Robustness assessment of whole bacterial genome segmentations

Comparison of closely related bacterial genomes has revealed the presence of highly conserved sequences forming a "backbone" that is interrupted by numerous, less conserved, DNA fragments. Segmentation of bacterial genomes into backbone and variable regions is particularly useful to investigate, among other things, bacterial genome evolution. Several software tools have been designed to compare complete bacterial chromosomes and a few online databases store pre-computed genome comparisons. However, very few statistical methods are available to evaluate the reliability of these software tools and to compare the results obtained with them. To fill this gap, we have developed two local scores to measure the robustness of bacterial genome segmentations. Our method uses a simulation procedure based on random perturbations of the compared genomes. The two scores described in this article provide useful information and are easy to implement, and their interpretation is intuitive. We show that they are suited to discriminate between robust and non-robust segmentations when genome aligners such as MAUVE and MGA are used.     

An efficient computational method for calculating ligand binding affinities

Virtual compound screening using molecular docking is widely used in the discovery of new lead compounds for drug design. However, the docking scores are not sufficiently precise to represent the protein-ligand binding affinity. Here, we developed an efficient computational method for calculating protein-ligand binding affinity, which is based on molecular mechanics generalized Born/surface area (MM-GBSA) calculations and Jarzynski identity. Jarzynski identity is an exact relation between free energy differences and the work done through non-equilibrium process, and MM-GBSA is a semimacroscopic approach to calculate the potential energy. To calculate the work distribution when a ligand is pulled out of its binding site, multiple protein-ligand conformations are randomly generated as an alternative to performing an explicit single-molecule pulling simulation. We assessed the new method, multiple random conformation/MM-GBSA (MRC-MMGBSA), by evaluating ligand-binding affinities (scores) for four target proteins, and comparing these scores with experimental data. The calculated scores were qualitatively in good agreement with the experimental binding affinities, and the optimal docking structure could be determined by ranking the scores of the multiple docking poses obtained by the molecular docking process. Furthermore, the scores showed a strong linear response to experimental binding free energies, so that the free energy difference of the ligand binding (ΔΔG) could be calculated by linear scaling of the scores. The error of calculated ΔΔG was within ≈±1.5 kcal•mol⁻¹ of the experimental values. Particularly, in the case of flexible target proteins, the MRC-MMGBSA scores were more effective in ranking ligands than those generated by the MM-GBSA method using a single protein-ligand conformation. The results suggest that, owing to its lower computational costs and greater accuracy, the MRC-MMGBSA offers efficient means to rank the ligands, in the post-docking process, according to their binding affinities, and to compare these directly with the experimental values.     

The Accuracy of Computerized Adaptive Testing in Heterogeneous Populations: A Mixture Item-Response Theory Analysis

Background

Computerized adaptive testing (CAT) utilizes latent variable measurement model parameters that are typically assumed to be equivalently applicable to all people. Biased latent variable scores may be obtained in samples that are heterogeneous with respect to a specified measurement model. We examined the implications of sample heterogeneity with respect to CAT-predicted patient-reported outcomes (PRO) scores for the measurement of pain.

Methods

A latent variable mixture modeling (LVMM) analysis was conducted using data collected from a heterogeneous sample of people in British Columbia, Canada, who were administered the 36 pain domain items of the CAT-5D-QOL. The fitted LVMM was then used to produce data for a simulation analysis. We evaluated bias by comparing the referent PRO scores of the LVMM with PRO scores predicted by a “conventional” CAT (ignoring heterogeneity) and a LVMM-based “mixture” CAT (accommodating heterogeneity).

Results

The LVMM analysis indicated support for three latent classes with class proportions of 0.25, 0.30 and 0.45, which suggests that the sample was heterogeneous. The simulation analyses revealed differences between the referent PRO scores and the PRO scores produced by the “conventional” CAT. The “mixture” CAT produced PRO scores that were nearly equivalent to the referent scores.

Conclusion

Bias in PRO scores based on latent variable models may result when population heterogeneity is ignored. Improved accuracy could be obtained by using CATs that are parameterized using LVMM.     

Discrete Delta Estimation of the Variance of the Logistic Scores Estimator of ED50

A discrete delta method is applied to estimation of the standard error of the logistic scores estimator of ED50 in quantal bioassay. Results of a simulation study suggest that the standard error estimator is useful for assessing the precision of the ED50 estimate and for interval estimation of ED50.     

Analysis of HIV Using a High Resolution Melting (HRM) Diversity Assay: Automation of HRM Data Analysis Enhances the Utility of the Assay for Analysis of HIV Incidence

Background

HIV diversity may be a useful biomarker for discriminating between recent and non-recent HIV infection. The high resolution melting (HRM) diversity assay was developed to quantify HIV diversity in viral populations without sequencing. In this assay, HIV diversity is expressed as a single numeric HRM score that represents the width of a melting peak. HRM scores are highly associated with diversity measures obtained with next generation sequencing. In this report, a software package, the HRM Diversity Assay Analysis Tool (DivMelt), was developed to automate calculation of HRM scores from melting curve data.

Methods

DivMelt uses computational algorithms to calculate HRM scores by identifying the start (T1) and end (T2) melting temperatures for a DNA sample and subtracting them (T2–T1 = HRM score). DivMelt contains many user-supplied analysis parameters to allow analyses to be tailored to different contexts. DivMelt analysis options were optimized to discriminate between recent and non-recent HIV infection and to maximize HRM score reproducibility. HRM scores calculated using DivMelt were compared to HRM scores obtained using a manual method that is based on visual inspection of DNA melting curves.

Results

HRM scores generated with DivMelt agreed with manually generated HRM scores obtained from the same DNA melting data. Optimal parameters for discriminating between recent and non-recent HIV infection were identified. DivMelt provided greater discrimination between recent and non-recent HIV infection than the manual method.

Conclusion

DivMelt provides a rapid, accurate method of determining HRM scores from melting curve data, facilitating use of the HRM diversity assay for large-scale studies.     

Estimating mean cost using auxiliary covariates

We study the estimation of mean medical cost when censoring is dependent and a large amount of auxiliary information is present. Under missing at random assumption, we propose semiparametric working models to obtain low-dimensional summarized scores. An estimator for the mean total cost can be derived nonparametrically conditional on the summarized scores. We show that when either the two working models for cost-survival process or the model for censoring distribution is correct, the estimator is consistent and asymptotically normal. Small-sample performance of the proposed method is evaluated via simulation studies. Finally, our approach is applied to analyze a real data set in health economics.     

Determination of component volumes of lipid bilayers from simulations.

An efficient method for extracting volumetric data from simulations is developed. The method is illustrated using a recent atomic-level molecular dynamics simulation of L alpha phase 1,2-dipalmitoyl-sn-glycero-3-phosphocholine bilayer. Results from this simulation are obtained for the volumes of water (VW), lipid (V1), chain methylenes (V2), chain terminal methyls (V3), and lipid headgroups (VH), including separate volumes for carboxyl (Vcoo), glyceryl (Vgl), phosphoryl (VPO4), and choline (Vchol) groups. The method assumes only that each group has the same average volume regardless of its location in the bilayer, and this assumption is then tested with the current simulation. The volumes obtained agree well with the values VW and VL that have been obtained directly from experiment, as well as with the volumes VH, V2, and V3 that require certain assumptions in addition to the experimental data. This method should help to support and refine some assumptions that are necessary when interpreting experimental data.     

Helix propensities of short peptides: molecular dynamics versus bioinformatics

Knowledge-based potential functions for protein structure prediction assume that the frequency of occurrence of a given structure or a contact in the protein database is a measure of its free energy. Here, we put this assumption to test by comparing the results obtained from sequence-structure cluster analysis with those obtained from long all-atom molecular dynamics simulations. Sixty-four eight-residue peptide sequences with varying degrees of similarity to the canonical sequence pattern for amphipathic helix were drawn from known protein structures, regardless of whether they were helical in the protein. Each was simulated using AMBER6.0 for at least 10 ns using explicit waters. The total simulation time was 1176 ns. The resulting trajectories were tested for reproducibility, and the helical content was measured. Natural peptides whose sequences matched the amphipathic helix motif with greater than 50% confidence were significantly more likely to form helix during the course of the simulation than peptides with lower confidence scores. The sequence pattern derived from the simulation data closely resembles the motif pattern derived from the database cluster analysis. The difficulties encountered in sampling conformational space and sequence space simultaneously are discussed.     

Exploring 3D structure of human gonadotropin hormone receptor at antagonist state using homology modeling,molecular dynamic simulation,and cross-docking studies

Human gonadotropin hormone receptor, a G-protein coupled receptor, is the target of many medications used in fertility disorders. Obtaining more structural information about the receptor could be useful in many studies related to drug design. In this study, the structure of human gonadotropin receptor was subjected to homology modeling studies and molecular dynamic simulation within a DPPC lipid bilayer for 100 ns. Several frames were thereafter extracted from simulation trajectories representing the receptor at different states. In order to find a proper model of the receptor at the antagonist state, all frames were subjected to cross-docking studies of some antagonists with known experimental values (Ki). Frame 194 revealed a reasonable correlation between docking calculated energy scores and experimental activity values (|r|?=?0.91). The obtained correlation was validated by means of SSLR and showed the presence of no chance correlation for the obtained model. Different structural features reported for the receptor, such as two disulfide bridges and ionic lock between GLU90 and LYS 121 were also investigated in the final model.     

The relative effectiveness of teaching methods on pupils' understanding of the classification of living organisms at two levels of intelligence

A classification task, involving the sorting of pictures of plants and animals into major orders and classes, and a standardised test of general intelligence, were administered to randomly selected groups of 12 year old pupils drawn from four comprehensive schools. Sub-samples were selected at random of pupils of above and below average intelligence who had been taught classification either by the “Nuffield” approach or by a “traditional” method. Analysis of variance of the scores obtained showed that although the achievement of the upper intelligence group was superior (1 %level) to that of the lower intelligence group, there was a significant interaction (5 % level) between the method of teaching that had been received and intellectual level. Pupils of above average intelligence generally obtained higher scores when they had been taught by the “Nuffield” method, whereas the achievement of pupils of below average intelligence was generally much greater when they had been taught by a “traditional” method.     

Calculation of conformational free energies by confinement simulations in explicit water with implicit desolvation

Abstract

The confinement method is a robust and conceptually simple free energy simulation method that allows the calculation of conformational free energy differences between highly dissimilar states. Application of the method to explicitly solvated systems requires a multi-stage simulation protocol for the calculation of desolvation free energies. Here we show that these desolvation free energies can be readily obtained from an implicit treatment, which is simpler and less costly. The accuracy and robustness of this protocol was shown by the calculation of conformational free energy differences of a series of explicitly solvated test systems. Given the accuracy and ease by which these free energy differences were obtained, the confinement method is promising for the treatment of conformational changes in large and complex systems.     

Titration of botulinum antitoxin of low levels by the score method

Botulinum antitoxin is commonly titrated by injecting a mixture of toxin and antitoxin into mice and by utilizing deaths as a marker to measure the amount of unneutralized toxin. We attempted to titrate antitoxin by converting the severity of symptoms (notably palsy) and time-to-death in days into scores. In neutralization tests with toxin levels at 5.9 LD50 and 23.5 LD50, a linear relationship was obtained for antitoxin dose in a range between 0.03 to 0.003 IU/ml. Statistical analysis showed that homogeneity of variance or slope was not denied for the scores obtained on any day from the first to the fourth days after injection, demonstrating that this method can titrate accurately antitoxin of such a low level as 0.003 IU/ml within 4 days after injection.     

Goodman et al.'s method for augmenting the number of nucleotide substitutions

Summary Statistical properties of Goodman et al.'s (1974) method of compensating for undetected nucleotide substitutions in evolution are investigated by using computer simulation. It is found that the method tends to overcompensate when the stochastic error of the number of nucleotide substitutions is large. Furthermore, the estimate of the number of nucleotide substitutions obtained by this method has a large variance. However, in order to see whether this method gives overcompensation when applied together with the maximum parsimony method, a much larger scale of simulation seems to be necessary.     

The continual reassessment method for multiple toxicity grades: a Bayesian quasi-likelihood approach

We consider the case of phase I trials for treatment of cancer or other severe diseases in which grade information is available about the severity of toxicity. Most dose allocation procedures dichotomize toxicity grades based on being dose limiting, which may not work well for severe and possibly irreversible toxicities such as renal, liver, and neurological toxicities, or toxicities with long duration. We propose a simple extension to the continual reassessment method (CRM), called the Quasi-CRM, to incorporate grade information. Toxicity grades are first converted to numeric scores that reflect their impacts on the dose allocation procedure, and then incorporated into the CRM using the quasi-Bernoulli likelihood. A simulation study demonstrates that the Quasi-CRM is superior to the standard CRM and comparable to a univariate version of the Bekele and Thall method (2004, Journal of the American Statistical Association 99, 26-35). We also present sensitivity analysis of the new method with respect to toxicity scores, and discuss practical issues such as extending the simple algorithmic up-and-down designs.     

Finite element modeling of the breakage behavior of agricultural biomass pellets under different heights during handling and storage

It is very important to determine the amount of mechanical damage to biomass pellets during handling, transportation, and storage. However, it is difficult to determine the amount of damage to biomass pellets caused by existing external forces. However, a useful method is the finite element methods, which can be used in different engineering fields to simulate the posture of the material under defined boundary conditions. In this research, a drop test simulation of biomass pellet samples was performed by using the finite element method. An experimental study (compressive test) was carried out to measure some mechanical properties of the sample and use the obtained data in the finite element method simulation. The stress–strain curve of different biomass pellets was determined. Yield strength, Poisson’s ratio, ultimate strength and modulus of elasticity, and stress were identified. In the end, the maximum equivalent stress, highest contact force (generated normal force from target surface at impact), and shape of deformation of samples at impact were obtained from simulation results. The drop scenario was created with 25 steps after the impact site, and the FEM simulation was solved. The maximum stress value was 9.486 MPa, and the maximum generated force was 485.31 N. at step 8 of the FEM simulation. When the stress magnitudes were assessed, simulation outputs indicated that simulation stress values are inconsistent with experimental data.     

A randomization test for controlling population stratification in whole-genome association studies

Population stratification can be a serious obstacle in the analysis of genomewide association studies. We propose a method for evaluating the significance of association scores in whole-genome cohorts with stratification. Our approach is a randomization test akin to a standard permutation test. It conditions on the genotype matrix and thus takes into account not only the population structure but also the complex linkage disequilibrium structure of the genome. As we show in simulation experiments, our method achieves higher power and significantly better control over false-positive rates than do existing methods. In addition, it can be easily applied to whole-genome association studies.     

Application of data quality assessment methods to an LCA of electricity generation

Background, Goal and Scope  For the life cycle assessment (LCA) tool to provide maximum benefit for decision makers, the uncertainty of its results should be reported. Several methods for assessing uncertainty have been developed, but despite recent efforts, there remains disagreement about their merits. Objectives  The objectives of the study were to review several assessment methods for estimating numerical and qualitative uncertainty of impact scores and recommend an appropriate uncertainty assessment scheme. The methods review has been conducted on the basis of an LCA case study regarding the comparison of the use of either brown or black coals in Australian electricity generation. Results and Discussion  Each assessment method indicated greater uncertainty in the impact scores calculated for black coal use than for brown coal use. Due to overlap of the uncertainty ranges in calculated impact scores neither of the coals could be regarded environmentally preferred. Conclusions  Both qualitative and quantitative methods were found to provide useful information about the uncertainty of calculated impact scores for the case study. Methods that combine qualitative and quantitative uncertainty provided no additional benefits, and obscured much of the information gained from using qualitative methods. Recommendation and Outlook  It is recommended that LCA results should include separate numerical (using Monte-Carlo simulation) and qualitative uncertainty assessments. When the ranges of calculated impact scores for compared options overlap, the normalised difference method is recommended.     

TLINKAGE-IMPRINT: a model-based approach to performing two-locus genetic imprinting analysis

OBJECTIVES: Imprinting refers to the expression of only one copy of a gene pair, which is determined by the parental origin of the copy. Imprinted genes play a role in the development of several complex diseases, including cancers and mental disorders. In certain situations, two-trait-loci models are shown to be more powerful than one-trait-locus models. However, no current methods use pedigree structure efficiently and perform two-locus imprinting analyses. In this paper, we apply the Elston-Stewart algorithm to the parametric two-trait-loci imprinting model used by Strauch et al. [2000] to obtain a method for qualitative trait linkage analyses that explicitly models imprinting and can be applied to large pedigrees. METHODS: We considered a parametric approach based on 4 x 4 penetrance matrix to account for imprinting and modified TLINKAGE software to implement this approach. We performed simulation studies using a small and a large pedigree under dominant and imprinted and dominant or imprinted scenarios. Furthermore, we developed a likelihood ratio-based test for imprinting that compares the logarithm of odds (LOD) score obtained using the two-locus imprinting model with that obtained using the standard two-locus model that does not allow for imprinting. RESULTS: In simulation studies of three scenarios where the true mode of inheritance included imprinting, accurate modeling through the proposed approach yielded higher LOD scores and better recombination fraction estimates than the traditional two-locus model that does not allow for imprinting. CONCLUSIONS: This imprinting model will be useful in identifying the genes responsible for several complex disorders that are potentially caused by a combination of imprinted and non-imprinted genes.     

Weighted scores method for regression models with dependent data

There are copula-based statistical models in the literature for regression with dependent data such as clustered and longitudinal overdispersed counts, for which parameter estimation and inference are straightforward. For situations where the main interest is in the regression and other univariate parameters and not the dependence, we propose a "weighted scores method", which is based on weighting score functions of the univariate margins. The weight matrices are obtained initially fitting a discretized multivariate normal distribution, which admits a wide range of dependence. The general methodology is applied to negative binomial regression models. Asymptotic and small-sample efficiency calculations show that our method is robust and nearly as efficient as maximum likelihood for fully specified copula models. An illustrative example is given to show the use of our weighted scores method to analyze utilization of health care based on family characteristics.     

CLUSTAL: a package for performing multiple sequence alignment on a microcomputer

An approach for performing multiple alignments of large numbers of amino acid or nucleotide sequences is described. The method is based on first deriving a phylogenetic tree from a matrix of all pairwise sequence similarity scores, obtained using a fast pairwise alignment algorithm. Then the multiple alignment is achieved from a series of pairwise alignments of clusters of sequences, following the order of branching in the tree. The method is sufficiently fast and economical with memory to be easily implemented on a microcomputer, and yet the results obtained are comparable to those from packages requiring mainframe computer facilities.