A likelihood ratio appropach to family-based association studies with covariates

We introduce a procedure for association based analysis of nuclear families that allows for dichotomous and more general measurements of phenotype and inclusion of covariate information. Standard generalized linear models are used to relate phenotype and its predictors. Our test procedure, based on the likelihood ratio, unifies the estimation of all parameters through the likelihood itself and yields maximum likelihood estimates of the genetic relative risk and interaction parameters. Our method has advantages in modelling the covariate and gene-covariate interaction terms over recently proposed conditional score tests that include covariate information via a two-stage modelling approach. We apply our method in a study of human systemic lupus erythematosus and the C-reactive protein that includes sex as a covariate.

Active-control trials with binary data: a comparison of methods for testing superiority or non-inferiority using the odds ratio

This paper considers methods for testing for superiority or non-inferiority in active-control trials with binary data, when the relative treatment effect is expressed as an odds ratio. Three asymptotic tests for the log-odds ratio based on the unconditional binary likelihood are presented, namely the likelihood ratio, Wald and score tests. All three tests can be implemented straightforwardly in standard statistical software packages, as can the corresponding confidence intervals. Simulations indicate that the three alternatives are similar in terms of the Type I error, with values close to the nominal level. However, when the non-inferiority margin becomes large, the score test slightly exceeds the nominal level. In general, the highest power is obtained from the score test, although all three tests are similar and the observed differences in power are not of practical importance. Copyright (C) 2007 John Wiley & Sons, Ltd.

The use of image analysis to estimate population growth rate in Daphnia magna

1. Population growth rate (PGR) is central to the theory of population ecology and is crucial for projecting population trends in conservation biology, pest management and wildlife harvesting. Furthermore, PGR is increasingly used to assess the effects of stressors. Image analysis that can automatically count and measure photographed individuals offers a potential methodology for estimating PGR. 2. This study evaluated two ways in which the PGR of Daphnia magna, exposed to different stressors, can be estimated using an image analysis system. The first method estimated PGR as the ratio of counts of individuals obtained at two different times, while the second method estimated PGR as the ratio of population sizes at two different times, where size is measured by the sum of the individuals' surface areas, i.e. total population surface area. This method is attractive if surface area is correlated with reproductive value (RV), as it is for D. magna, because of the theoretical result that PGR is the rate at which the population RV increases. 3. The image analysis system proved reliable and reproducible in counting populations of up to 440 individuals in 5 L of water. Image counts correlated well with manual counts but with a systematic underestimate of about 30%. This does not affect accuracy when estimating PGR as the ratio of two counts. Area estimates of PGR correlated well with count estimates, but were systematically higher, possibly reflecting their greater accuracy in the study situation. 4. Analysis of relevant scenarios suggested the correlation between RV and body size will generally be good for organisms in which fecundity correlates with body size. In these circumstances, area estimation of PGR is theoretically better than count estimation. 5. Synthesis and applications. There are both theoretical and practical advantages to area estimation of population growth rate when individuals' reproductive values are consistently well correlated with their surface areas. Because stressors may affect both the number and quality of individuals, area estimation of population growth rate should improve the accuracy of predicting stress impacts at the population level.

Linkage disequilibrium assessment via log-linear modeling of SNP haplotype frequencies

Analyses of high-density single-nucleotide polymorphism (SNP) data, such as genetic mapping and linkage disequilibrium (LD) studies, require phase-known haplotypes to allow for the correlation between tightly linked loci. However, current SNP genotyping technology cannot determine phase, which must be inferred statistically. In this paper, we present a new Bayesian Markov chain Monte Carlo (MCMC) algorithm for population haplotype frequency estimation, particulary in the context of LD assessment. The novel feature of the method is the incorporation of a log-linear prior model for population haplotype frequencies. We present simulations to suggest that 1) the log-linear prior model is more appropriate than the standard coalescent process in the presence of recombination (>0.02cM between adjacent loci), and 2) there is substantial inflation in measures of LD obtained by a "two-stage" approach to the analysis by treating the "best" haplotype configuration as correct, without regard to uncertainty in the recombination process. Genet Epidemiol 25:106-114, 2003. (C) 2003 Wiley-Liss, Inc.

Interaction of the D-2short dopamine receptor with G proteins: analysis of receptor G protein selectivity

The human D-2short (D-2S) dopamine receptor has been expressed together with the G proteins Gi2 and Go in insect cells using the baculovirus system. Levels of receptor were determined using [H-3]spiperone binding. Levels of G protein heterotrimer were determined using quantitative Western blot and using [S-35]GTPgammaS saturation binding experiments. Levels of the receptor and G protein and the receptor/G protein ratio were similar in the two preparations. Stimulation of [S-35]GTPgammaS binding by a range of agonists occurred with higher relative efficacy and in some cases higher potency in the preparation expressing Go, indicating that interaction of the D-2S receptor is more efficient with this G protein. The effects of various G protein-selective agents on 10,11-dihydroxy-N-n-propylnorapomorphine ([H-3]NPA) binding were used to examine the receptor/G protein complex in the two preparations. Suramin inhibited [H-3]NPA binding with slightly higher potency in the Gi2 preparation, whereas GppNHp inhibited [H-3]NPA binding with greater potency (similar to6-fold) in the Go preparation. This may imply that the G protein is more readily activated in the D-2S/Go preparation. [H-3]Spiperone binding occurred with an increased B-max in the presence of suramin in the Go preparation but not in the Gi2 preparation, suggesting a higher affinity interaction between the free receptor and this G protein. It is concluded that the higher efficiency activation of Go by the D-2S receptor may be a function of higher affinity receptor/G protein interaction as well as a greater ability to activate the G protein. (C) 2003 Elsevier Science Inc. All rights reserved.

Identification of stimulatory and inhibitory inputs to the hypothalamic-pituitary-adrenal axis during hypoglycaemia or transport in ewes

This study used the novel approach of statistical modelling to investigate the control of hypothalamic-pituitary-adrenal (HPA) axis and quantify temporal relationships between hormones. Two experimental paradigms were chosen, insulin-induced hypoglycaemia and 2 h transport, to assess differences in control between noncognitive and cognitive stimuli. Vasopressin and corticotropin-releasing hormone (CRH) were measured in hypophysial portal plasma, and adrenocorticotropin hormone (ACTH) and cortisol in jugular plasma of conscious sheep, and deconvolution analysis was used to calculate secretory rates, before modelling. During hypoglycaemia, the relationship between plasma glucose and vasopressin or CRH was best described by log(10) transforming variables (i.e. a positive power-curve relationship). A negative-feedback relationship with log(10) cortisol concentration 2 h previously was detected. Analysis of the 'transport' stimulus suggested that the strength of the perceived stimulus decreased over time after accounting for cortisol facilitation and negative-feedback. The time course of vasopressin and CRH responses to each stimulus were different However, at the pituitary level, the data suggested that log(10) ACTH secretion rate was related to log(10) vasopressin and CRH concentrations with very similar regression coefficients and an identical ratio of actions (2.3 : 1) for both stimuli. Similar magnitude negative-feedback effects of log(10) cortisol at -110 min (hypoglycaemia) or -40 min (transport) were detected, and both models contained a stimulatory relationship with cortisol at 0 min (facilitation). At adrenal gland level, cortisol secretory rates were related to simultaneously measured untransformed ACTH concentration but the regression coefficient for the hypoglycaemia model was 2.5-fold greater than for transport. No individual sustained maximum cortisol secretion for longer than 20 min during hypoglycaemia and 40 min during transport. These unique models demonstrate that corticosteroid negative-feedback is a significant control mechanism at both the pituitary and hypothalamus. The amplitude of HPA response may be related to stimulus intensity and corticosteroid negative-feedback, while duration depended on feedback alone.

Analysis of the SDS-lysozyme binding isotherm

A scheme to describe SDS-lysozyme complex formation has been proposed on the basis of isothermal titration calorimetry (ITC) and FTIR spectroscopy data. ITC isotherms are convoluted and reveal a marked effect of both SDS and lysozyme concentration on the stoichiometry of the SDS-lysozyme complex. The binding isotherms have been described with the aid of FTIR spectroscopy in terms of changes in the lysozyme structure and the nature of the SDS binding. At low SDS concentrations, ITC isotherms feature an exothermic region that corresponds to specific electrostatic binding of SDS to positively charged amino acid residues on the lysozyme surface. This leads to charge neutralization of the complex and precipitation. The number of SDS molecules that bind specifically to lysozyme is approximately 8, as determined from our ITC isotherms, and is independent of lysozyme solution concentration. At high SDS concentrations, hydrophobic cooperative association dominates the binding process. Saturated binding stoichiometries as a molar ratio of SDS per molecule of lysozyme range from 220: 1 to 80: 1, depending on the lysozyme solution concentration. A limiting value of 78: 1 has been calculated for lysozyme solution concentrations above 0.25 mM.

A study of the effect of heat source location in a ventilated room using multiple regression analysis

Multiple regression analysis is a statistical technique which allows to predict a dependent variable from m ore than one independent variable and also to determine influential independent variables. Using experimental data, in this study the multiple regression analysis is applied to predict the room mean velocity and determine the most influencing parameters on the velocity. More than 120 experiments for four different heat source locations were carried out in a test chamber with a high level wall mounted air supply terminal at air change rates 3-6 ach. The influence of the environmental parameters such as supply air momentum, room heat load, Archimedes number and local temperature ratio, were examined by two methods: a simple regression analysis incorporated into scatter matrix plots and multiple stepwise regression analysis. It is concluded that, when a heat source is located along the jet centre line, the supply momentum mainly influences the room mean velocity regardless of the plume strength. However, when the heat source is located outside the jet region, the local temperature ratio (the inverse of the local heat removal effectiveness) is a major influencing parameter.

Influence of environmental stress on distributions of times to first division in Escherichia coli populations, as determined by digital-image analysis of individual cells

The distributions of times to first cell division were determined for populations of Escherichia coli stationary-phase cells inoculated onto agar media. This was accomplished by using automated analysis of digital images of individual cells growing on agar and calculation of the "box area ratio." Using approximately 300 cells per experiment, the mean time to first division and standard deviation for cells grown in liquid medium at 37 degrees C and inoculated on agar and incubated at 20 degrees C were determined as 3.0 h and 0.7 h, respectively. Distributions were observed to tail toward the higher values, but no definitive model distribution was identified. Both preinoculation stress by heating cultures at 50 degrees C and postinoculation stress by growth in the presence of higher concentrations of NaCl increased mean times to first division. Both stresses also resulted in an increase in the spread of the distributions that was proportional to the mean division time, the coefficient of variation being constant at approximately 0.2 in all cases. The "relative division time," which is the time to first division for individual cells expressed in terms of the cell size doubling time, was used as measure of the "work to be done" to prepare for cell division. Relative division times were greater for heat-stressed cells than for those growing under osmotic stress.

A novel method for measuring lag times in division of individual bacterial cells using image analysis

A method is presented for determining the time to first division of individual bacterial cells growing on agar media. Bacteria were inoculated onto agar-coated slides and viewed by phase-contrast microscopy. Digital images of the growing bacteria were captured at intervals and the time to first division estimated by calculating the "box area ratio". This is the area of the smallest rectangle that can be drawn around an object, divided by the area of the object itself. The box area ratios of cells were found to increase suddenly during growth at a time that correlated with cell division as estimated by visual inspection of the digital images. This was caused by a change in the orientation of the two daughter cells that occurred when sufficient flexibility arose at their point of attachment. This method was used successfully to generate lag time distributions for populations of Escherichia coli, Listeria monocytogenes and Pseudomonas aeruginosa, but did not work with the coccoid organism Staphylococcus aureus. This method provides an objective measure of the time to first cell division, whilst automation of the data processing allows a large number of cells to be examined per experiment. (c) 2005 Elsevier B.V. All rights reserved.

Lack of effect of dietary n-6 : n-3 PUFA ratio on plasma lipids and markers of insulin responses in Indian Asians living in the UK

Background: Indian Asians living in Western Countries have an over 50% increased risk of coronary heart disease (CHD) relative to their Caucasians counterparts. The atherogenic lipoprotein phenotype (ALP), which is more prevalent in this ethnic group, may in part explain the increased risk. A low dietary long chain n-3 fatty acid (LC n-3 PUFA) intake and a high dietary n-6 PUFA intake and n-6:n-3 PUFA ratio in Indian Asians have been proposed as contributors to the increased ALP incidence and CHD risk in this subgroup. Aim: To examine the impact of dietary n-6:n-3 PUFA ratio on membrane fatty acid composition, blood lipid levels and markers of insulin sensitivity in Indian Asians living in the UK. Methods: Twenty-nine males were assigned to either a moderate or high n-6:n-3 PUFA (9 or 16) diet for 6 weeks. Fasting blood samples were collected at baseline and 6 weeks for analysis of triglycerides, total-, LDL- and HDL- cholesterol, non-esterified fatty acids, glucose, insulin, markers of insulin sensitivity and C-reactive protein. Results: Group mean saturated fatty acid, MUFA, n-6 PUFA and n-3 PUFA on the moderate and high n-6:n-3 PUFA diets were 26 g/d, 43 g/d, 15 g/d, 2 g/d and 25 g/d, 25 g/d, 28 g/d, 2 g/d respectively. A significantly lower total membrane n-3 PUFA and a trend towards lower EPA and DHA levels were observed following the high n-6:n-3 PUFA diet. However no significant effect of treatment on plasma lipids was evident. There was a trend towards a loss of insulin sensitivity on the high n-6:n-3 PUFA diet, with the increase in fasting insulin (P = 0.04) and HOMA IR [(insulin x glucose)/22.5] (P = 0.02) reaching significance. Conclusion: The results of the current study suggest that, within the context of a western diet, it is unlikely that dietary n-6:n-3 PUFA ratio has any major impact on the levels of LC n-3 PUFA in membrane phospholipids or have any major clinically relevant impact on insulin sensitivity and its associated dyslipidaemia.

A tool for replay and analysis of gaze-enhanced multiparty sessions captured in immersive collaborative environments

A desktop tool for replay and analysis of gaze-enhanced multiparty virtual collaborative sessions is described. We linked three CAVE (TM)-like environments, creating a multiparty collaborative virtual space where avatars are animated with 3D gaze as well as head and hand motions in real time. Log files are recorded for subsequent playback and analysis Using the proposed software tool. During replaying the user can rotate the viewpoint and navigate in the simulated 3D scene. The playback mechanism relies on multiple distributed log files captured at every site. This structure enables an observer to experience latencies of movement and information transfer for every site as this is important fir conversation analysis. Playback uses an event-replay algorithm, modified to allow fast traversal of the scene by selective rendering of nodes, and to simulate fast random access. The tool's is analysis module can show each participant's 3D gaze points and areas where gaze has been concentrated.

Slogger: a profiling and analysis system based on semantic web technologies

Increasingly, distributed systems are being used to host all manner of applications. While these platforms provide a relatively cheap and effective means of executing applications, so far there has been little work in developing tools and utilities that can help application developers understand problems with the supporting software, or the executing applications. To fully understand why an application executing on a distributed system is not behaving as would be expected it is important that not only the application, but also the underlying middleware, and the operating system are analysed too, otherwise issues could be missed and certainly overall performance profiling and fault diagnoses would be harder to understand. We believe that one approach to profiling and the analysis of distributed systems and the associated applications is via the plethora of log files generated at runtime. In this paper we report on a system (Slogger), that utilises various emerging Semantic Web technologies to gather the heterogeneous log files generated by the various layers in a distributed system and unify them in common data store. Once unified, the log data can be queried and visualised in order to highlight potential problems or issues that may be occurring in the supporting software or the application itself.

Verification of cloud-fraction forecasts

Cloud radar and lidar can be used to evaluate the skill of numerical weather prediction models in forecasting the timing and placement of clouds, but care must be taken in choosing the appropriate metric of skill to use due to the non- Gaussian nature of cloud-fraction distributions. We compare the properties of a number of different verification measures and conclude that of existing measures the Log of Odds Ratio is the most suitable for cloud fraction. We also propose a new measure, the Symmetric Extreme Dependency Score, which has very attractive properties, being equitable (for large samples), difficult to hedge and independent of the frequency of occurrence of the quantity being verified. We then use data from five European ground-based sites and seven forecast models, processed using the ‘Cloudnet’ analysis system, to investigate the dependence of forecast skill on cloud fraction threshold (for binary skill scores), height, horizontal scale and (for the Met Office and German Weather Service models) forecast lead time. The models are found to be least skillful at predicting the timing and placement of boundary-layer clouds and most skilful at predicting mid-level clouds, although in the latter case they tend to underestimate mean cloud fraction when cloud is present. It is found that skill decreases approximately inverse-exponentially with forecast lead time, enabling a forecast ‘half-life’ to be estimated. When considering the skill of instantaneous model snapshots, we find typical values ranging between 2.5 and 4.5 days. Copyright c 2009 Royal Meteorological Society

Characterising the variability and extremes of the stratospheric polar vortices using 2D moment analysis

The mean state, variability and extreme variability of the stratospheric polar vortices, with an emphasis on the Northern Hemisphere vortex, are examined using 2-dimensional moment analysis and Extreme Value Theory (EVT). The use of moments as an analysis to ol gives rise to information about the vortex area, centroid latitude, aspect ratio and kurtosis. The application of EVT to these moment derived quantaties allows the extreme variability of the vortex to be assessed. The data used for this study is ECMWF ERA-40 potential vorticity fields on interpolated isentropic surfaces that range from 450K-1450K. Analyses show that the most extreme vortex variability occurs most commonly in late January and early February, consistent with when most planetary wave driving from the troposphere is observed. Composites around sudden stratospheric warming (SSW) events reveal that the moment diagnostics evolve in statistically different ways between vortex splitting events and vortex displacement events, in contrast to the traditional diagnostics. Histograms of the vortex diagnostics on the 850K (∼10hPa) surface over the 1958-2001 period are fitted with parametric distributions, and show that SSW events comprise the majority of data in the tails of the distributions. The distribution of each diagnostic is computed on various surfaces throughout the depth of the stratosphere, and shows that in general the vortex becomes more circular with higher filamentation at the upper levels. The Northern Hemisphere (NH) and Southern Hemisphere (SH) vortices are also compared through the analysis of their respective vortex diagnostics, and confirm that the SH vortex is less variable and lacks extreme events compared to the NH vortex. Finally extreme value theory is used to statistically mo del the vortex diagnostics and make inferences about the underlying dynamics of the polar vortices.