largely congruent, however, there are some areas of significant disagreement regarding higher-level relationships. Also, there are critical areas of the notothenioid phylogeny that are unresolved in both molecular and morphological phylogenetic analyses. Previous molecular phylogenetic analyses of notothenioids using partial mtDNA 12S and 16S rRNA sequence data have resulted in limited phylogenetic resolution and relatively low node support. One particularly controversial result from these analyses is the paraphyly of the Nototheniidae, the most diverse family in the Notothenioidei. It is unclear if the phylogenetic results from the 12S and 16S partial gene sequence dataset are due to limited character sampling, or if they reflect patterns of evolutionary diversification in notothenioids. We sequenced the complete mtDNA 16S rRNA gene for 43 notothenioid species, the largest sampling to-date from all eight taxonomically recognized families. Phylogenetic analyses using both maximum parsimony and maximum likelihood resulted in well-resolved trees with most nodes supported with high bootstrap pseudoreplicate scores and significant Bayesian posterior probabilities. In all analyses the Nototheniidae was monophyletic. Shimodaira-Hasegawa tests were able to reject two hypotheses that resulted from prior morphological analyses. However, despite substantial resolution and node support in the 16S rRNA trees, several phylogenetic hypotheses among closely related species and clades were not rejected. The inability to reject particular hypotheses among species in apical clades is likely due to the lower rate of nucleotide substitution in mtDNA rRNA genes relative to protein coding regions. Nevertheless, with the most extensive notothenioid taxon sampling to date, and the much greater phylogenetic resolution offered by the complete 16S rRNA sequences over the commonly used partial 12S and 16S gene dataset, it would be advantageous for future molecular investigations of notothenioid phylogenetics to utilize at the minimum the complete gene 16S rRNA dataset.

Animals↗

PubMed2003

Chemistry. The motions of an enzyme soloist.

Dynamics of proteins are crucial to their function. In his Perspective, Orrit stresses the advantages of studying these dynamics with single-molecule methods--which require no synchronization--rather than with conventional ensemble measurements. He highlights the report by Yang et al., who follow the fluorescence of a single enzyme molecule. Electron transfer from the fluorophore to a quencher induces fluctuations of the fluorescence lifetime along with the fluorophore-quencher distance. The wide range of characteristic times of those fluctuations reveals the complexity of the protein's potential energy landscape. As a new molecular ruler, electron transfer complements other single-molecule methods such as energy transfer (FRET) for distances shorter than a few nanometers.

Catalysis↗

PubMedDate not supplied

Continuous trees and NEVADA simulation: a quadrature approach to modeling continuous random variables in decision analysis.

This paper introduces an improved technique for modeling risk and decision problems that have continuous random variables and probabilistic dependence. Variables are modeled with mixtures of four-parameter random variables, called "continuous trees." Functions of random variables are calculated using gaussian quadrature in a manner called "Nevada simulation" (NumErical Integration of Variance And probabilistic Dependence Analyzer). This technique is compared with traditional decision-tree modeling in terms of analytic technique, solution-time complexity, and accuracy. Nevada simulation takes advantage of the probabilistic independence in a decision problem while allowing for probabilistic dependence to achieve polynomial computational-time complexity for many decision problems. It improves on the accuracy of traditional decision trees by employing larger approximations than traditional decision analysis. It improves on traditional decision analysis by modeling continuous variables with continuous, rather than discrete, distributions. A Bayesian analysis using a mixed discrete-continuous probability distribution for cigarette smoking rate is presented.

Algorithms↗

PubMed2002

Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task.

Decisions about the visual world can take time to form, especially when information is unreliable. We studied the neural correlate of gradual decision formation by recording activity from the lateral intraparietal cortex (area LIP) of rhesus monkeys during a combined motion-discrimination reaction-time task. Monkeys reported the direction of random-dot motion by making an eye movement to one of two peripheral choice targets, one of which was within the response field of the neuron. We varied the difficulty of the task and measured both the accuracy of direction discrimination and the time required to reach a decision. Both the accuracy and speed of decisions increased as a function of motion strength. During the period of decision formation, the epoch between onset of visual motion and the initiation of the eye movement response, LIP neurons underwent ramp-like changes in their discharge rate that predicted the monkey's decision. A steeper rise in spike rate was associated with stronger stimulus motion and shorter reaction times. The observations suggest that neurons in LIP integrate time-varying signals that originate in the extrastriate visual cortex, accumulating evidence for or against a specific behavioral response. A threshold level of LIP activity appears to mark the completion of the decision process and to govern the tradeoff between accuracy and speed of perception.

Action Potentials↗

PubMedDate not supplied

Power determination for geographically clustered data using generalized estimating equations.

Study designs in public health research often require the estimation of intervention effects that have been applied to a cluster of subjects in a common geographic area, rather than randomly assigned to individual subjects, and where the outcome is dichotomous. Statistical methods that account for the intracluster correlation of measurements must be used or the standard errors of regression coefficients will be under-estimated. Generalized estimating equations (GEE) can be used to account for this correlation, although there are no straightforward methods to determine sample-size requirements for adequate power. A simulation study was performed to calculate power in a GEE model for a proposed study of the effect of an intervention, designed to reduce lower-back injuries among nursing personnel employed in nursing homes. Nursing homes will be randomly assigned to either an intervention or control group and all employees within a nursing home will be treated alike. Historical injury data indicates that the baseline-injury risk for each home can be reasonably modelled using a beta distribution. It is assumed that the risk for any individual nurse within a nursing home follows a Bernoulli probability distribution expressed as a logit function of fixed covariates, which have values of odds ratios determined from previous studies which represent characteristics of the study population, and a random-intercept term which is specific for each home. Results indicate that failure to account for intracluster correlation can lead to overestimates of power as well as inflation of type I error by as much as 20 per cent. Although the GEE method accounted for the intracluster correlation when present, estimates of the intracluster correlation were negatively biased when no intracluster correlation was present. In addition, and possibly related to the negatively biased estimates of intracluster correlation, we also found inflated type I error estimates from the GEE method.

Algorithms↗

PubMed2005

Haplotype effects on human survival: logistic regression models applied to unphased genotype data.

Haplotype based linkage disequilibrium (LD) mapping exhibits higher power than the single locus approach because it makes use of the LD information contained in the flanking markers. New statistical methods have been proposed to help to infer haplotype effects on human diseases using multi-locus genotype data collected from unrelated individuals. In this paper, we introduce a statistical procedure for measuring haplotype effects on human survival using the popular logistic regression model with haplotype based parameterizations. By modeling haplotype frequency as a function of age, our model infers haplotype effects by estimating and testing the slope parameters under different genetic mechanisms (multiplicative, dominant, or recessive). In addition, by estimating the sex-specific slope parameters, our model allows the detection of sex-specific haplotype effects or haplotype-sex interactions. As an example, we apply our model to an empirical dataset on a stress related gene, interleukin-6, to look for haplotypes that affect individual survival and for haplotype-sex interactions. We show that our logistic regression based haplotype model can be a helpful tool for researchers interested in the genetics of human aging and longevity.

Female↗

PubMedDate not supplied

Flexible modelling in survival analysis. Structuring biological complexity from the information provided by tumor markers.

The aim of the present article is to introduce and discuss the problem of optimal modelling of the prognostic information provided by putative prognostic variables, possibly measured on a quantitative scale. A number of methodological aspects will be treated, with particular reference to the role of spline functions and artificial neural networks, which will be discussed in the context of the analysis of survival data. The problem of the evaluation and the choice of the optimal statistical models will be examined, with particular attention to the critical aspects related to the definition of prognostic indexes on the basis of the results of the selected models. Clinical examples in breast cancer on the evaluation of the prognostic impact of several tumor markers are provided. This paper is addressed to all researchers who are interested in the evaluation of the prognostic role of tumor markers, therefore we will stress the necessity of integrating the methodologies of biological, clinical and statistical research in the assessment of prognosis.

Biomarkers, Tumor↗

PubMed1999

Genes, demography, and life span: the contribution of demographic data in genetic studies on aging and longevity.

In population studies on aging, the data on genetic markers are often collected for individuals from different age groups. The purpose of such studies is to identify, by comparison of the frequencies of selected genotypes, "longevity" or "frailty" genes in the oldest and in younger groups of individuals. To address questions about more-complicated aspects of genetic influence on longevity, additional information must be used. In this article, we show that the use of demographic information, together with data on genetic markers, allows us to calculate hazard rates, relative risks, and survival functions for respective genes or genotypes. New methods of combining genetic and demographic information are discussed. These methods are tested on simulated data and then are applied to the analysis of data on genetic markers for two haplogroups of human mtDNA. The approaches suggested in this article provide a powerful tool for analyzing the influence of candidate genes on longevity and survival. We also show how factors such as changes in the initial frequencies of candidate genes in subsequent cohorts, or secular trends in cohort mortality, may influence the results of an analysis.

Aging↗

PubMed1998

Independent effects of Alzheimer's disease on neuropsychological functioning.

A new analytical procedure, single common factor analysis, was carried out on the data from a relatively large sample of normals (n = 101) and patients with Alzheimer's disease (AD; n = 180) to examine the extent to which there were independent effects of disease status on different neuropsychological variables. This technique uses structural equation methods to determine what all of the variables have in common, and then controls this common factor when examining the relationship between diagnostic group and each individual test variable. To the extent that AD represents the sum of independent breakdowns of different information processing domains, then there should be sets of variables that have weak or nonexistent links to the other variables. However, the results revealed that a large proportion of the AD-related effects on test scores was shared and was not independent of the AD-related effects on other variables.

Aged↗

PubMed2000

Composite statistics for QTL mapping with moderately discordant sibling pairs.

Extreme discordant sibling-pair (EDSP) designs have been shown in theory to be very powerful for mapping quantitative-trait loci (QTLs) in humans. However, their practical applicability has been somewhat limited by the need to phenotype very large populations to find enough pairs that are extremely discordant. In this paper, we demonstrate that there is also substantial power in pairs that are only moderately discordant, and that designs using moderately discordant pairs can yield a more practical balance between phenotyping and genotyping efforts. The power we demonstrate for moderately discordant pairs stems from a new statistical result. Statistical analysis in discordant-pair studies is generally done by testing for reduced identity by descent (IBD) sharing in the pairs. By contrast, the most commonly-used statistical methods for more standard QTL mapping are Haseman-Elston regression and variance-components analysis. Both of these use statistics that are functions of the trait values given IBD information for the pedigree. We show that IBD sharing statistics and "trait value given IBD" statistics contribute complementary rather than redundant information, and thus that statistics of the two types can be combined to form more powerful tests of linkage. We propose a simple composite statistic, and test it with simulation studies. The simulation results show that our composite statistic increases power only minimally for extremely discordant pairs. However, it boosts the power of moderately discordant pairs substantially and makes them a very practical alternative. Our composite statistic is straightforward to calculate with existing software; we give a practical example of its use by applying it to a Genetic Analysis Workshop (GAW) data set.

Chromosome Mapping↗

PubMed1991

The structure of self-reported physical health among the aged in the United States and Japan.

This article attempts to extend the generalizability of a three-dimensional model of self-reported physical health among the aged to a nonwestern culture. Consisting of three interrelated dimensions, chronic illness, functional status, and self-rated health, this model was empirically evaluated by using national data on the aged gathered in the United States and Japan. The three-dimensional specification was found to apply equally well to U.S. and Japanese elderly. In addition to examining the internal structure of this three-dimensional model, the study assessed the model's relationships with a set of selected exogenous variables including age, sex, marital status, and education. The relationships between the selected exogenous variables and physical health dimensions are largely similar in both countries. However, clear differences appeared in at least three instances.

Activities of Daily Living↗

PubMed2004

Multivariate character process models for the analysis of two or more correlated function-valued traits.

Various methods, including random regression, structured antedependence models, and character process models, have been proposed for the genetic analysis of longitudinal data and other function-valued traits. For univariate problems, the character process models have been shown to perform well in comparison to alternative methods. The aim of this article is to present an extension of these models to the simultaneous analysis of two or more correlated function-valued traits. Analytical forms for stationary and nonstationary cross-covariance functions are studied. Comparisons with the other approaches are presented in a simulation study and in an example of a bivariate analysis of genetic covariance in age-specific fecundity and mortality in Drosophila. As in the univariate case, bivariate character process models with an exponential correlation were found to be quite close to first-order structured antedependence models. The simulation study showed that the choice of the most appropriate methodology is highly dependent on the covariance structure of the data. The bivariate character process approach proved to be able to deal with quite complex nonstationary and nonsymmetric cross-correlation structures and was found to be the most appropriate for the real data example of the fruit fly Drosophila melanogaster.

Age Factors↗

PubMed2004

Comparative evolutionary histories of chitinase genes in the Genus zea and Family poaceae.

Patterns of DNA sequence diversity vary widely among genes encoding proteins that protect plants against pathogens and herbivores. Comparative studies may help determine whether these differences are due to the strength of selection acting on different types of defense, in different evolutionary lineages, or both. I analyzed sequence diversity at three chitinases, a well-studied component of defense, in two species of Zea and several Poaceae taxa. Although the Zea species are closely related and these genes code for proteins with similar biochemical function, patterns of diversity vary widely within and among species. Intraspecific diversity at chiB, chiI, and Z. mays ssp. parviglumis chiA are consistent with a neutral-equilibrium model whereas chiA had no segregating sites within Z. diploperennis--consistent with a recent and strong selective sweep. Codons identified as having diverged among Poaceae taxa in response to positive selection were significantly overrepresented among targets of selection in Arabis, suggesting common responses to selection in distantly related plant taxa. Divergence of the recent duplicates chiA and chiB is consistent with positive selection but relaxed constraint cannot be rejected. Weak evidence for adaptive divergence of these duplicated downstream components of defense contrasts with strong evidence for adaptive divergence of genes involved in pathogen recognition.

Amino Acid Sequence↗

PubMed2000

The Beta Poisson dose-response model is not a single-hit model.

The choice of a dose-response model is decisive for the outcome of quantitative risk assessment. Single-hit models have played a prominent role in dose-response assessment for pathogenic microorganisms, since their introduction. Hit theory models are based on a few simple concepts that are attractive for their clarity and plausibility. These models, in particular the Beta Poisson model, are used for extrapolation of experimental dose-response data to low doses, as are often present in drinking water or food products. Unfortunately, the Beta Poisson model, as it is used throughout the microbial risk literature, is an approximation whose validity is not widely known. The exact functional relation is numerically complex, especially for use in optimization or uncertainty analysis. Here it is shown that although the discrepancy between the Beta Poisson formula and the exact function is not very large for many data sets, the differences are greatest at low doses--the region of interest for many risk applications. Errors may become very large, however, in the results of uncertainty analysis, or when the data contain little low-dose information. One striking property of the exact single-hit model is that it has a maximum risk curve, limiting the upper confidence level of the dose-response relation. This is due to the fact that the risk cannot exceed the probability of exposure, a property that is not retained in the Beta Poisson approximation. This maximum possible response curve is important for uncertainty analysis, and for risk assessment of pathogens with unknown properties.

Algorithms↗

PubMed2007

Bayesian parallel imaging with edge-preserving priors.

Existing parallel MRI methods are limited by a fundamental trade-off in that suppressing noise introduces aliasing artifacts. Bayesian methods with an appropriately chosen image prior offer a promising alternative; however, previous methods with spatial priors assume that intensities vary smoothly over the entire image, resulting in blurred edges. Here we introduce an edge-preserving prior (EPP) that instead assumes that intensities are piecewise smooth, and propose a new approach to efficiently compute its Bayesian estimate. The estimation task is formulated as an optimization problem that requires a nonconvex objective function to be minimized in a space with thousands of dimensions. As a result, traditional continuous minimization methods cannot be applied. This optimization task is closely related to some problems in the field of computer vision for which discrete optimization methods have been developed in the last few years. We adapt these algorithms, which are based on graph cuts, to address our optimization problem. The results of several parallel imaging experiments on brain and torso regions performed under challenging conditions with high acceleration factors are shown and compared with the results of conventional sensitivity encoding (SENSE) methods. An empirical analysis indicates that the proposed method visually improves overall quality compared to conventional methods.

Algorithms↗