Methods for testing association between uncertain genotypes and quantitative traits.

Interpretability and power of genome-wide association studies can be increased by imputing unobserved genotypes, using a reference panel of individuals genotyped at higher marker density. For many markers, genotypes cannot be imputed with complete certainty, and the uncertainty needs to be taken into account when testing for association with a given phenotype. In this paper, we compare currently available methods for testing association between uncertain genotypes and quantitative traits. We show that some previously described methods offer poor control of the false-positive rate (FPR), and that satisfactory performance of these methods is obtained only by using ad hoc filtering rules or by using a harsh transformation of the trait under study. We propose new methods that are based on exact maximum likelihood estimation and use a mixture model to accommodate nonnormal trait distributions when necessary. The new methods adequately control the FPR and also have equal or better power compared to all previously described methods. We provide a fast software implementation of all the methods studied here; our new method requires computation time of less than one computer-day for a typical genome-wide scan, with 2.5 M single nucleotide polymorphisms and 5000 individuals.

Statistical discrimination of steroid profiles in doping control with support vector machines.

Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport.

Statistical Analysis of Eco-Toxicologic Data of Mammals from a Polluted Area

Several eco-toxicological studies have shown that insectivorous mammals, due to theirfeeding habits, easily accumulate high amounts of pollutants in relation to other mammal species. To assess the bio-accumulation levels of toxic metals and their in°uenceon essential metals, we quantified the concentration of 19 elements (Ca, K, Fe, B, P,S, Na, Al, Zn, Ba, Rb, Sr, Cu, Mn, Hg, Cd, Mo, Cr and Pb) in bones of 105 greaterwhite-toothed shrews (Crocidura russula) from a polluted (Ebro Delta) and a control(Medas Islands) area. Since chemical contents of a bio-indicator are mainly compositional data, conventional statistical analyses currently used in eco-toxicology can givemisleading results. Therefore, to improve the interpretation of the data obtained, weused statistical techniques for compositional data analysis to define groups of metalsand to evaluate the relationships between them, from an inter-population viewpoint.Hypothesis testing on the adequate balance-coordinates allow us to confirm intuitionbased hypothesis and some previous results. The main statistical goal was to test equalmeans of balance-coordinates for the two defined populations. After checking normality,one-way ANOVA or Mann-Whitney tests were carried out for the inter-group balances

Adaptive strategy for the statistical analysis of connectomes.

We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores.

Iowa GED Statistical Report for Calendar Year2001, 2001

The following information summarizes the major statistical trends relative to Iowa’s GED testing program for calendar year 2001

Iowa GED Statistical Report, 2004

The following information summarizes the major statistical trends relative to Iowa’s GED testing program for calendar year 2004.

Iowa GED Statistical Report, 2002

The following information summarizes the major statistical trends relative to Iowa’s GED testing program for calendar year 2002

Iowa GED Statistical Report, 2006

The following information summarizes the major statistical trends relative to Iowa’s GED testing program for calendar Year 2005.

In-vitro testing of biofilm formation on infected bone grafts and bone substitutes

Background: Bacteria form biofilms on the surface of orthopaedic devices, causing persistent infections. Monitoring biofilm formation on bone grafts and bone substitutes is challenging due to heterogeneous surface characteristics. We analyzed various bone grafts and bone substitutes regarding their propensity for in-vitro biofilm formation caused by S. aureus and S. epidermidis. Methods: Beta-tricalciumphosphate (b-TCP, ChronOsTM), processed human spongiosa (TutoplastTM) and PMMA (PalacosTM) were investigated. PE was added as a growth control. As test strains S. aureus (ATCC 29213) and S. epidermidis RP62A (ATCC 35984) were used. Test materials were incubated with 105 cfu/ml. After 24 h, test materials were removed and washed, followed by a standardised sonication protocol. The resulting sonication fluid was plated and bacterial counts were enumerated and expressed as cfu/sample. Sonicated samples were transferred to a microcalorimeter (TA Instrument) and heat flow monitored over a 24 h period with a precision of 0.0001°C and a sensitiviy of 200 μW. Experiments were performed in triplicates to calculate the mean ± SD. One-way ANOVA analysis was used for statistical analysis. Results: Bacterial counts (log10 cfu/sample) were highest on b-TCP (S. aureus 7.67 ± 0.17; S. epidermidis 8.14 ± 0.05) while bacterial density (log10 cfu/surface) was highest on PMMA (S. aureus 6.12 ± 0.2, S. epidermidis 7.65 ± 0.13). Detection time for S. aureus biofilms was shorter for the porous materials (b-TCP and Tutoplast, p <0.001) compared to the smooth materials (PMMA and PE) with no differences between b-TCP and TutoplastTM (p >0.05) or PMMA and PE (p >0.05). In contrast, for S. epidermidis biofilms the detection time was different (p <0.001) between all materials except between Tutoplast and PE (p >0.05). Conclusion: Our results demonstrate biofilm formation with both strains on all tested materials. Microcalorimetry was able to detect quantitatively the amount of biofilm. Further studies are needed to see whether calorimetry is a suitable tool also to monitor approaches to prevent and treat infections associated with bone grafts and bone substitutes.

Testing the response of macroinvertebrate functional structure and biodiversity to flooding and confinement

The aim of the present study was to investigate the relative importance of flooding- and confinement-related environmentalfeatures in explaining macroinvertebrate trait structure and diversity in a pool of wetlands located in a Mediterranean riverfloodplain. To test hypothesized trait-environment relationships, we employed a recently implemented statistical procedure, thefourth-corner method. We found that flooding-related variables, mainly pH and turbidity, were related to traits that confer an abilityof the organism to resist flooding (e.g., small body-shape, protection of eggs) or recuperate faster after flooding (e.g., short life-span, asexual reproduction). In contrast, confinement-related variables, mainly temperature and organic matter, enhanced traits that allow organisms to interact and compete with other organisms (e.g., large size, sexual reproduction) and to efficiently use habitat and resources (e.g., diverse locomotion and feeding strategies). These results are in agreement with predictions made under the River Habitat Templet for lotic ecosystems, and demonstrate the ability of the fourth-corner method to test hypothesis that posit traitenvironment relationships. Trait diversity was slightly higher in flooded than in confined sites, whereas trait richness was not significantly different. This suggests that although trait structure may change in response to the main environmental factors, as evidenced by the fourth-corner method, the number of life-history strategies needed to persist in the face of such constraints remains more or less constant; only their relative dominance differs

Paper 4: EUROCAT statistical monitoring: identification and investigation of ten year trends of congenital anomalies in Europe.

BACKGROUND: As part of EUROCAT's surveillance of congenital anomalies in Europe, a statistical monitoring system has been developed to detect recent clusters or long-term (10 year) time trends. The purpose of this article is to describe the system for the identification and investigation of 10-year time trends, conceived as a "screening" tool ultimately leading to the identification of trends which may be due to changing teratogenic factors.METHODS: The EUROCAT database consists of all cases of congenital anomalies including livebirths, fetal deaths from 20 weeks gestational age, and terminations of pregnancy for fetal anomaly. Monitoring of 10-year trends is performed for each registry for each of 96 non-independent EUROCAT congenital anomaly subgroups, while Pan-Europe analysis combines data from all registries. The monitoring results are reviewed, prioritized according to a prioritization strategy, and communicated to registries for investigation. Twenty-one registries covering over 4 million births, from 1999 to 2008, were included in monitoring in 2010.CONCLUSIONS: Significant increasing trends were detected for abdominal wall anomalies, gastroschisis, hypospadias, Trisomy 18 and renal dysplasia in the Pan-Europe analysis while 68 increasing trends were identified in individual registries. A decreasing trend was detected in over one-third of anomaly subgroups in the Pan-Europe analysis, and 16.9% of individual registry tests. Registry preliminary investigations indicated that many trends are due to changes in data quality, ascertainment, screening, or diagnostic methods. Some trends are inevitably chance phenomena related to multiple testing, while others seem to represent real and continuing change needing further investigation and response by regional/national public health authorities.

More on Testing for Validity Instead of Looking for It

Using Monte Carlo simulations and reanalyzing the data of a validation study of the AEIM emotional intelligence test, we demonstrated that an atheoretical approach and the use of weak statistical procedures can result in biased validity estimates. These procedures included stepwise regression-and the general case of failing to include important theoretical controls-extreme scores analysis, and ignoring heteroscedasticity as well as measurement error. The authors of the AEIM test responded by offering more complete information about their analyses, allowing us to further examine the perils of ignoring theory and correct statistical procedures. In this paper we show with extended analyses that the AEIM test is invalid.

Task 4: Testing Iowa Portland Cement Concrete Mixtures for the AASHTO Mechanistic-Empirical Pavement Design Procedure, May 2008

The present research project was designed to identify the typical Iowa material input values that are required by the Mechanistic-Empirical Pavement Design Guide (MEPDG) for the Level 3 concrete pavement design. It was also designed to investigate the existing equations that might be used to predict Iowa pavement concrete for the Level 2 pavement design. In this project, over 20,000 data were collected from the Iowa Department of Transportation (DOT) and other sources. These data, most of which were concrete compressive strength, slump, air content, and unit weight data, were synthesized and their statistical parameters (such as the mean values and standard variations) were analyzed. Based on the analyses, the typical input values of Iowa pavement concrete, such as 28-day compressive strength (f’c), splitting tensile strength (fsp), elastic modulus (Ec), and modulus of rupture (MOR), were evaluated. The study indicates that the 28-day MOR of Iowa concrete is 646 + 51 psi, very close to the MEPDG default value (650 psi). The 28-day Ec of Iowa concrete (based only on two available data of the Iowa Curling and Warping project) is 4.82 + 0.28x106 psi, which is quite different from the MEPDG default value (3.93 x106 psi); therefore, the researchers recommend re-evaluating after more Iowa test data become available. The drying shrinkage (εc) of a typical Iowa concrete (C-3WR-C20 mix) was tested at Concrete Technology Laboratory (CTL). The test results show that the ultimate shrinkage of the concrete is about 454 microstrain and the time for the concrete to reach 50% of ultimate shrinkage is at 32 days; both of these values are very close to the MEPDG default values. The comparison of the Iowa test data and the MEPDG default values, as well as the recommendations on the input values to be used in MEPDG for Iowa PCC pavement design, are summarized in Table 20 of this report. The available equations for predicting the above-mentioned concrete properties were also assembled. The validity of these equations for Iowa concrete materials was examined. Multiple-parameters nonlinear regression analyses, along with the artificial neural network (ANN) method, were employed to investigate the relationships among Iowa concrete material properties and to modify the existing equations so as to be suitable for Iowa concrete materials. However, due to lack of necessary data sets, the relationships between Iowa concrete properties were established based on the limited data from CP Tech Center’s projects and ISU classes only. The researchers suggest that the resulting relationships be used by Iowa pavement design engineers as references only. The present study furthermore indicates that appropriately documenting concrete properties, including flexural strength, elastic modulus, and information on concrete mix design, is essential for updating the typical Iowa material input values and providing rational prediction equations for concrete pavement design in the future.

Combination of carbon isotope ratio with hydrogen isotope ratio determinations in sports drug testing.

Carbon isotope ratio (CIR) analysis has been routinely and successfully applied to doping control analysis for many years to uncover the misuse of endogenous steroids such as testosterone. Over the years, several challenges and limitations of this approach became apparent, e.g., the influence of inadequate chromatographic separation on CIR values or the emergence of steroid preparations comprising identical CIRs as endogenous steroids. While the latter has been addressed recently by the implementation of hydrogen isotope ratios (HIR), an improved sample preparation for CIR avoiding co-eluting compounds is presented herein together with newly established reference values of those endogenous steroids being relevant for doping controls. From the fraction of glucuronidated steroids 5β-pregnane-3α,20α-diol, 5α-androst-16-en-3α-ol, 3α-Hydroxy-5β-androstane-11,17-dione, 3α-hydroxy-5α-androstan-17-one (ANDRO), 3α-hydroxy-5β-androstan-17-one (ETIO), 3β-hydroxy-androst-5-en-17-one (DHEA), 5α- and 5β-androstane-3α,17β-diol (5aDIOL and 5bDIOL), 17β-hydroxy-androst-4-en-3-one and 17α-hydroxy-androst-4-en-3-one were included. In addition, sulfate conjugates of ANDRO, ETIO, DHEA, 3β-hydroxy-5α-androstan-17-one plus 17α- and androst-5-ene-3β,17β-diol were considered and analyzed after acidic solvolysis. The results obtained for the reference population encompassing n = 67 males and females confirmed earlier findings regarding factors influencing endogenous CIR. Variations in sample preparation influenced CIR measurements especially for 5aDIOL and 5bDIOL, the most valuable steroidal analytes for the detection of testosterone misuse. Earlier investigations on the HIR of the same reference population enabled the evaluation of combined measurements of CIR and HIR and its usefulness regarding both steroid metabolism studies and doping control analysis. The combination of both stable isotopes would allow for lower reference limits providing the same statistical power and certainty to distinguish between the endo- or exogenous origin of a urinary steroid.