Empirical study of supervised gene screening

Background  

Microarray studies provide a way of linking variations of phenotypes with their genetic causations. Constructing predictive models using high dimensional microarray measurements usually consists of three steps: (1) unsupervised gene screening; (2) supervised gene screening; and (3) statistical model building. Supervised gene screening based on marginal gene ranking is commonly used to reduce the number of genes in the model building. Various simple statistics, such as t-statistic or signal to noise ratio, have been used to rank genes in the supervised screening. Despite of its extensive usage, statistical study of supervised gene screening remains scarce. Our study is partly motivated by the differences in gene discovery results caused by using different supervised gene screening methods.     

Application of meta‐analysis methods for identifying proteomic expression level differences

We present new statistical approaches for identification of proteins with expression levels that are significantly changed when applying meta‐analysis to two or more independent experiments. We showed that the Euclidean distance measure has reduced risk of false positives compared to the rank product method. Our Ψ‐ranking method has advantages over the traditional fold‐change approach by incorporating both the fold‐change direction as well as the p‐value. In addition, the second novel method, Π‐ranking, considers the ratio of the fold‐change and thus integrates all three parameters. We further improved the latter by introducing our third technique, Σ‐ranking, which combines all three parameters in a balanced nonparametric approach.     

Contact calling behaviour in the male ring‐tailed lemur (Lemur catta)

The ring‐tailed lemur (Lemur catta) is a group‐living strepsirhine primate endemic to Madagascar that has a complex vocal repertoire including affiliative moan and hmm calls. Past research has suggested that both vocalisations may be contact calls, and we assessed their usage in addition to examining the effect of individual differences and social factors on male calling behaviour. We tested three hypotheses: the group cohesion, preferred companion and individual differences hypotheses. From March to July 2010, 565 h of focal animal data were collected on 31 males aged ≥1 year at the Beza Mahafaly Special Reserve, Madagascar. Focal males were observed for 30 min, with vocalisations, allogrooming and agonistic interactions noted using one‐zero sampling, and general behaviour, nearest neighbour identity and distance noted using instantaneous point sampling, all at 2.5 min intervals. We found support for the group cohesion hypothesis for both vocalisations, and support for the preferred companion and individual differences hypotheses for the hmm but not the moan vocalisation. Moan and hmm calls maintained the distance between a male and his nearest neighbour, and were made at higher rates during behaviours which may lead to separation from conspecifics, such as travel and vigilance. Males made hmm calls at higher rates when they were low‐ranking, and/or when the nearest neighbour of a male or a preferred companion of either sex. Low‐ranking males may hmm call to maintain proximity to specific individuals within social groups who will show them increased tolerance, with the hmm signalling peaceful intent. Ring‐tailed lemurs are one of the best living models of gregarious primate ancestors, and gaining a better knowledge of the function and range of usage of their contact calls informs our understanding of the evolution of primate cognition.     

Efficient Evaluation of Ranking Procedures when the Number of Units is Large,with Application to SNP Identification

Simulation‐based assessment is a popular and frequently necessary approach for evaluating statistical procedures. Sometimes overlooked is the ability to take advantage of underlying mathematical relations and we focus on this aspect. We show how to take advantage of large‐sample theory when conducting a simulation using the analysis of genomic data as a motivating example. The approach uses convergence results to provide an approximation to smaller‐sample results, results that are available only by simulation. We consider evaluating and comparing various ranking‐based methods for identifying the most highly associated SNPs in a genome‐wide association study, derive integral equation representations of the pre‐posterior distribution of percentiles produced by three ranking methods, and provide examples comparing performance. These results are of interest in their own right and set the framework for a more extensive set of comparisons.     

How feeding competition determines female chimpanzee gregariousness and ranging in the Taï National Park, Côte d'Ivoire

Socioecological theory suggests that feeding competition shapes female social relationships. Chimpanzees (Pan troglodytes) live in fission–fusion societies that allow them to react flexibly to increased feeding competition by forming smaller foraging parties when food is scarce. In chimpanzees at Gombe and Kibale, female dominance rank can crucially influence feeding competition and reproductive success as high‐ranking females monopolize core areas of relatively high quality, are more gregarious, and have higher body mass and reproductive success than low‐ranking females. Chimpanzee females in Taï National Park do not monopolize core areas; they use the entire territory as do the males of their community and are highly gregarious. Although female chimpanzees in Taï generally exhibit a linear dominance hierarchy benefits of high rank are currently not well understood. We used a multivariate analysis of long‐term data from two Taï chimpanzee communities to test whether high‐ranking females (1) increase gregariousness and (2) minimize their travel costs. We found that high‐ranking females were more gregarious than low‐rankers only when food was scarce. During periods of food scarcity, high rank allowed females to enjoy benefits of gregariousness, while low‐ranking females strongly decreased their gregariousness. High‐ranking females traveled more than low‐ranking females, suggesting that low‐rankers might follow a strategy to minimize energy expenditure. Our results suggest that, in contrast to other chimpanzee populations and depending on the prevailing ecological conditions, female chimpanzees at Taï respond differently to varying levels of feeding competition. Care needs to be taken before generalizing results found in any one chimpanzee population to the species level. Am. J. Primatol. 73:305–313, 2011. © 2010 Wiley‐Liss, Inc.     

Patterns of den occupation by the spotted hyaena (Crocuta crocuta)

Spotted hyaenas utilize isolated natal dens (NDs) and communal dens (CDs) for rearing their cubs. Here we describe patterns of natal and CD occupation by hyaenas belonging to one well‐studied clan in the Maasai Mara National Reserve during a 10‐year period. Locations of 98 den sites that were used as natal or CDs by hyaenas in the study clan were digitized in a Geographic Information System, and the duration of use of each den site, frequency of re‐use, and distances involved in den moves were quantified. Hyaenas moved their CD monthly on average. Most CD sites were occupied only once during the study, but several sites were used repeatedly. On rare occasions, the movement of hyaenas to a new den site could be attributed to a disturbance event at the CD, but factors regularly prompting hyaenas to move to new CD sites were unclear. High‐ranking female hyaenas were more likely to rear their cubs from birth in a CD than low‐ranking females. Low‐ranking females almost always utilized isolated NDs for the first few weeks of a litter's development, and low‐ranking females transferred their cubs over longer distances than did high‐ranking females.     

Food access in captive Ammotragus: the role played by hierarchy and mother–infant interactions

An analysis of individuals' behavior when accessing a restricted food source (troughs) was carried out in a captive population of aoudad (Ammotragus lervia). Access to the troughs followed a strict hierarchical order, as higher‐ranking individuals fed before lower‐ranking ones. Unweaned male and female calves made use of the troughs from the ages of 2 and 3 months, respectively. Both fed from the troughs more frequently and for longer periods when their mother was present, which allowed them to make use of the troughs while skipping the hierarchical order. Calves received fewer threats when in proximity to their mothers, particularly in high‐ranking families. Mothers defended their calves from other herdmates more frequently when at the feeding area than in other areas of the herd. However, only sated mothers let their calves feed freely from the troughs; unsated mothers showed an aggressive behavior even toward their calves. I conclude that a maternal presence is necessary for aoudad calves to successfully feed from troughs, and that families of higher social rank benefit by getting access to this food source earlier in the day and are disturbed less than low‐ranking families. Zoo Biol 21:597–605, 2002. © 2002 Wiley‐Liss, Inc.     

Evaluating the absolute quality of a single protein model using structural features and support vector machines

Knowing the quality of a protein structure model is important for its appropriate usage. We developed a model evaluation method to assess the absolute quality of a single protein model using only structural features with support vector machine regression. The method assigns an absolute quantitative score (i.e. GDT‐TS) to a model by comparing its secondary structure, relative solvent accessibility, contact map, and beta sheet structure with their counterparts predicted from its primary sequence. We trained and tested the method on the CASP6 dataset using cross‐validation. The correlation between predicted and true scores is 0.82. On the independent CASP7 dataset, the correlation averaged over 95 protein targets is 0.76; the average correlation for template‐based and ab initio targets is 0.82 and 0.50, respectively. Furthermore, the predicted absolute quality scores can be used to rank models effectively. The average difference (or loss) between the scores of the top‐ranked models and the best models is 5.70 on the CASP7 targets. This method performs favorably when compared with the other methods used on the same dataset. Moreover, the predicted absolute quality scores are comparable across models for different proteins. These features make the method a valuable tool for model quality assurance and ranking. Proteins 2009. © 2008 Wiley‐Liss, Inc.     

Confidence assessment for protein identification by using peptide‐mass fingerprinting data

Protein identification using Peptide Mass Fingerprinting (PMF) data remains an important yet only partially solved problem. Current computational methods may lead to false positive identification since the top hit from a database search may not be the target protein. In addition, the identification scores assigned singly by a scoring function (raw scores) are not normalized. Therefore, the ranking based on raw scores may be biased. To address the above issue, we have developed a statistical model to evaluate the confidence of the raw score and to improve the ranking of proteins for identification. The results show that the statistical model better ranks the correct protein than the raw scores. Our study provides a new method to enhance the accuracy of protein identification by using PMF data. We incorporated the method into our software package “Protein‐Decision” together with a user‐friendly graphical interface. A standalone version of Protein‐Decision is freely available at http://digbio.missouri.edu/ProteinDecision/ .     

Factors affecting the distribution and prevalence of oral mucosal lesions in complete denture wearers

Gerodontology 2010; doi: 10.1111/j.1741‐2358.2009.00351.x
Factors affecting the distribution and prevalence of oral mucosal lesions in complete denture wearers Objective: To determine the frequency of the oral lesions related to gender, age, the length of time of denture usage, education level and economic status. Methods: The 153 patients with old complete dentures (CD) were asked to participate in the investigation. The subjects (76 male and 77 female) were 37–85 years of age with a mean age of 61.8 ± 9.8 years. Education, economic status and age factors were estimated in subgroups. The data obtained were evaluated by one‐way anova , Mann–Whitney U‐test, Kruskal–Wallis test, Student’s t‐test and chi‐squared test. The level of statistical significance was set at p < 0.05. Results: The patients who had denture stomatitis and traumatic ulcers were statistically significantly older than the ones who did not have these lesions (p < 0.05). Based on the length of denture usage, patients who had a flabby ridge, fibrous inflammatory hyperplasia, traumatic ulcers (p < 0.01) and denture stomatitis (p < 0.05) were using their dentures statistically significantly longer than the ones who had healthy tissues. Conclusions: The CD wearers should be advised to visit their dentist regularly to prevent oral mucosal lesions due to the changing supporting tissues during the length of denture usage and to improve their quality of life.     

Sex, Rank and Age Differences in the Japanese Macaque (Macaca fuscata yakui) Participation in Inter-Group Encounters

In many species interactions among group are often characterized by agonistic behaviour. Although animals may participate in inter‐group encounters in different ways, depending on their energetic requirements, reproductive tactics, and/or developmental stage, the proximate causes affecting an animal's participation in inter‐group encounters are still poorly understood. Indeed, many studies have analysed the behaviour of males and females during inter‐group encounters without considering the importance of additional factors (e.g. rank). This study focuses on wild non‐provisioned Japanese macaques (Macaca fuscata yakui) living on Yakushima Island, Japan. It aims to determine how monkeys of different sex, age, and rank behave during inter‐group encounters and it discusses the implications and consequences of their behaviour on group composition and male dispersal. Males participated significantly more than females in inter‐group encounters, by displaying more aggressive or affiliative behaviour. High‐ranking and/or adult males were more aggressive than low‐ranking and/or subadult males during encounters occurring in the mating season and they also showed more herding behaviour. This trend was not found in inter‐group encounters occurring during the non‐mating season. Finally, males which then emigrated to new groups were low‐ranking and/or subadult individuals. Those males displayed more affiliative behaviour towards foreign males than males which did emigrate. These data indicate that in non‐territorial species with male dominance over female and high competition for mating partners males play an active, and often aggressive, role during inter‐group encounter while female participation is scarce. Factors such as age, rank and period of the year (in seasonally breeding species) have to be taken into considerations when analysing interactions between groups and their effects on group composition and social behaviour.     

Optimized distance‐dependent atom‐pair‐based potential DOOP for protein structure prediction

The DOcking decoy‐based Optimized Potential (DOOP) energy function for protein structure prediction is based on empirical distance‐dependent atom‐pair interactions. To optimize the atom‐pair interactions, native protein structures are decomposed into polypeptide chain segments that correspond to structural motives involving complete secondary structure elements. They constitute near native ligand–receptor systems (or just pairs). Thus, a total of 8609 ligand–receptor systems were prepared from 954 selected proteins. For each of these hypothetical ligand–receptor systems, 1000 evenly sampled docking decoys with 0–10 Å interface root‐mean‐square‐deviation (iRMSD) were generated with a method used before for protein–protein docking. A neural network‐based optimization method was applied to derive the optimized energy parameters using these decoys so that the energy function mimics the funnel‐like energy landscape for the interaction between these hypothetical ligand–receptor systems. Thus, our method hierarchically models the overall funnel‐like energy landscape of native protein structures. The resulting energy function was tested on several commonly used decoy sets for native protein structure recognition and compared with other statistical potentials. In combination with a torsion potential term which describes the local conformational preference, the atom‐pair‐based potential outperforms other reported statistical energy functions in correct ranking of native protein structures for a variety of decoy sets. This is especially the case for the most challenging ROSETTA decoy set, although it does not take into account side chain orientation‐dependence explicitly. The DOOP energy function for protein structure prediction, the underlying database of protein structures with hypothetical ligand–receptor systems and their decoys are freely available at http://agknapp.chemie.fu‐berlin.de/doop/ . Proteins 2015; 83:881–890. © 2015 Wiley Periodicals, Inc.     

Refining near‐native protein–protein docking decoys by local resampling and energy minimization

How to refine a near‐native structure to make it closer to its native conformation is an unsolved problem in protein‐structure and protein–protein complex‐structure prediction. In this article, we first test several scoring functions for selecting locally resampled near‐native protein–protein docking conformations and then propose a computationally efficient protocol for structure refinement via local resampling and energy minimization. The proposed method employs a statistical energy function based on a Distance‐scaled Ideal‐gas REference state (DFIRE) as an initial filter and an empirical energy function EMPIRE (EMpirical Protein‐InteRaction Energy) for optimization and re‐ranking. Significant improvement of final top‐1 ranked structures over initial near‐native structures is observed in the ZDOCK 2.3 decoy set for Benchmark 1.0 (74% whose global rmsd reduced by 0.5 Å or more and only 7% increased by 0.5 Å or more). Less significant improvement is observed for Benchmark 2.0 (38% versus 33%). Possible reasons are discussed. Proteins 2009. © 2008 Wiley‐Liss, Inc.     

A Test of the Cross-Generational Transmission of Grooming Preferences in Macaques

In this study we compared the grooming networks of macaque mothers and adult daughters in order to test whether primate social preferences may be transmitted from one generation to the next. We studied four social groups belonging to three different species (Macaca fascicularis, M. fuscata and M. sylvanus). We found no evidence for the transmission of individual degrees of kin bias or of preference for high‐ranking individuals (transmission of ‘rules of choice’). Only in one of four social groups were idiosyncratic interindividual preferences of mothers significantly similar to those of their adult daughters. Overall, the results of this study question the generality of the intergenerational transmission of social preferences in macaques. It is suggested that species‐specific degrees of preferences for kin and for high‐ranking individuals should be selected for and strategically adjusted by individual females in relation to social circumstances.     

Estimating space-use and habitat preference from wildlife telemetry data

Management and conservation of populations of animals requires information on where they are, why they are there, and where else they could be. These objectives are typically approached by collecting data on the animals' use of space, relating these positional data to prevailing environmental conditions and employing the resulting statistical models to predict usage at other geographical regions. Technical advances in wildlife telemetry have accomplished manifold increases in the amount and quality of available data, creating the need for a statistical framework that can use them to make population‐level inferences for habitat preference and space‐use. This has been slow‐in‐coming because wildlife telemetry data are spatio‐temporally autocorrelated, often unbalanced, presence‐only observations of behaviourally complex animals, responding to a multitude of cross‐correlated environmental variables. We review the evolution of regression models for the analysis of space‐use and habitat preference and outline the essential features of a framework that emerges naturally from these foundations. This allows us to derive a relationship between usage of points in geographical space and preference of habitats in environmental space. Within this framework, we discuss eight challenges, inherent in the spatial analysis of telemetry data and, for each, we propose solutions that can work in tandem. Specifically, we propose a logistic, mixed‐effects approach that uses generalized additive transformations of the environmental covariates and is fitted to a response data‐set comprising the telemetry and simulated observations, under a case‐control design. We apply this framework to a non‐trivial case‐study using satellite‐tagged grey seals Halichoerus grypus from the east coast of Scotland. We perform model selection by cross‐validation and confront our final model's predictions with telemetry data from the same, as well as different, geographical regions. We conclude that, despite the complex behaviour of the study species, flexible empirical models can capture the environmental relationships that shape population distributions.     

Model-supervised kernel smoothing for the estimation of spatial usage

The analysis of telemetry data obtained from tagged animals often requires that a smooth surface of spatial usage is fitted to the observations. Well‐established statistical techniques for doing this, such as kernel smoothing (KS), are based on asymptotic arguments that guarantee the convergence of their estimates to the truth with increasing sample size. Often, in addition to telemetry data, ecologists have access to a wealth of information relating to the animals’ distribution and movement. This additional information is potentially useful for the estimation of spatial usage but currently remains unused by existing methods. In this paper, I outline and begin the validation of model‐supervised kernel smoothing (MSKS), a modification of KS that uses such information to supervise surface‐fitting to telemetry data. MSKS initially requires an ad‐hoc synthesis of all the available information, excluding telemetry, into an auxiliary usage surface (the model). This is then combined with the kernel‐smoothed telemetry data into a hybrid surface that is the weighted average of the two. Automatic selection of the smoothing coefficient and the weight associated with the model is done by means of likelihood cross‐validation. I examine the performance of MSKS first, by extensive, numerical exploration on simulated data in one‐dimensional space and second, on two‐dimensional data obtained from an individual‐based simulation of a central‐place forager. The results for different models and sample sizes indicate that MSKS has three important properties. Firstly, it generally outperforms KS by an extent that depends on the quality of the auxiliary model. Secondly, when the auxiliary model is not informative, MSKS automatically reverts to a similar output as KS. Finally, in practical terms, MSKS is easy to implement and adds little to the computational requirements already made by KS methods. I illustrate the application of MSKS and further validate its performance on satellite telemetry data collected from a grey seal on the east coast of Scotland.