Methods and results from the genome-wide association group at GAW20

Background

X chromosome inactivation (XCI) is an important gene regulation mechanism in females to equalize the expression levels of X chromosome between two sexes. Generally, one of two X chromosomes in females is randomly chosen to be inactivated. Nonrandom XCI (XCI skewing) is also observed in females, which has been reported to play an important role in many X-linked diseases. However, there is no statistical measure available for the degree of the XCI skewing based on family data in population genetics.

Results

In this article, we propose a statistical approach to measure the degree of the XCI skewing based on family trios, which is represented by a ratio of two genotypic relative risks in females. The point estimate of the ratio is obtained from the maximum likelihood estimates of two genotypic relative risks. When parental genotypes are missing in some family trios, the expectation-conditional-maximization algorithm is adopted to obtain the corresponding maximum likelihood estimates. Further, the confidence interval of the ratio is derived based on the likelihood ratio test. Simulation results show that the likelihood-based confidence interval has an accurate coverage probability under the situations considered. Also, we apply our proposed method to the rheumatoid arthritis data from USA for its practical use, and find out that a locus, rs2238907, may undergo the XCI skewing against the at-risk allele. But this needs to be further confirmed by molecular genetics.

Conclusions

The proposed statistical measure for the skewness of XCI is applicable to complete family trio data or family trio data with some paternal genotypes missing. The likelihood-based confidence interval has an accurate coverage probability under the situations considered. Therefore, our proposed statistical measure is generally recommended in practice for discovering the potential loci which undergo the XCI skewing.

     

A scale to measure microbehaviors of oral contraceptive pill use

The ways in which contraceptive methods are actually used is of increasing interest to researchers, clinicians, and policy makers. Although contraceptive "use" has multiple dimensions, existing indicators measure only one aspect of use or combine unidimensional measures to produce a questionable pastiche. This study uses a subsample of 612 respondents from a larger study of first-time patients at a public-health-department family planning clinic to develop a new measure. Psychometric properties of this measure are examined and discussed.     

The number needed to treat: a clinically useful measure of treatment effect.

The relative benefit of an active treatment over a control is usually expressed as the relative risk, the relative risk reduction, or the odds ratio. These measures are used extensively in both clinical and epidemiological investigations. For clinical decision making, however, it is more meaningful to use the measure "number needed to treat." This measure is calculated on the inverse of the absolute risk reduction. It has the advantage that it conveys both statistical and clinical significance to the doctor. Furthermore, it can be used to extrapolate published findings to a patient at an arbitrary specified baseline risk when the relative risk reduction associated with treatment is constant for all levels of risk.     

Principal components analysis as an evaluation and classification tool for lower torso sEMG data

The use of univariate statistical techniques on multivariate electromyography data can fail to uncover important relationships between variables. Principal components analysis (PCA) is a multivariate statistical technique that can be used as a data exploration tool, both by classifying participants and simplifying data structures. Past research using this technique has focused on discriminating between "patients" and "normals". This investigation explored the use of PCA on electromyography data from healthy participants, with the objective of elucidating any between-participant differences in the multivariate patterns of muscle coactivation. Results indicated that, even between healthy participants, quantitative and qualitative differences in muscle coactivation patterns exist and that, in the context of the lower torso, a large portion (>70%) of the empirically determined muscle activation could be synthesized in a theoretical three-parameter control model.     

On Measures of Gametic Disequilibrium

Various measures have been proposed for characterizing the statistical association that arises between alleles at different loci. Hedrick has compared these measures with the standardized measure D' proposed by Lewontin on the grounds that this latter measure is independent of allele frequency. Although D' has the same range for all allelic frequencies, in fact, D' is not "independent" of allele frequency, and no measure with that general property is possible for the multilocus association problem. The insolubility of this problem arises from the ill-defined nature of general "association."     

Phylogenetic signal, evolutionary process, and rate

A recent advance in the phylogenetic comparative analysis of continuous traits has been explicit, model-based measurement of "phylogenetic signal" in data sets composed of observations collected from species related by a phylogenetic tree. Phylogenetic signal is a measure of the statistical dependence among species' trait values due to their phylogenetic relationships. Although phylogenetic signal is a measure of pattern (statistical dependence), there has nonetheless been a widespread propensity in the literature to attribute this pattern to aspects of the evolutionary process or rate. This may be due, in part, to the perception that high evolutionary rate necessarily results in low phylogenetic signal; and, conversely, that low evolutionary rate or stabilizing selection results in high phylogenetic signal (due to the resulting high resemblance between related species). In this study, we use individual-based numerical simulations on stochastic phylogenetic trees to clarify the relationship between phylogenetic signal, rate, and evolutionary process. Under the simplest model for quantitative trait evolution, homogeneous rate genetic drift, there is no relation between evolutionary rate and phylogenetic signal. For other circumstances, such as functional constraint, fluctuating selection, niche conservatism, and evolutionary heterogeneity, the relationship between process, rate, and phylogenetic signal is complex. For these reasons, we recommend against interpretations of evolutionary process or rate based on estimates of phylogenetic signal.     

Measuring the number of co-dominants in ecological communities

We suggest a concept that allows the objective determination of the number of co-dominants in a community. We define co-dominants as a subset of species that are more abundant and more uniformly distributed than other species in a given sample. We compare the sample with a model community and use Simpsons diversity index to estimate the apparent number of co-dominants. Dominant species determined in this way are responsible for 70–90% of the total measure of abundance in the sample. The statistical significance of the apparent number of co-dominants may be assessed by a randomization test.     

An application of autocorrelation methods to the interpretation of intestinal motility records

The application of statistical communication techniques to the analysis of intestinal motility records has made available certain information that has heretofore been obscure. This information is: 1. A measure of total activity expressed in square millimeters of Hg. 2. The frequency and amplitude of segmental activity. 3. A measure of the random variations in the amplitude of the "segmental" waves. 4. A measure of random activity and the range and relative amplitudes of the frequencies making up this component.     

Leukemia-related morphological features in blast cells

This paper investigates the use of image-processing methods to detect leukemia-related morphological differences in mononuclear blast cells. Routinely prepared Pappenheim-stained blood smears were scanned in a high-resolution color TV-microscope system. Eleven blast-cell classes (OMSBC, T-ALL, OMS, ALL, LBL, IBL, AUL, AML, AMOL, AMMOL, and CML) were analyzed with the nonparametric statistical software program "Classification and Regression Trees" (CART). This paper documents the initial statistical evaluation of 62 leukemia-related morphological features that directly measure and analyze the cell-related quantifiable differences occurring in the various blast cells. The 62 cell image features include both common cytophotometric features, and new texture and color features developed for this project. This study found that each leukemia specimen contains a dominant class of blasts that correlates with the specific leukemia, plus a distribution of blasts from related diseases. The present data suggest the existence of a distribution fingerprint pattern for each leukemia.     

An investigation of the phase locking index for measuring of interdependency of cortical source signals recorded in the EEG

The phase locking index (PLI) was introduced to quantify in a statistical sense the phase synchronization of two signals. It has been commonly used to process biosignals. In this article, we investigate the PLI for measuring the interdependency of cortical source signals (CSSs) recorded in the Electroencephalogram (EEG). To this end, we consider simple analytical models for the mapping of simulated CSSs into the EEG. For these models, the PLI is investigated analytically and through numerical simulations. An evaluation is made of the sensitivity of the PLI to the amount of crosstalk between the sources through biological tissues of the head. It is found that the PLI is a useful interdependency measure for CSSs, especially when the amount of crosstalk is small. Another common interdependency measure is the coherence. A direct comparison of both measures has not been made in the literature so far. We assess the performance of the PLI and coherence for estimation and detection purposes based on, respectively, a normalized variance and a novel statistical measure termed contrast. Based on these performance measures, it is found that the PLI is similar or better than the CM in most cases. This result is also confirmed through analysis of EEGs recorded from epileptic patients.

Statistical dependency as a measure to evaluate Markov properties of stochastic point processes

Neuronal spike trains are regarded as stochastic point processes. To estimate the order and value of Markov processes of the interspike interval sequences with small number of samples, we have proposed a new measure of simplified statistical dependencyd _m. This measure is derived from statistical dependencyd _m (T=) in the case of Gaussian process, and is obtained by the standard deviation and the matrices of the serial correlation coefficients. Sinced _m is a parametric measure, it is calculated from the interval sequence transformed into the aormal distribution. We designate this as normalized simplified statistical dependencyNd _m. The order and value of the maintained spike sequences recorded from the mesencephalic reticular formation, red nucleus, optic tract, and lateral geniculate nucleus neurons in cats have been estimated. It is indicated that there is a considerable correspondence between the value ofNd _m and that ofd _m (T=). This suggests thatNd _m is useful in practice to estimate the order and value of Markov process with small number of samples.     

Ergonomical valorization of working spaces in multipurpose ships

In this work it is shown how anthropological data are among the most needed factors in ergonomical valorization of crew working spaces. Ship's working or living environment involves many unique human factors, which should be specially considered in our case as limitation of crew space. In this work we have chosen ships of different years of construction to prove this tendency. As a micro study, the work posture analysis using the pulling force experiment is performed in order to determine lumbar moment, intra-abdominal pressure as a measure of evaluating and comparing different crew work positions. As a macro-study, the "crew work posture analysis" was carried out by the use of the data collected from real cases. The most probable work postures in different spaces of a ship are classified and after some corrections of the work place the profile and its grade were determined. The "statistical analysis for real ship's spaces" is also performed, as well as another macro study, in order to show some real designed ship spaces from the point of view of the allocated volume.     

AnthropMMD: An R package with a graphical user interface for the mean measure of divergence

The mean measure of divergence is a dissimilarity measure between groups of individuals described by dichotomous variables. It is well suited to datasets with many missing values, and it is generally used to compute distance matrices and represent phenograms. Although often used in biological anthropology and archaeozoology, this method suffers from a lack of implementation in common statistical software. A package for the R statistical software, AnthropMMD, is presented here. Offering a dynamic graphical user interface, it is the first one dedicated to Smith's mean measure of divergence. The package also provides facilities for graphical representations and the crucial step of trait selection, so that the entire analysis can be performed through the graphical user interface. Its use is demonstrated using an artificial dataset, and the impact of trait selection is discussed. Finally, AnthropMMD is compared to three other free tools available for calculating the mean measure of divergence, and is proven to be consistent with them.     

hp‐rare 1.0: a computer program for performing rarefaction on measures of allelic richness

The number of alleles in a sample (allelic richness) is a fundamental measure of genetic diversity. However, this diversity measure has been difficult to use because large samples are expected to contain more alleles than small samples. The statistical technique of rarefaction compensates for this sampling disparity. Here I introduce a computer program that performs rarefaction on private alleles and hierarchical sampling designs.     

A Method for Measuring the Efficiency Gap between Average and Best Practice Energy Use: The ENERGY STAR Industrial Energy Performance Indicator

A common feature distinguishing between parametric/statistical models and engineering economics models is that engineering models explicitly represent best practice technologies, whereas parametric/statistical models are typically based on average practice. Measures of energy intensity based on average practice are of little use in corporate management of energy use or for public policy goal setting. In the context of companyor plant‐level indicators, it is more useful to have a measure of energy intensity that is capable of indicating where a company or plant lies within a distribution of performance. In other words, is the performance close to (or far from) the industry best practice? This article presents a parametric/statistical approach that can be used to measure best practice, thereby providing a measure of the difference, or “efficiency gap,” at a plant, company, or overall industry level. The approach requires plant‐level data and applies a stochastic frontier regression analysis used by the ENERGY STAR^TM industrial energy performance indicator (EPI) to energy intensity. Stochastic frontier regression analysis separates energy intensity into three components: systematic effects, inefficiency, and statistical (random) error. The article outlines the method and gives examples of EPI analysis conducted for two industries, breweries and motor vehicle assembly. In the EPI developed with the stochastic frontier regression for the auto industry, the industry median “efficiency gap” was around 27%.     

Comparison of Self-Reported Alcohol Consumption to Phosphatidylethanol Measurement among HIV-Infected Patients Initiating Antiretroviral Treatment in Southwestern Uganda

Background

Alcohol consumption among HIV-infected patients may accelerate HIV disease progression or reduce antiretroviral therapy adherence. Self-reported alcohol use is frequently under-reported due to social desirability and recall bias. The aim of this study was to compare self-reported alcohol consumption to phosphatidylethanol (PEth), a biomarker of alcohol consumption, and to estimate the correlation between multiple measures of self-reported alcohol consumption with PEth.

Methods

The Uganda AIDS Rural Treatment Outcomes (UARTO) cohort is located in southwestern Uganda and follows patients on ART to measure treatment outcomes. Patients complete standardized questionnaires quarterly including questions on demographics, health status and alcohol consumption. Baseline dried blood spots (DBS) were collected and retrieved to measure PEth.

Results

One hundred fifty samples were tested, and 56 (37.3%) were PEth positive (≥8 ng/mL). Of those, 51.7% did not report alcohol use in the past month. Men were more likely to under-report compared to women, OR 2.9, 95% CI = 1.26, 6.65) and those in the higher economic asset categories were less likely to under-report compared to those in the lowest category (OR = 0.41 95% CI: 0.17, 0.94). Among self-reported drinkers (n = 31), PEth was highly correlated with the total number of drinking days in the last 30 (Spearman R = 0.73, p<0.001).

Conclusions

Approximately half of HIV infected patients initiating ART and consuming alcohol under-report their use of alcohol. Given the high prevalence, clinicians should assess all patients for alcohol use with more attention to males and those in lower economic asset categories who deny alcohol use. Among those reporting current drinking, self-reported drinking days is a useful quantitative measure.     

Development and Validation of the Keele Musculoskeletal Patient Reported Outcome Measure (MSK-PROM)

Objective

To develop and validate a patient report outcome measure (PROM) for clinical practice that can monitor health status of patients with a range of musculoskeletal (MSK) disorders.

Methods

Constructs for inclusion in the MSK-PROM were identified from a consensus process involving patients with musculoskeletal conditions, clinicians, purchasers of healthcare services, and primary care researchers. Psychometric properties of the brief tool, including face and construct validity, repeatability and responsiveness were assessed in a sample of patients with musculoskeletal pain consulting physiotherapy services in the United Kingdom (n=425).

Results

The consensus process identified 10 prioritised domains for monitoring musculoskeletal health status: pain intensity, quality of life, physical capacity, interference with social/leisure activities, emotional well-being, severity of most difficult thing, activities and roles, understanding independence, and overall impact. As the EuroQol (EQ-5D-5L) is a widely adopted PROMs tool and covers the first four domains listed, to reduce patient burden to a minimum the MSK-PROM was designed to capture the remaining six prioritised domains which are not measured by the EQ-5D-5L. The tool demonstrated excellent reliability, construct validity, responsiveness and acceptability to patients and clinicians for use in clinical practice.

Conclusion

We have validated a brief patient reported outcome measure (MSK-PROM) for use in clinical practice to measure musculoskeletal health status and monitor outcomes over time using domains that are meaningful to patients and sensitive to change. Further work will establish whether the MSK-PROM is useful in other musculoskeletal healthcare settings.     

Diagnosis of hypothyroidism: a comparison of statistical techniques.

From replies to a postal questionnaire used in a radioactive iodine follow-up scheme patients had to be classified as either "suspected hypothyroid" or "euthyroid." A comparisons has been made of the effectiveness of published statistical techniques in making this classification. Two main conclusions emerged. Firstly, all except one of the methods identified an acceptable proportion of the hypothyroid patients, and, secondly, the results given by these methods were remarkably similar. Thus the simplest, which required only a count of the number of symptoms present, was selected for use.     

Designing a neural network for the constraint optimization of the fitness functions devised based on the load minimization of the genetic code

Nonrandom patterns in codon assignments are supported by many statistical and biochemical studies in the last two decades. The canonical genetic code is known to be highly efficient in minimizing the effects of mistranslational errors and point mutations, an ability, which in term is designated "load minimization". Prior studies have included many attempts at quantitative estimation of the fraction of randomly generated codes, which in terms of load minimization, score higher than the canonical genetic code. In this study, a neural network, which estimates a highly optimized genetic code in a relatively short period of time has been devised. Several fitness functions were used throughout this text. Meanwhile, we have made use of two cost measure matrices, PAM74-100 and mutation matrix.