Survival regression models with dependent Bayesian nonparametric priors

We present a novel Bayesian nonparametric model for regression in survival analysis. Our model builds on the classical neutral to the right model of Doksum (1974) and on the Cox proportional hazards model of Kim and Lee (2003). The use of a vector of dependent Bayesian nonparametric priors allows us to efficiently model the hazard as a function of covariates whilst allowing nonproportionality. The model can be seen as having competing latent risks. We characterize the posterior of the underlying dependent vector of completely random measures and study the asymptotic behavior of the model. We show how an MCMC scheme can provide Bayesian inference for posterior means and credible intervals. The method is illustrated using simulated and real data

Application of site and haplotype-frequency based approaches for detecting selection signatures in cattle

<p>Abstract</p> <p>Background</p> <p>'Selection signatures' delimit regions of the genome that are, or have been, functionally important and have therefore been under either natural or artificial selection. In this study, two different and complementary methods--integrated Haplotype Homozygosity Score (|iHS|) and population differentiation index (F_ST)--were applied to identify traces of decades of intensive artificial selection for traits of economic importance in modern cattle.</p> <p>Results</p> <p>We scanned the genome of a diverse set of dairy and beef breeds from Germany, Canada and Australia genotyped with a 50 K SNP panel. Across breeds, a total of 109 extreme |iHS| values exceeded the empirical threshold level of 5% with 19, 27, 9, 10 and 17 outliers in Holstein, Brown Swiss, Australian Angus, Hereford and Simmental, respectively. Annotating the regions harboring clustered |iHS| signals revealed a panel of interesting candidate genes like SPATA17, MGAT1, PGRMC2 and ACTC1, COL23A1, MATN2, respectively, in the context of reproduction and muscle formation. In a further step, a new Bayesian F_ST-based approach was applied with a set of geographically separated populations including Holstein, Brown Swiss, Simmental, North American Angus and Piedmontese for detecting differentiated loci. In total, 127 regions exceeding the 2.5 per cent threshold of the empirical posterior distribution were identified as extremely differentiated. In a substantial number (56 out of 127 cases) the extreme F_STvalues were found to be positioned in poor gene content regions which deviated significantly (p < 0.05) from the expectation assuming a random distribution. However, significant F_STvalues were found in regions of some relevant genes such as SMCP and FGF1.</p> <p>Conclusions</p> <p>Overall, 236 regions putatively subject to recent positive selection in the cattle genome were detected. Both |iHS| and F_STsuggested selection in the vicinity of the Sialic acid binding Ig-like lectin 5 gene on BTA18. This region was recently reported to be a major QTL with strong effects on productive life and fertility traits in Holstein cattle. We conclude that high-resolution genome scans of selection signatures can be used to identify genomic regions contributing to within- and inter-breed phenotypic variation.</p

Doctors under the microscope: the birth of medical audit

In 1989 a UK government White Paper introduced medical audit as a comprehensive and statutory system of assessment and improvement in quality of care in hospitals. A considerable body of research has described the evolution of medical audit in terms of a struggle between doctors and National Health Service managers over control of quality assurance. In this paper we examine the emergence of medical audit from 1910 to the early 1950s, with a particular focus on the pioneering work of the American surgeons Codman, MacEachern and Ponton. It is contended that medical professionals initially created medical audit in order to articulate a suitable methodology for assessing individual and organisational performance. Rather than a means of protecting the medical profession from public scrutiny, medical auditing was conceived and operationalised as a managerial tool for fostering the active engagement of senior hospital managers and discharging public accountability. These early debates reveal how accounting was implicated in the development of a system for monitoring and improving the work of medical professionals, advancing the quality of hospital care, and was advocated in ways, which included rather than excluded managers

The genomic architecture of resistance to Campylobacter jejuni intestinal colonisation in chickens

Campylobacter is the leading cause of foodborne diarrhoeal illness in humans and is mostly acquired from consumption or handling of contaminated poultry meat. In the absence of effective licensed vaccines and inhibitors, selection for chickens with increased resistance to Campylobacter could potentially reduce its subsequent entry into the food chain. Campylobacter intestinal colonisation levels are influenced by the host genetics of the chicken. In the present study, two chicken populations were used to investigate the genetic architecture of avian resistance to colonisation: (i) a back-cross of two White Leghorn derived inbred lines [(61 x N) x N] known to differ in resistance to Campylobacter colonisation and (ii) a 9th generation advanced intercross (61 x N) line

Analysis of paediatric visual acuity using Bayesian copula models with sinh-arcsinh marginal densities

We analyse paediatric ophthalmic data from a large sample of children aged between 3 and 8 years. We modify the Bayesian additive conditional bivariate copula regression model of Klein and Kneib [1] by using sinh-arcsinh marginal densities with location, scale and shape parameters that depend smoothly on a covariate. We perform Bayesian inference about the unknown quantities of our model using a specially tailored Markov chain Monte Carlo algorithm. We gain new insights about the processes which determine transformations in visual acuity with respect to age, including the nature of joint changes in both eyes as modelled with the age-related copula dependence parameter. We analyse posterior predictive distributions to identify children with unusual sight characteristics, distinguishing those who are bivariate, but not univariate outliers. In this way we provide an innovative tool that enables clinicians to identify children with unusual sight who may otherwise be missed. We compare our simultaneous Bayesian method with the two-step frequentist generalized additive modelling approach of Vatter and Chavez-Demoulin [2]