DIANA-EST: a statistical analysis.

MOTIVATION: Expressed Sequence Tags (ESTs) are next to cDNA sequences as the most direct way to locate in silico the genes of the genome and determine their structure. Currently ESTs make up more than 60% of all the database entries. The goal of this work is the development of a new program called DNA Intelligent Analysis for ESTs (DIANA-EST) based on a combination of Artificial Neural Networks (ANN) and statistics for the characterization of the coding regions within ESTs and the reconstruction of the encoded protein. RESULTS: 89.7% of the nucleotides from an independent test set with 127 ESTs were predicted correctly as to whether they are coding or non coding. AVAILABILITY: The program is available upon request from the author. CONTACT: Present address: Department of Genetics, University of Pennsylvania, School of Medicine, 475 Clinical Research Building, 415 Curie Boulevard, Philadelphia, PA 19104-6145, USA. artemis@pcbi.upenn.edu.     

Biosecurity surveillance design: detecting non-indigenous vertebrate introductions using risk and power

Ecosystems can be severely damaged by the introduction, establishment and spread of non-indigenous species (NIS) including vertebrates, invertebrates and plants. Development and use of natural areas poses a biosecurity risk regarding the introduction of increase NIS invasion risks, so biosecurity systems including prevention and detection measures are required. Even with the most rigorous biosecurity efforts, there is potential for NIS to evade quarantine and go on to establish and spread. The cost of such an event can be great, both environmentally and financially (e.g. containment/ management or eradication). We have developed a surveillance design methodology, for an application where increased use of a natural area may result in NIS incursions, even with extensive biosecurity systems. The surveillance design methodology acknowledges heterogeneity of risk in the study area and stratifies the area to optimise surveillance deployment, achieving great efficiencies and improvement in statistical power of detection. Many of the risk decisions require lack data and so the system incorporates expert opinion with available data. The design covers the broad range of potential NIS that may be introduced by using exemplar species and a variety of surveillance system components (SSCs) (such as a combination of formal scientific surveys, trapping methods, and casual observation) distributed optimally over time and space. The mix of SSCs can be manipulated to take into account such factors as their relative financial costs and demands on expertise. The methodology has the flexibility to be applied to various groups of potential NIS (e.g. vertebrates, invertebrates and plants), and the design can evolve as data are collected (adaptive management). Overall, the surveillance design methodology allows for an efficient use of resources, providing sufficient power to detect incursions, resulting in reduced environmental and financial costs from NIS incursions.     

AMMI adjustment for statistical analysis of an international wheat yield trial

Summary Multilocation trials are important for the CIMMYT Bread Wheat Program in producing high-yielding, adapted lines for a wide range of environments. This study investigated procedures for improving predictive success of a yield trial, grouping environments and genotypes into homogeneous subsets, and determining the yield stability of 18 CIMMYT bread wheats evaluated at 25 locations. Additive Main effects and Multiplicative Interaction (AMMI) analysis gave more precise estimates of genotypic yields within locations than means across replicates. This precision facilitated formation by cluster analysis of more cohesive groups of genotypes and locations for biological interpretation of interactions than occurred with unadjusted means. Locations were clustered into two subsets for which genotypes with positive interactions manifested in high, stable yields were identified. The analyses highlighted superior selections with both broad and specific adaptation.     

Biosecurity on cattle farms: a study in north-west England

Background

Few studies have considered in detail the range of biosecurity practices undertaken on cattle farms, particularly within the UK. In this study, 56 cattle farmers in a 100 km² area of north-west England were questioned regarding their on-farm biosecurity practices, including those relating to animal movements, equipment sharing and companies and contractors visiting the farms.

Methodology/Principal Findings

There was great variation between farms in terms of the type of, and extent to which, biosecurity was carried out. For example, the majority of farmers did not isolate stock bought onto the farm, but a small proportion always isolated stock. Many farmers administered treatments post-movement, primarily vaccinations and anthelmintics, but very few farms reported carrying out any health checks after moving animals on. In addition, there appeared to be much variation in the amount of biosecurity carried out by the different companies and contractors visiting the farms. Deadstock collectors and contracted animal waste spreaders, although likely to have a high potential for contact with infectious agents, were reported to infrequently disinfect themselves and their vehicles.

Conclusions/Significance

These findings suggest that although certain biosecurity practices are undertaken, many are carried out infrequently or not at all. This may be due to many factors, including cost (in time and money), lack of proven efficacies of practices and lack of relevant education of veterinary surgeons, producers and other herd health specialists. Further research exploring the reasons for the lack of uptake is imperative if preventive medicine is to be utilised fully by the farming industry.     

Quantifying neighbourhood socioeconomic effects in clustering of behaviour-related risk factors: a multilevel analysis

Background

The extent to which neighbourhood characteristics explain accumulation of health behaviours is poorly understood. We examined whether neighbourhood disadvantage was associated with co-occurrence of behaviour-related risk factors, and how much of the neighbourhood differences in the co-occurrence can be explained by individual and neighbourhood level covariates.

Methods

The study population consisted of 60 694 Finnish Public Sector Study participants in 2004 and 2008. Neighbourhood disadvantage was determined using small-area level information on household income, education attainment, and unemployment rate, and linked with individual data using Global Positioning System-coordinates. Associations between neighbourhood disadvantage and co-occurrence of three behaviour-related risk factors (smoking, heavy alcohol use, and physical inactivity), and the extent to which individual and neighbourhood level covariates explain neighbourhood differences in co-occurrence of risk factors were determined with multilevel cumulative logistic regression.

Results

After adjusting for age, sex, marital status, and population density we found a dose-response relationship between neighbourhood disadvantage and co-occurrence of risk factors within each level of individual socioeconomic status. The cumulative odds ratios for the sum of health risks comparing the most to the least disadvantaged neighbourhoods ranged between 1.13 (95% confidence interval (CI): 1.03–1.24) and 1.75 (95% CI, 1.54–1.98). Individual socioeconomic characteristics explained 35%, and neighbourhood disadvantage and population density 17% of the neighbourhood differences in the co-occurrence of risk factors.

Conclusions

Co-occurrence of poor health behaviours associated with neighbourhood disadvantage over and above individual''s own socioeconomic status. Neighbourhood differences cannot be captured using individual socioeconomic factors alone, but neighbourhood level characteristics should also be considered.     

Large-scale analysis of HLA peptides presented by HLA-Cw4

A large number of HLA-Cw4 (Cw *0402) peptides were purified, sequenced, and identified from breast and ovarian carcinoma cell lines. HLA-Cw4 molecules were expressed in these cells as soluble, secreted HLA (sHLA) and recovered from the growth medium. The peptides were separated by capillary reversed-phase HPLC and analyzed by tandem mass-spectrometry. The resulting peptides fit to some extent, but not completely, the known consensus of the Cw4 peptide-binding motif. Among the identified peptides, there are a few that originate from proteins of possible interest for cancer immunotherapy or diagnostics, including mucin-5B, ART-1, fatty acid synthase, putative prostate cancer tumor suppressor, DNA topoisomerase-1, and Rac1. This work demonstrates that large-scale identification of HLA peptides recovered from sHLA is an advantageous approach for establishing the HLA peptide consensus of different haplotypes and the identification of useful peptides for treatment of diseases such as cancer, viral, and autoimmune diseases.     

Novel statistical approaches to identify risk factors for soil-transmitted helminth infection in Timor-Leste

Soil-transmitted helminths (STHs) are parasitic intestinal worms that infect almost a fifth of the global population. Sustainable control of STHs requires understanding the complex interaction of factors contributing to transmission. Identifying risk factors has mainly relied on logistic regression models where the underlying assumption of independence between variables is not always satisfied. Previously demonstrated risk factors including water, sanitation and hygiene (WASH) access and behaviours, and socioeconomic status are intrinsically linked. Similarly, environmental factors including climate, soil and land attributes are often strongly correlated. Alternative methods such as recursive partitioning and Bayesian networks can handle correlated variables, but there are no published studies comparing these methods with logistic regression in the context of STH risk factor analysis. Baseline cross-sectional data from school-aged children in the (S)WASH-D for Worms study were used to compare risk factors identified from modelling the same data using three different statistical techniques. Outcomes of interest were infection with Ascaris spp. and any hookworm species (Necator americanus, Ancylostoma duodenale, and Ancylostoma ceylanicum). Mixed-effects logistic regression identified the fewest risk factors. Recursive partitioning identified the most WASH and demographic risk factors, while Bayesian networks identified the most environmental risk factors. Recursive partitioning produced classification trees that visualised potentially at-risk population sub-groups. Bayesian networks helped visualise relationships between variables and enabled interactive modelling of outcomes based on different scenarios for the predictor variables of interest. Model performance was similar across all techniques. Risk factors identified across all techniques were vegetation for Ascaris spp., and cleaning oneself with water after defecating for hookworm. This study adds to the limited body of evidence exploring alternative data modelling approaches in identifying risk factors for STH infections. Our findings suggest these approaches can provide novel insights for more robust interpretation.     

Sampling culturable heterotrophs from microcosms: a statistical analysis.

The contributions of different sources of error in sampling mixed and unmixed bacterial microcosms were evaluated by using analysis of variance. Culturable heterotrophic bacteria from a turbid freshwater impoundment were sampled from 9-liter tanks that were unagitated or mixed with magnetic stirrers or pumps and from dilution bottles that were unagitated or agitated with a mechanical shaker. Axenic cultures of Enterobacter aerogenes were also sampled from manually shaken test tubes. In both agitated and unagitated tanks and in unagitated dilution bottles, dilutions made from the same sampling pipette were significantly different, showing a clumping of bacteria on the scale of millimeters. Also, microcosms within a single experiment differed from one another by a large margin. Dilution mean squares and tank or bottle mean squares were homogeneous for all types of tanks and unagitated bottles, indicating that the gentle mixing provided by pumps and stir bars did not reduce either millimeter scale or intermicrocosm variability over what prevailed in unagitated microcosms. By contrast, the vigorously shaken bottles and test tubes showed no millimeter scale variability. Intermicrocosm variability was undetectable in test tubes and two orders of magnitude less in shaken bottles than in unshaken bottles. When these facts are coupled with the inherent statistical advantage of replicating large rather than small experimental units, it is concluded that sampling error in the enumeration of aquatic bacteria in microcosms will be reduced by using numerous, small, violently agitated microcosms with a minimum of subsampling per microcosm.     

Impact of meteorological factors on ozone concentrations modelled by time series analysis and multivariate statistical methods

The ozone concentrations in Slavonia (eastern part of Croatia) were measured for the first time in spring–summer season 2002. Fourier analysis, principal components analysis (PCA) and multiple linear regression analysis (MLR) were applied to these time series. Weekday effect in spring and weekend effect in summer period were observed. Correlation with meteorological parameters is strongly emphasized from 10 a.m.–3 p.m. MLR models showed that variations in ozone concentrations are attributed to variation of few meteorological parameters with R² ≈ 0.7 and 0.8 in the spring and summer, respectively.     

Cardiovascular risk factors in a tourist town: association with job-related factors

Previous studies have shown that mortality from cardiovascular diseases in fishing villages was lower than that in farming villages. In contrast, few reports on the population living in a tourist village have appeared. Then, we report here the characteristic features of a tourist town, and that in fishing and farming towns. The rural farming town in Gunma prefecture had a population of 15,100. The population working in the primary industry was 17.1%, and the farming population was 17.0%. The fishing town in Shizuoka prefecture had a population of 11,700. The population working in the primary industry was 11.0%, and the fishing population was 10.2%. The rural tourist town in Shizuoka prefecture had a population of 17,800. The population working in the tertiary industry was 60.2%, and the wholesaling or retailing population was 16.6%. Standardized mortality ratios of cardiovascular diseases in the tourist town reported by Shizuoka health officials were higher than the fishing town. The rate of participation at ages of 50-59 years for the basic health examination in the tourist town was lower than the fishing and the farming towns. From the results of the health examination of residents at ages of 50-59 years, the high prevalence of obesity and hypertension in men and high prevalence of hypertension in women were found in the tourist town. In the tourist town, self-employed women at ages of 50-59 years had irregular time of meals and insufficient care of diet in comparison with employed women. Furthermore, the prevalence of hypertension in self-employed women was also higher than that of employed women. We could suggest that health status in communities might be associated with job-related factors.     

HIV international clinical research: exploitation and risk

This paper aims to show that to reduce the level of exploitation present in (some) international clinical trials, research sponsors must aim to provide both an ex-ante expected gain in utility and a fair ex-post distribution of benefits for research subjects. I suggest the following principles of fair risk distribution in international research as the basis of a normative definition of fairness: (a) Persons should not be forced (by circumstance) to gamble in order to achieve or protect basic goods; (b) In cases where one party is gambling with basic goods and the other party is not, the distribution of benefits and burdens must be arranged so that they are of greatest benefit to the worst off; (c) In relationships where one party is gambling for basic goods and the other party is not, the party gambling for basic goods must be assured of some guaranteed benefits in addition to the chance of getting some practical benefits. These principles are applied to the case of HIV international research. I conclude that the research (as described) is mutually advantageous but still exploitative because the distribution of surplus benefits is unfair. It is unfair because research subjects are gambling with and for basic goods but they are not assured of a fair ex-post distribution of benefits. Principles (b) and (c) are not satisfied. Research participants are not accorded enough guaranteed benefits to outweigh the risks they undertake.     

Tandem mass spectrometry of human tryptic blood peptides calculated by a statistical algorithm and captured by a relational database with exploration by a general statistical analysis system

A goodness of fit test may be used to assign tandem mass spectra of peptides to amino acid sequences and to directly calculate the expected probability of mis-identification. The product of the peptide expectation values directly yields the probability that the parent protein has been mis-identified. A relational database could capture the mass spectral data, the best fit results, and permit subsequent calculations by a general statistical analysis system. The many files of the Hupo blood protein data correlated by X!TANDEM against the proteins of ENSEMBL were collected into a relational database. A redundant set of 247,077 proteins and peptides were correlated by X!TANDEM, and that was collapsed to a set of 34,956 peptides from 13,379 distinct proteins. About 6875 distinct proteins were only represented by a single distinct peptide, 2866 proteins showed 2 distinct peptides, and 3454 proteins showed at least three distinct peptides by X!TANDEM. More than 99% of the peptides were associated with proteins that had cumulative expectation values, i.e. probability of false positive identification, of one in one hundred or less. The distribution of peptides per protein from X!TANDEM was significantly different than those expected from random assignment of peptides.     

Tandem mass spectrometry of human tryptic blood peptides calculated by a statistical algorithm and captured by a relational database with exploration by a general statistical analysis system

A goodness of fit test may be used to assign tandem mass spectra of peptides to amino acid sequences and to directly calculate the expected probability of mis-identification. The product of the peptide expectation values directly yields the probability that the parent protein has been mis-identified. A relational database could capture the mass spectral data, the best fit results, and permit subsequent calculations by a general statistical analysis system. The many files of the Hupo blood protein data correlated by X!TANDEM against the proteins of ENSEMBL were collected into a relational database. A redundant set of 247,077 proteins and peptides were correlated by X!TANDEM, and that was collapsed to a set of 34,956 peptides from 13,379 distinct proteins. About 6875 distinct proteins were only represented by a single distinct peptide, 2866 proteins showed 2 distinct peptides, and 3454 proteins showed at least three distinct peptides by X!TANDEM. More than 99% of the peptides were associated with proteins that had cumulative expectation values, i.e. probability of false positive identification, of one in one hundred or less. The distribution of peptides per protein from X!TANDEM was significantly different than those expected from random assignment of peptides.     

DAnTE: a statistical tool for quantitative analysis of -omics data

Data Analysis Tool Extension (DAnTE) is a statistical tool designed to address challenges associated with quantitative bottom-up, shotgun proteomics data. This tool has also been demonstrated for microarray data and can easily be extended to other high-throughput data types. DAnTE features selected normalization methods, missing value imputation algorithms, peptide-to-protein rollup methods, an extensive array of plotting functions and a comprehensive hypothesis-testing scheme that can handle unbalanced data and random effects. The graphical user interface (GUI) is designed to be very intuitive and user friendly. AVAILABILITY: DAnTE may be downloaded free of charge at http://omics.pnl.gov/software/. SUPPLEMENTARY INFORMATION: An example dataset with instructions on how to perform a series of analysis steps is available at http://omics.pnl.gov/software/     

Selective isolation of mycobacteria from soil: a statistical analysis approach

We compared four decontamination methods for the isolation of mycobacteria from soil specimens. Different media were used: L?wenstein-Jensen, Ogawa and various modified Ogawa media. Statistical analysis demonstrated that the best results (low contamination and high positivity rates) were obtained when the specimens were incubated in trypticase soy broth, treated with solutions containing malachite green and cycloheximide, then decontaminated with sodium hydroxide and inoculated onto Ogawa media. The lowest contamination rates were obtained with Ogawa medium containing 500 micrograms cycloheximide ml-1. The use of these techniques is proposed for the isolation of mycobacteria from heavily contaminated clinical specimens as well as from soil.