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.

Effects of a sex-ratio distorting endosymbiont on mtDNA variation in a global insect pest

Background: Patterns of mtDNA variation within a species reflect long-term population structure, but may also be influenced by maternally inherited endosymbionts, such as Wolbachia. These bacteria often alter host reproductive biology and can drive particular mtDNA haplotypes through populations. We investigated the impacts of Wolbachia infection and geography on mtDNA variation in the diamondback moth, a major global pest whose geographic distribution reflects both natural processes and transport via human agricultural activities. Results: The mtDNA phylogeny of 95 individuals sampled from 10 countries on four continents revealed two major clades. One contained only Wolbachia-infected individuals from Malaysia and Kenya, while the other contained only uninfected individuals, from all countries including Malaysia and Kenya. Within the uninfected group was a further clade containing all individuals from Australasia and displaying very limited sequence variation. In contrast, a biparental nuclear gene phylogeny did not have infected and uninfected clades, supporting the notion that maternally-inherited Wolbachia are responsible for the mtDNA pattern. Only about 5% (15/306) of our global sample of individuals was infected with the plutWBI isolate and even within infected local populations, many insects were uninfected. Comparisons of infected and uninfected isofemale lines revealed that plutWBI is associated with sex ratio distortion. Uninfected lines have a 1:1 sex ratio, while infected ones show a 2:1 female bias. Conclusion: The main correlate of mtDNA variation in P. xylostella is presence or absence of the plutWBI infection. This is associated with substantial sex ratio distortion and the underlying mechanisms deserve further study. In contrast, geographic origin is a poor predictor of moth mtDNA sequences, reflecting human activity in moving the insects around the globe. The exception is a clade of Australasian individuals, which may reflect a bottleneck during their recent introduction to this region.

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.

Use of a novel Hill-climbing genetic algorithm in protein folding simulations

We have developed a novel Hill-climbing genetic algorithm (GA) for simulation of protein folding. The program (written in C) builds a set of Cartesian points to represent an unfolded polypeptide's backbone. The dihedral angles determining the chain's configuration are stored in an array of chromosome structures that is copied and then mutated. The fitness of the mutated chain's configuration is determined by its radius of gyration. A four-helix bundle was used to optimise simulation conditions, and the program was compared with other, larger, genetic algorithms on a variety of structures. The program ran 50% faster than other GA programs. Overall, tests on 100 non-redundant structures gave comparable results to other genetic algorithms, with the Hill-climbing program running from between 20 and 50% faster. Examples including crambin, cytochrome c, cytochrome B and hemerythrin gave good secondary structure fits with overall alpha carbon atom rms deviations of between 5 and 5.6 Angstrom with an optimised hydrophobic term in the fitness function. (C) 2003 Elsevier Ltd. All rights reserved.

Chromatographic alignment of LC-MS and LC-MS/MS datasets by genetic algorithm feature extraction

Liquid chromatography-mass spectrometry (LC-MS) datasets can be compared or combined following chromatographic alignment. Here we describe a simple solution to the specific problem of aligning one LC-MS dataset and one LC-MS/MS dataset, acquired on separate instruments from an enzymatic digest of a protein mixture, using feature extraction and a genetic algorithm. First, the LC-MS dataset is searched within a few ppm of the calculated theoretical masses of peptides confidently identified by LC-MS/MS. A piecewise linear function is then fitted to these matched peptides using a genetic algorithm with a fitness function that is insensitive to incorrect matches but sufficiently flexible to adapt to the discrete shifts common when comparing LC datasets. We demonstrate the utility of this method by aligning ion trap LC-MS/MS data with accurate LC-MS data from an FTICR mass spectrometer and show how hybrid datasets can improve peptide and protein identification by combining the speed of the ion trap with the mass accuracy of the FTICR, similar to using a hybrid ion trap-FTICR instrument. We also show that the high resolving power of FTICR can improve precision and linear dynamic range in quantitative proteomics. The alignment software, msalign, is freely available as open source.

Exposing the myth of the 1:5:200 ratio relating initial cost, maintenance and staffing costs of office buildings

In an attempt to focus clients' minds on the importance of considering the construction and maintenance costs of a commercial office building (both as a factor in staff productivity and as a fraction of lifetime staff costs) there is an often-quoted ratio of costs of 1:5:200, where for every one pound spent on construction cost, five are spent on maintenance and building operating costs and 200 on staffing and business operating costs. This seems to stem from a paper published by the Royal Academy of Engineering, in which no data is given and no derivation or defence of the ratio appears. The accompanying belief that higher quality design and construction increases staff productivity, and simultaneously reduces maintenance costs, how ever laudable, appears unsupported by research, and carries all the hallmarks of an "urban myth". In tracking down data about real buildings, a more realistic ratio appears to depend on a huge variety of variables, as well as the definition of the number of "lifetime" years. The ill-defined origins of the original ratio (1:5:200) describing these variables have made replication impossible. However, by using published sources of data, we have found that for three office buildings, a more realistic ratio is 1:0.4:12. As there is nothing in the public domain about what comprised the original research that gave rise to 1:5:200, it is not possible to make a true comparison between these new calculations and the originals. Clients and construction professionals stand to be misled because the popularity and widespread use of the wrong ratio appears to be mis-informing important investment and policy decisions.

UK Food Standards Agency workshop report: the effects of the dietary n-6 : n-3 fatty acid ratio on cardiovascular health

This report summarises a workshop convened by the UK Food Standards Agency (FSA) on 11 September 2006 to review the results of three FSA-funded studies and other recent research on effects of the dietary n-6:n-3 fatty acid ratio on cardiovascular health. The objective of this workshop was to reach a clear conclusion on whether or not it was worth funding any further research in this area. On the basis of this review of the experimental evidence and on theoretical grounds, it was concluded that the n-6:n-3 fatty acid ratio is not a useful concept and that it distracts attention away from increasing absolute intakes of long-chain n-3 fatty acids which have been shown to have beneficial effects on cardiovascular health. Other markers of fatty acid intake, that more closely relate to physiological function, may be more useful.

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.

Effects of variation in the palm stearin: palm olein ratio on the crystallisation of a low-trans shortening

Changes in the theological properties during crystallisation and in the crystal size and morphology of blends containing rapeseed oil with varying percentages of palm stearin (POs) and palm olein (POf) have been studied. The crystals formed from all three blends were studied by confocal laser scanning microscopy, light microscopy and environmental scanning electron microscopy, which revealed the development of clusters of 3-5 individual elementary "spherulites" in the early stages of crystallisation. The saturated triacylglycerol content of the solid crystals separated at the onset of crystallisation was much greater than that in the total fat. Fat blends with a higher content of palm stearin had a more rapid nucleation rate when observed by light microscopy, and this caused an earlier change in the rheological properties of the fat during crystallisation. Using a low torque amplitude (0.005 Pa, which was within the linear viscoelastic region of all samples studied) and a frequency of 1 Hz, the viscoelastic properties of melted fat during cooling were studied. All samples, prior to crystallisation, showed weak viscoelastic liquid behaviour (G '', loss modulus >G', storage modulus). After crystallisation a more "solid like" behaviour was observed (G' similar to or greater than G ''). The blend having the highest concentration of POs was found to have the earliest onset of crystallisation (27% w/w POs; 12 mins, 22% w/w POs; 13.5 mins, 17% w/w POs, 15 mins, respectively). However, there were no significant differences in the time to the point when G' became greater than G' among the three blends. (c) 2006 Elsevier Ltd. All rights reserved.

Variable step LMS algorithm using the accumulated instantaneous error concept

The convergence speed of the standard Least Mean Square adaptive array may be degraded in mobile communication environments. Different conventional variable step size LMS algorithms were proposed to enhance the convergence speed while maintaining low steady state error. In this paper, a new variable step LMS algorithm, using the accumulated instantaneous error concept is proposed. In the proposed algorithm, the accumulated instantaneous error is used to update the step size parameter of standard LMS is varied. Simulation results show that the proposed algorithm is simpler and yields better performance than conventional variable step LMS.

Unsupervised genetic algorithm deployed for intrusion detection

This paper represents the first step in an on-going work for designing an unsupervised method based on genetic algorithm for intrusion detection. Its main role in a broader system is to notify of an unusual traffic and in that way provide the possibility of detecting unknown attacks. Most of the machine-learning techniques deployed for intrusion detection are supervised as these techniques are generally more accurate, but this implies the need of labeling the data for training and testing which is time-consuming and error-prone. Hence, our goal is to devise an anomaly detector which would be unsupervised, but at the same time robust and accurate. Genetic algorithms are robust and able to avoid getting stuck in local optima, unlike the rest of clustering techniques. The model is verified on KDD99 benchmark dataset, generating a solution competitive with the solutions of the state-of-the-art which demonstrates high possibilities of the proposed method.

A new algorithm for OFDM joint data detection and phase noise cancellation

This paper proposes a new iterative algorithm for OFDM joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the problem of "overfitting" such that the iterative approach may converge to a trivial solution. Although it is essential for this joint approach, the overfitting problem was relatively less studied in existing algorithms. In this paper, specifically, we apply a hard decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the phase noise, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical simulations are also given to verify the proposed algorithm.

A sparse kernel density estimation algorithm using forward constrained regression

Using the classical Parzen window (PW) estimate as the target function, the sparse kernel density estimator is constructed in a forward constrained regression manner. The leave-one-out (LOO) test score is used for kernel selection. The jackknife parameter estimator subject to positivity constraint check is used for the parameter estimation of a single parameter at each forward step. As such the proposed approach is simple to implement and the associated computational cost is very low. An illustrative example is employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with comparable accuracy to that of the classical Parzen window estimate.

An on-line algorithm of uncertain time delay estimation in a continuous system

In this paper, we present an on-line estimation algorithm for an uncertain time delay in a continuous system based on the observational input-output data, subject to observational noise. The first order Pade approximation is used to approximate the time delay. At each time step, the algorithm combines the well known Kalman filter algorithm and the recursive instrumental variable least squares (RIVLS) algorithm in cascade form. The instrumental variable least squares algorithm is used in order to achieve the consistency of the delay parameter estimate, since an error-in-the-variable model is involved. An illustrative example is utilized to demonstrate the efficacy of the proposed approach.