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Very Large Number (very + large_number)
Selected AbstractsA Constructive Graphical Model Approach for Knowledge-Based Systems: A Vehicle Monitoring Case StudyCOMPUTATIONAL INTELLIGENCE, Issue 3 2003Y. Xiang Graphical models have been widely applied to uncertain reasoning in knowledge-based systems. For many of the problems tackled, a single graphical model is constructed before individual cases are presented and the model is used to reason about each new case. In this work, we consider a class of problems whose solution requires inference over a very large number of models that are impractical to construct a priori. We conduct a case study in the domain of vehicle monitoring and then generalize the approach taken. We show that the previously held negative belief on the applicability of graphical models to such problems is unjustified. We propose a set of techniques based on domain decomposition, model separation, model approximation, model compilation, and re-analysis to meet the computational challenges imposed by the combinatorial explosion. Experimental results on vehicle monitoring demonstrated good performance at near-real-time. [source] Metabolic responses of novel cellulolytic and saccharolytic agricultural soil Bacteria to oxygenENVIRONMENTAL MICROBIOLOGY, Issue 4 2010Stefanie Schellenberger Summary Cellulose is the most abundant biopolymer in terrestrial ecosystems and is degraded by microbial communities in soils. However, relatively little is known about the diversity and function of soil prokaryotes that might participate in the overall degradation of this biopolymer. The active cellulolytic and saccharolytic Bacteria in an agricultural soil were evaluated by 16S rRNA 13C-based stable isotope probing. Cellulose, cellobiose and glucose were mineralized under oxic conditions in soil slurries to carbon dioxide. Under anoxic conditions, these substrates were converted primarily to acetate, butyrate, carbon dioxide, hydrogen and traces of propionate and iso-butyrate; the production of these fermentation end-products was concomitant with the apparent reduction of iron(III). [13C]-cellulose was mainly degraded under oxic conditions by novel family-level taxa of the Bacteroidetes and Chloroflexi, and a known family-level taxon of Planctomycetes, whereas degradation under anoxic conditions was facilitated by the Kineosporiaceae (Actinobacteria) and cluster III Clostridiaceae and novel clusters within Bacteroidetes. Active aerobic sub-communities in oxic [13C]-cellobiose and [13C]-glucose treatments were dominated by Intrasporangiaceae and Micrococcaceae (Actinobacteria) whereas active cluster I Clostridiaceae (Firmicutes) were prevalent in anoxic treatments. A very large number (i.e. 28) of the detected taxa did not closely affiliate with known families, and active Archaea were not detected in any of the treatments. These collective findings suggest that: (i) a large uncultured diversity of soil Bacteria was involved in the utilization of cellulose and products of its hydrolysis, (ii) the active saccharolytic community differed phylogenetically from the active cellulolytic community, (iii) oxygen availability impacted differentially on the activity of taxa and (iv) different redox guilds (e.g. fermenters and iron reducers) compete or interact during cellulose degradation in aerated soils. [source] Avian influenza surveillance in wild birds in the European Union in 2006INFLUENZA AND OTHER RESPIRATORY VIRUSES, Issue 1 2009Uta Hesterberg Abstract Background, Infections of wild birds with highly pathogenic avian influenza (AI) subtype H5N1 virus were reported for the first time in the European Union in 2006. Objectives, To capture epidemiological information on H5N1 HPAI in wild bird populations through large-scale surveillance and extensive data collection. Methods, Records were analysed at bird level to explore the epidemiology of AI with regard to species of wild birds involved, timing and location of infections as well as the applicability of different surveillance types for the detection of infections. Results, In total, 120,706 records of birds were sent to the Community Reference Laboratory for analysis. Incidents of H5N1 HPAI in wild birds were detected in 14 EU Member States during 2006. All of these incidents occurred between February and May, with the exception of two single cases during the summer months in Germany and Spain. Conclusions, For the detection of H5N1 HPAI virus, passive surveillance of dead or diseased birds appeared the most effective approach, whilst active surveillance offered better detection of low pathogenic avian influenza (LPAI) viruses. No carrier species for H5N1 HPAI virus could be identified and almost all birds infected with H5N1 HPAI virus were either dead or showed clinical signs. A very large number of Mallards (Anas platyrhynchos) were tested in 2006 and while a high proportion of LPAI infections were found in this species, H5N1 HPAI virus was rarely identified in these birds. Orders of species that appeared to be very clinically susceptible to H5N1 HPAI virus were swans, diving ducks, mergansers and grebes, supporting experimental evidence. Surveillance results indicate that H5N1 HPAI virus did not establish itself successfully in the EU wild bird population in 2006. [source] Simulation analyses of weighted fair bandwidth-on-demand (WFBoD) process for broadband multimedia geostationary satellite systemsINTERNATIONAL JOURNAL OF SATELLITE COMMUNICATIONS AND NETWORKING, Issue 4 2005Güray Açar Abstract Advanced resource management schemes are required for broadband multimedia satellite networks to provide efficient and fair resource allocation while delivering guaranteed quality of service (QoS) to a potentially very large number of users. Such resource management schemes must provide well-defined service segregation to the different traffic flows of the satellite network, and they must be integrated with some connection admission control (CAC) process at least for the flows requiring QoS guarantees. Weighted fair bandwidth-on-demand (WFBoD) is a resource management process for broadband multimedia geostationary (GEO) satellite systems that provides fair and efficient resource allocation coupled with a well-defined MAC-level QoS framework (compatible with ATM and IP QoS frameworks) and a multi-level service segregation to a large number of users with diverse characteristics. WFBoD is also integrated with the CAC process. In this paper, we analyse via extensive simulations the WFBoD process in a bent-pipe satellite network. Our results show that WFBoD can be used to provide guaranteed QoS for both non-real-time and real-time variable bit rate (VBR) flows. Our results also show how to choose the main parameters of the WFBoD process depending on the system parameters and on the traffic characteristics of the flows. Copyright © 2005 John Wiley & Sons, Ltd. [source] Factor forecasts for the UKJOURNAL OF FORECASTING, Issue 4 2005Michael J. Artis Abstract Data are now readily available for a very large number of macroeconomic variables that are potentially useful when forecasting. We argue that recent developments in the theory of dynamic factor models enable such large data sets to be summarized by relatively few estimated factors, which can then be used to improve forecast accuracy. In this paper we construct a large macroeconomic data set for the UK, with about 80 variables, model it using a dynamic factor model, and compare the resulting forecasts with those from a set of standard time-series models. We find that just six factors are sufficient to explain 50% of the variability of all the variables in the data set. These factors, which can be shown to be related to key variables in the economy, and their use leads to considerable improvements upon standard time-series benchmarks in terms of forecasting performance. Copyright © 2005 John Wiley & Sons, Ltd. [source] Consulting the source code: prospects for gene-based medical diagnosticsJOURNAL OF INTERNAL MEDICINE, Issue S741 2001U. Landegren Abstract. Landegren U (Rudbeck Laboratory, Uppsala, Sweden) Gene-based diagnostics (Internal Medicine in the 21st Century). J Intern Med 2000; 248: 271,276. Gene-based diagnostics has been slow to enter medical routine practice in a grand way, but it is now spurred on by three important developments: the total genetic informational content of humans and most of our pathogens is rapidly becoming available; a very large number of genetic factors of diagnostic value in disease are being identified; and such factors include the identity of genes frequently targeted by mutations in specific diseases, common DNA sequence variants associated with disease or responses to therapy, and copy number alterations at the level of DNA or RNA that are characteristic of specific diseases. Finally, improved methodology for genetic analysis now brings all of these genetic factors within reach in clinical practice. The increasing opportunities for genetic diagnostics may gradually influence views on health and normality, and on the genetic plasticity of human beings, provoking discussions about some of the central attributes of genetics. [source] Towards statistical multicriteria decision modelling: a first approachJOURNAL OF MULTI CRITERIA DECISION ANALYSIS, Issue 6 2002Yves De Smet Abstract Many real life situations result from decisions taken by a very large number of decision makers. Among them, we may cite road traffic congestion, crowding during shopping, equity market behaviour, distribution of holiday destinations, etc. Furthermore, these decisions often depend on the optimisation of several conflicting criteria. In this paper, we introduce a new multicriteria tool based on Markov chains to model and manage these macroscopic phenomena. Finally, the road traffic congestion problem will be considered to illustrate the applicability of our approach. Copyright © 2003 John Wiley & Sons, Ltd. [source] Rate-based nonisothermal LLX model and its experimental validationAICHE JOURNAL, Issue 2 2004Debjit Sanpui Abstract Most of the current open literature handles liquid,liquid extraction (LLX) using equilibrium and/or isothermal models. However, in most industrial applications, the assumption of equilibrium and isothermal operation is not reasonable. A rate-based nonequilibrium model for both the mass and energy transfer in LLX during the three distinct stages of drop formation,drop, fall or rise, and drop coalescence,has been developed. These three hydrodynamic phenomena affect the mass transfer between dispersed and continuous phases for which a parallel,parallel mass-transfer resistance model has been incorporated. Because of the very large number of computations associated with repeated calculations of mass-transfer coefficients a local model has been proposed. We have compared our rate-based simulator with two other commercial simulators and our bench-scale experiments have been done for toluene,acetone,water and methyl isobutyl ketone,acetic acid,water systems. Stagewise mass and energy transfer and the hydrodynamics features have been compared between the experimental and the simulation runs. Relative-error square analysis (for the concentration profiles) shows that our simulation results are two orders of magnitude better in comparison to other commercial simulators. © 2004 American Institute of Chemical Engineers AIChE J, 50: 368,381, 2004 [source] Nonparametric Estimation and Testing in Panels of Intercorrelated Time SeriesJOURNAL OF TIME SERIES ANALYSIS, Issue 6 2004Vidar Hjellvik Abstract., We consider nonparametric estimation and testing of linearity in a panel of intercorrelated time series. We place the emphasis on the situation where there are many time series in the panel but few observations for each of the series. The intercorrelation is described by a latent process, and a conditioning argument involving this process plays an important role in deriving the asymptotic theory. To be accurate the asymptotic distribution of the test functional of linearity requires a very large number of observations, and bootstrapping gives much better finite sample results. A number of simulation experiments and an illustration on a real data set are included. [source] The ProteoMiner and the FortyNiners: Searching for gold nuggets in the proteomic arenaMASS SPECTROMETRY REVIEWS, Issue 6 2008Pier Giorgio Righetti Abstract The present review covers modern aspects of combinatorial peptide ligand libraries (CPLL), as used to analyze the "low-abundance proteome" in association with mass spectrometry. First, the capturing properties of baits of different lengths (from single amino acid to hexa-peptides) are described to show that a plateau is rapidly reached above a tetra-peptide in length, thus confirming the validity of having adopted hexapeptides for the considered application. The mechanism of interaction with proteins from very complex proteomes and the ability to decrease the dynamic concentration range is demonstrated with the help of mass spectrometry analysis. Examples are given on how treatment with CPLLs dramatically improves the detectability of peptides in mass spectrometry analysis, permitting detection of a very large number of proteins as compared with control, untreated samples. The use of complementary libraries is discussed with the aim to discover additional low-abundance species that escaped the first library. A discussion on the possibility to discover extremely rare gene products, and the quantitative aspect of the technology when associated with mass spectrometry is also provided. Some insights on the applications for hidden, low-abundance biomarkers are also presented. © 2008 Wiley Periodicals, Inc., Mass Spec Rev 27: 596,608, 2008 [source] Host immunity modulates transcriptional changes in a multigene family (yir) of rodent malariaMOLECULAR MICROBIOLOGY, Issue 3 2005Deirdre A. Cunningham Summary Variant antigens, encoded by multigene families, and expressed at the surface of erythrocytes infected with the human malaria parasite Plasmodium falciparum and the simian parasite Plasmodium knowlesi, are important in evasion of host immunity. The vir multigene family, encoding a very large number of variant antigens, has been identified in the human parasite Plasmodium vivax and homologues (yir) of this family exist in the rodent parasite Plasmodium yoelii. These genes are part of a superfamily (pir) which are found in Plasmodium species infecting rodents, monkeys and humans (P. yoelii, P. berghei, P. chabaudi, P. knowlesi and P. vivax). Here, we show that YIR proteins are expressed on the surface of erythrocytes infected with late-stage asexual parasites, and that host immunity modulates transcription of yir genes. The surface location and expression pattern of YIR is consistent with a role in antigenic variation. This provides a unique opportunity to study the regulation and expression of the pir superfamily, and its role in both protective immunity and antigenic variation, in an easily accessible animal model system. [source] Peak energy of the prompt emission of long gamma-ray bursts versus their fluence and peak fluxMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 2 2008L. Nava ABSTRACT The spectral-energy (and luminosity) correlations in long gamma-ray bursts are being hotly debated to establish, first of all, their reality against possible selection effects. These are best studied in the observer planes, namely the peak energy Eobspeak versus the fluence F or the peak flux P. In a recent paper, we have started to investigate this problem considering all bursts with known redshift and spectral properties. Here, we consider instead all bursts with known Eobspeak, irrespective of redshift, adding to those a sample of 100 faint BATSE bursts representative of a larger population of 1000 objects. This allows us to construct a complete, fluence-limited, sample, tailored to study the selection/instrumental effects we consider. We found that the fainter BATSE bursts have smaller Eobspeak than those of bright events. As a consequence, the Eobspeak of these bursts is correlated with the fluence, though with a slope flatter than that defined by bursts with z. Selection effects, which are present, are shown not to be responsible for the existence of such a correlation. About six per cent of these bursts are surely outliers of the Epeak,Eiso correlation (updated in this paper to include 83 bursts), since they are inconsistent with it for any redshift. Eobspeak also correlates with the peak flux, with a slope similar to the Epeak,Liso correlation. In this case, there is only one sure outlier. The scatter of the Eobspeak,P correlation defined by the BATSE bursts of our sample is significantly smaller than the Eobspeak,F correlation of the same bursts, while for the bursts with known redshift the Epeak,Eiso correlation is tighter than the Epeak,Liso one. Once a very large number of bursts with Eobspeak and redshift will be available, we thus expect that the Epeak,Liso correlation will be similar to that currently found, whereas it is very likely that the Epeak,Eiso correlation will become flatter and with a larger scatter. [source] Emergency transshipment in decentralized dealer networks: When to send and accept transshipment requestsNAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 6 2006Hui Zhao Abstract While there has been significant previous literature on inventory transshipment, most research has focused on the dealers' demand filling decision (when to fill transshipment requests from other dealers), ignoring the requesting decision (when to send transshipment requests to other dealers). In this paper we develop optimal inventory transshipment policies that incorporate both types of decisions. We consider a decentralized system in which the dealers are independent of the manufacturer and of each other. We first study a network consisting of a very large number of dealers. We prove that the optimal inventory and transshipment decisions for an individual dealer are controlled by threshold rationing and requesting levels. Then, in order to study the impact of transshipment among independent dealers in a smaller dealer network, we consider a decentralized two-dealer network and use a game theoretic approach to characterize the equilibrium inventory strategies of the individual dealers. An extensive numerical study highlights the impact of the requesting decision on the dealers' equilibrium behavior in a decentralized setting. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006 [source] Persons with severe mental illness in jails and prisons: A reviewNEW DIRECTIONS FOR YOUTH DEVELOPMENT, Issue 90 2001H. Richard Lamb One of the greatest problems of deinstitutionalization has been the very large number of persons with severe mental illness who have entered the criminal justice system instead of the mental health system. [source] How to make single small holes with large aspect ratiosPHYSICA STATUS SOLIDI - RAPID RESEARCH LETTERS, Issue 2-3 2009Helmut Föll Abstract In many areas of research a need for single small holes with diameters from a few nm to several ,m and large aspect ratios exists that is hard to meet with existing technologies. In a proof of principle it is shown that suitable single holes or specific arrays of some single holes can be made by first etching a very large number of small and deep holes or pores into semiconductors like Si or InP by established electrochemical means, followed by masking the desired holes and filling all others with, e.g., a metal in a galvanic process. The potential and limitations of this technique is briefly discussed. (© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] ,Pockets' of effective agencies in weak governance states: Where are they likely and why does it matter?PUBLIC ADMINISTRATION & DEVELOPMENT, Issue 2 2010David K. Leonard Abstract It is well established that even in countries that have poor governance and weak public sectors, exceptional well-functioning government and government-supported agencies do exist. What has not been established is where and why these ,pockets of effectiveness' are able to emerge. Some attribute their existence to exceptional leadership and good management. Others, while not doubting the importance of these internal factors, believe that these ,pockets' are generated by their place in the country's political economy. The literature on this subject is dominated by case studies and the consequence is that a very large number of hypotheses have been generated about what the political processes at work might be. This article inventories the array of available hypotheses and condenses them into five sets of meta-hypotheses. It also discusses how social scientists and practitioners ought to think about something whose occurrence is idiosyncratic. The future of development administration will be enhanced by more informed choice of strategic opportunities,avoiding both political determinism and a naïve faith that all is equally possible to those who will it. Copyright © 2010 John Wiley & Sons, Ltd. [source] Understanding race and human variation: Why forensic anthropologists are good at identifying raceAMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY, Issue 1 2009Stephen Ousley Abstract American forensicanthropologists uncritically accepted the biological race concept from classic physical anthropology and applied it to methods of human identification. Why and how the biological race concept might work in forensic anthropology was contemplated by Sauer (Soc Sci Med 34 1992 107,111), who hypothesized that American forensic anthropologists are good at what they do because of a concordance between social race and skeletal morphology in American whites and blacks. However, Sauer also stressed that this concordance did not validate the classic biological race concept of physical anthropology that there are a relatively small number of discrete types of human beings. Results from Howells (Papers of the Peabody Museum of Archaeology and Ethnology 67 1973 1,259; Papers of the Peabody Museum of Archaeology and Ethnology 79 1989 1,189; Papers of the Peabody Museum of Archaeology and Ethnology 82 1995 1,108) and others using craniometric and molecular data show strong geographic patterning of human variation despite overlap in their distributions. However, Williams et al. (Curr Anthropol 46 2005 340,346) concluded that skeletal morphology cannot be used to accurately classify individuals. Williams et al. cited additional support from Lewontin (Evol Biol 6 1972 381,398), who analyzed classic genetic markers. In this study, multivariate analyses of craniometric data support Sauer's hypothesis that there are morphological differences between American whites and blacks. We also confirm significant geographic patterning in human variation but also find differences among groups within continents. As a result, if biological races are defined by uniqueness, then there are a very large number of biological races that can be defined, contradicting the classic biological race concept of physical anthropology. Further, our results show that humans can be accurately classified into geographic origin using craniometrics even though there is overlap among groups. Am J Phys Anthropol 2009. © 2009 Wiley-Liss, Inc. [source] Outcomes and Efficacy of Newborn Hearing Screening: Strengths and Weaknesses (Success or Failure?),THE LARYNGOSCOPE, Issue 7 2008S. Korres MD Abstract Objective: To assess the outcomes of neonatal hearing screening with regard to the final diagnosis in a very large number of newborns and investigate related strengths and weaknesses of the program. Subjects: In this study, 76,560 newborns were assessed. Method: All neonates were assessed using transient evoked otoacoustic emissions (TEOAEs). Results: From the 76,560 neonates screened, 1,564 (2%) failed the test. According to the screening protocol, all parents of failed neonates were asked to bring their children 1 month following discharge to repeat the test. Of the 541 (34.6%) newborns who repeated the test, 303 (56%) were found normal and 238 (44%) again failed TEOAE. The latter children were referred to two special public centers for full audiology evaluation. In addition, 124 neonates were also referred due to other reasons revealed in the screening process (family history, high levels of bilirubin, etc.). Of the 362 children who were referred to the two special audiology centers, 113 (31.2%) were evaluated by these two centers. In addition, 42 children who had failed initial screening and did not show up for a follow-up appointment to repeat TEOAE were also assessed in the same centers. Of the 155 children who had a special audiologic evaluation, 56 (36.1%) were found to have hearing loss (HL) and 99 (63.9%) normal hearing. In detail, 28 had bilateral sensorineural HL greater than 40 dB, 10 had unilateral sensorineural HL greater than 40 dB, and 18 had otitis media with effusion or other conductive HL. Conclusions: Derived from the present study: 1) repeated testing of "failed" newborns in the maternity hospital and before discharge leads to an acceptable referral rate of 2%; 2) the 1-month follow-up of "failed" newborns further limits the false positive results but leads to high rate of newborns lost to follow-up; 3) a dedicated secretariat system should be implemented to follow-up each "failed" newborn and remind parents about their follow-up appointments; and 4) additional measures such as detailed educational material and parental friendly approach should also be implemented. [source] Using cluster analysis to study transition-metal geometries: four-coordinate complexes with two salicylaldiminato or related ligandsACTA CRYSTALLOGRAPHICA SECTION B, Issue 4 2007Andrew Parkin Cluster analysis is shown to be an effective method to analyse and classify metal coordination geometry in a very large number of four-coordinate bis -salicylaldimato (or bis- ,-iminoketonate) transition-metal complexes available in the Cambridge Structural Database. The methods described require no prior knowledge of chemistry to be input; retrieved structures are automatically clustered into groups based purely on the geometric similarity of the fragments and these groupings can then be interpreted by the structural chemist. [source] Productivity and impact of astronomical facilities: A recent sampleASTRONOMISCHE NACHRICHTEN, Issue 3 2010V. Trimble Abstract The papers published in 11 key astronomical journals in 2008, and a year of citations to those from the first half of the year, have been associated with the telescopes, satellites, and so forth where the data were gathered using a form of fractional counting. Some numbers are also given by journal, by subfield, and by wavelength band. The largest numbers of papers, and generally also quite highly cited ones, in their respective wavelength bands come from the Very Large Array, the Hubble Space Telescope, the Sloan Digital Sky Survey, the Spitzer Space Telescope, and the Chandra X-ray Telescope. Optical astronomy is still the largest sector; and papers about cosmology and exoplanets are cited more often than papers about binary stars and planetary nebulae. The authors conclude that it is of equal importance to recognize (a) that a very large number of papers also come from less famous facilities, (b) that a very large fraction of papers (and their authors) are concerned with the less highly-cited topics, (c) that many facilities are quite slow in achieving their eventual level of influence, and (d) that one really needs at least three years of citation data, not just one or two, to provide a fair picture of what is going on (© 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Crystallization and preliminary X-ray characterization of a glycerol dehydrogenase from the human pathogen Salmonella enterica serovar TyphimuriumACTA CRYSTALLOGRAPHICA SECTION F (ELECTRONIC), Issue 7 2009A. T. Gonçalves Glycerol dehydrogenase (GldA) encoded by the STM4108 gene (gldA) has been related to the synthesis of HilA, a major transcriptional regulator that is responsible for the expression of invasion genes in the human pathogen Salmonella enterica serovar Typhimurium. Single colourless crystals were obtained from a recombinant preparation of GldA overexpressed in Escherichia coli. They belonged to space group P2221, with unit-cell parameters a = 127.0, b = 160.1, c = 665.2,Å. The crystals contained a very large number of molecules in the asymmetric unit, probably 30,35. Diffraction data were collected to 3.5,Å resolution using synchrotron radiation at the European Synchrotron Radiation Facility. [source] The Scalasca performance toolset architectureCONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 6 2010Markus Geimer Abstract Scalasca is a performance toolset that has been specifically designed to analyze parallel application execution behavior on large-scale systems with many thousands of processors. It offers an incremental performance-analysis procedure that integrates runtime summaries with in-depth studies of concurrent behavior via event tracing, adopting a strategy of successively refined measurement configurations. Distinctive features are its ability to identify wait states in applications with very large numbers of processes and to combine these with efficiently summarized local measurements. In this article, we review the current toolset architecture, emphasizing its scalable design and the role of the different components in transforming raw measurement data into knowledge of application execution behavior. The scalability and effectiveness of Scalasca are then surveyed from experience measuring and analyzing real-world applications on a range of computer systems. Copyright © 2010 John Wiley & Sons, Ltd. [source] Forest Stand Dynamics and Livestock Grazing in Historical ContextCONSERVATION BIOLOGY, Issue 5 2005MICHAEL M. BORMAN clima; incendio forestal; pastoreo histórico; pino ponderosa; supresión de fuego Abstract:,Livestock grazing has been implicated as a cause of the unhealthy condition of ponderosa pine forest stands in the western United States. An evaluation of livestock grazing impacts on natural resources requires an understanding of the context in which grazing occurred. Context should include timing of grazing, duration of grazing, intensity of grazing, and species of grazing animal. Historical context, when and under what circumstances grazing occurred, is also an important consideration. Many of the dense ponderosa pine forests and less-than-desirable forest health conditions of today originated in the early 1900s. Contributing to that condition was a convergence of fire, climate, and grazing factors that were unique to that time. During that time period, substantially fewer low-intensity ground fires (those that thinned dense stands of younger trees) were the result of reduced fine fuels (grazing), a substantial reduction in fires initiated by Native Americans, and effective fire-suppression programs. Especially favorable climate years for tree reproduction occurred during the early 1900s. Exceptionally heavy, unregulated, unmanaged grazing by very large numbers of horses, cattle, and sheep during the late nineteenth and early twentieth centuries occurred in most of the U.S. West and beginning earlier in portions of the Southwest. Today, livestock numbers on public lands are substantially lower than they were during this time and grazing is generally managed. Grazing then and grazing now are not the same. Resumen:,El pastoreo de ganado ha sido implicado como una causa de la mala salud de los bosques de pino ponderosa en el occidente de Estados Unidos. La evaluación de los impactos del pastoreo sobre los recursos naturales requiere de conocimiento del contexto en que ocurrió el pastoreo. El contexto debe incluir al período de ocurrencia, la duración y la intensidad del pastoreo, así como la especie de animal que pastoreó. El contexto histórico, cuando y bajo que circunstancias ocurrió el pastoreo, también es una consideración importante. Muchos de los bosques densos de pino ponderosa y de las condiciones, menos que deseables, de salud de los bosques actuales se originaron al principio del siglo pasado. Contribuyó a esa condición una convergencia de factores, fuego, clima y pastoreo, que fueron únicos en ese tiempo. Durante ese período, hubo sustancialmente menos incendios superficiales de baja intensidad (que afectaron a grupos densos de árboles más jóvenes) como resultado de la reducción de combustibles finos (pastoreo), una reducción sustancial en los incendios iniciados por Americanos Nativos y programas efectivos de supresión de incendios. Al inicio del siglo pasado hubo años con clima especialmente favorable para la reproducción de árboles. Al final del siglo diecinueve y comienzo del veinte hubo pastoreo no regulado ni manejado, excepcionalmente intensivo, por una gran cantidad de caballos, reses y ovejas en la mayor parte del oeste de E.U.A. y aun antes en porciones del suroeste. En la actualidad, el número de semovientes en terrenos públicos es sustancialmente menor al de ese tiempo, y el pastoreo generalmente es manejado. El pastoreo entonces y el pastoreo ahora no son lo mismo. [source] Surface deformation due to loading of a layered elastic half-space: a rapid numerical kernel based on a circular loading elementGEOPHYSICAL JOURNAL INTERNATIONAL, Issue 1 2007E. Pan SUMMARY This study is motivated by a desire to develop a fast numerical algorithm for computing the surface deformation field induced by surface pressure loading on a layered, isotropic, elastic half-space. The approach that we pursue here is based on a circular loading element. That is, an arbitrary surface pressure field applied within a finite surface domain will be represented by a large number of circular loading elements, all with the same radius, in which the applied downwards pressure (normal stress) is piecewise uniform: that is, the load within each individual circle is laterally uniform. The key practical requirement associated with this approach is that we need to be able to solve for the displacement field due to a single circular load, at very large numbers of points (or ,stations'), at very low computational cost. This elemental problem is axisymmetric, and so the displacement vector field consists of radial and vertical components both of which are functions only of the radial coordinate r. We achieve high computational speeds using a novel two-stage approach that we call the sparse evaluation and massive interpolation (SEMI) method. First, we use a high accuracy but computationally expensive method to compute the displacement vectors at a limited number of r values (called control points or knots), and then we use a variety of fast interpolation methods to determine the displacements at much larger numbers of intervening points. The accurate solutions achieved at the control points are framed in terms of cylindrical vector functions, Hankel transforms and propagator matrices. Adaptive Gauss quadrature is used to handle the oscillatory nature of the integrands in an optimal manner. To extend these exact solutions via interpolation we divide the r -axis into three zones, and employ a different interpolation algorithm in each zone. The magnitude of the errors associated with the interpolation is controlled by the number, M, of control points. For M= 54, the maximum RMS relative error associated with the SEMI method is less than 0.2 per cent, and it is possible to evaluate the displacement field at 100 000 stations about 1200 times faster than if the direct (exact) solution was evaluated at each station; for M= 99 which corresponds to a maximum RMS relative error less than 0.03 per cent, the SEMI method is about 700 times faster than the direct solution. [source] 135 Life History and Ecology of Trentepohliaceae (Chlorophyta) in the West of IrelandJOURNAL OF PHYCOLOGY, Issue 2003F. Rindi Species of subaerial green algae of the family Trentepohliaceae are common in tropical and temperate regions. Despite nearly two centuries of investigations, several important aspects of their biology (such as life history and taxonomic relationships of some species) are still poorly understood. In western Ireland, the abundance of Trentepohliaceae is a peculiar feature of the subaerial algal vegetation. Six species are present (Phycopeltis arundinacea, Printzina lagenifera, Trentepohlia abietina, T. aurea, T. iolithus and T. umbrina). Life history and phenology of these were examined by extensive field and culture studies. In contrast to most other subaerial algae, the Trentepohliaceae show a generally strict substratum-specificity in western Ireland. T. iolithus, in particular, is remarkable for its occurrence on concrete walls, where it may produce extensive dark-red growths. Our observations suggest that general statements about the life history of Trentepohlia should be reconsidered critically. There is no evidence that in Irish populations a regular alternation of isomorphic gametophytes and sporophytes takes place; biflagellate swarmers (usually considered gametes) behave as asexual spores and reproduce the same morphological phase. No fusion of gametes was observed and a detailed examination of the literature concerning the genus shows that this phenomenon is extremely rare. A combination of studies based on different types of data (molecular data, examination of very large numbers of field samples, chromosome numbers, culture studies) is considered fundamental to any definitive clarification of the taxonomy and life history of Trentepohlia. [source] Use of checkerboard DNA,DNA hybridization to study complex microbial ecosystemsMOLECULAR ORAL MICROBIOLOGY, Issue 6 2004S. S. Socransky It has been difficult to conduct large scale studies of microbiologically complex ecosystems using conventional microbiological techniques. Molecular identification techniques in new probe-target formats, such as checkerboard DNA,DNA hybridization, permit enumeration of large numbers of species in very large numbers of samples. Digoxigenin-labeled whole genomic probes to 40 common subgingival species were tested in a checkerboard hydridization format. Chemifluorescent signals resulting from the hybridization reactions were quantified using a Fluorimager and used to evaluate sensitivity and specificity of the probes. Sensitivity of the DNA probes was adjusted to detect 104 cells. In all, 93.5% of potential cross-reactions to 80 cultivable species exhibited signals <5% of that detected for the homologous probe signal. Competitive hybridization and probes prepared by subtraction hybridization and polymerase chain reaction were effective in minimizing cross-reactions for closely related taxa. To demonstrate utility, the technique was used to evaluate 8887 subgingival plaque samples from 79 periodontally healthy and 272 chronic periodontitis subjects and 8126 samples from 166 subjects taken prior to and after periodontal therapy. Significant differences were detected for many taxa for mean counts, proportion of total sample, and percentage of sites colonized between samples from periodontally healthy and periodontitis subjects. Further, significant reductions were observed post therapy for many subgingival species including periodontal pathogens. DNA probes used in the checkerboard DNA,DNA format provide a useful tool for the enumeration of bacterial species in microbiologically complex systems. [source] Internal migration in Britain, 2000,01, examined through an area classification frameworkPOPULATION, SPACE AND PLACE (PREVIOUSLY:-INT JOURNAL OF POPULATION GEOGRAPHY), Issue 6 2010Adam Dennett Abstract This paper explores the age variations in origin,destination migration data from the 2001 UK Census. It does so using a national district classification as a framework for summarising what is a series of matrices, each containing very large numbers of cells. The results demonstrate how migration propensities and patterns vary between different types of district, providing new insights into the processes through which the population is redistributed throughout Great Britain. Copyright © 2009 John Wiley & Sons, Ltd. [source] A genome wide association study for QTL affecting direct and maternal effects of stillbirth and dystocia in cattleANIMAL GENETICS, Issue 3 2010H. G. Olsen Summary Dystocia and stillbirth are significant causes of female and neonatal death in many species and there is evidence for a genetic component to both traits. Identifying causal mutations affecting these traits through genome wide association studies could reveal the genetic pathways involved and will be a step towards targeted interventions. Norwegian Red cattle are an ideal model breed for such studies as very large numbers of records are available. We conducted a genome wide association study for direct and maternal effects of dystocia and stillbirth using almost 1 million records of these traits. Genotyping costs were minimized by genotyping the sires of the recorded cows, and using daughter averages as phenotypes. A dense marker map containing 17 343 single nucleotide polymorphisms covering all autosomal chromosomes was utilized. The genotyped sires were assigned to one of two groups in an attempt to ensure independence between the groups. Associations were only considered validated if they occurred in both groups. Strong associations were found and validated on chromosomes 4, 5, 6, 9, 12, 20, 22 and 28. The QTL region on chromosome 6 was refined using LDLA analysis. The results showed that this chromosome most probably contains two QTL for direct effect on dystocia and one for direct effect on stillbirth. Several candidate genes may be identified close to these QTL. Of these, a cluster of genes expected to affect bone and cartilage formation (i.e. SPP1, IBSP and MEPE) are of particular interest and we suggest that these genes are screened in candidate gene studies for dystocia and stillbirth in cattle as well as other species. [source] European Mathematical Genetics Meeting, Heidelberg, Germany, 12th,13th April 2007ANNALS OF HUMAN GENETICS, Issue 4 2007Article first published online: 28 MAY 200 Saurabh Ghosh 11 Indian Statistical Institute, Kolkata, India High correlations between two quantitative traits may be either due to common genetic factors or common environmental factors or a combination of both. In this study, we develop statistical methods to extract the contribution of a common QTL to the total correlation between the components of a bivariate phenotype. Using data on bivariate phenotypes and marker genotypes for sib-pairs, we propose a test for linkage between a common QTL and a marker locus based on the conditional cross-sib trait correlations (trait 1 of sib 1 , trait 2 of sib 2 and conversely) given the identity-by-descent sharing at the marker locus. The null hypothesis cannot be rejected unless there exists a common QTL. We use Monte-Carlo simulations to evaluate the performance of the proposed test under different trait parameters and quantitative trait distributions. An application of the method is illustrated using data on two alcohol-related phenotypes from the Collaborative Study On The Genetics Of Alcoholism project. Rémi Kazma 1 , Catherine Bonaïti-Pellié 1 , Emmanuelle Génin 12 INSERM UMR-S535 and Université Paris Sud, Villejuif, 94817, France Keywords: Gene-environment interaction, sibling recurrence risk, exposure correlation Gene-environment interactions may play important roles in complex disease susceptibility but their detection is often difficult. Here we show how gene-environment interactions can be detected by investigating the degree of familial aggregation according to the exposure of the probands. In case of gene-environment interaction, the distribution of genotypes of affected individuals, and consequently the risk in relatives, depends on their exposure. We developed a test comparing the risks in sibs according to the proband exposure. To evaluate the properties of this new test, we derived the formulas for calculating the expected risks in sibs according to the exposure of probands for various values of exposure frequency, relative risk due to exposure alone, frequencies of latent susceptibility genotypes, genetic relative risks and interaction coefficients. We find that the ratio of risks when the proband is exposed and not exposed is a good indicator of the interaction effect. We evaluate the power of the test for various sample sizes of affected individuals. We conclude that this test is valuable for diseases with moderate familial aggregation, only when the role of the exposure has been clearly evidenced. Since a correlation for exposure among sibs might lead to a difference in risks among sibs in the different proband exposure strata, we also add an exposure correlation coefficient in the model. Interestingly, we find that when this correlation is correctly accounted for, the power of the test is not decreased and might even be significantly increased. Andrea Callegaro 1 , Hans J.C. Van Houwelingen 1 , Jeanine Houwing-Duistermaat 13 Dept. of Medical Statistics and Bioinformatics, Leiden University Medical Center, The Netherlands Keywords: Survival analysis, age at onset, score test, linkage analysis Non parametric linkage (NPL) analysis compares the identical by descent (IBD) sharing in sibling pairs to the expected IBD sharing under the hypothesis of no linkage. Often information is available on the marginal cumulative hazards (for example breast cancer incidence curves). Our aim is to extend the NPL methods by taking into account the age at onset of selected sibling pairs using these known marginal hazards. Li and Zhong (2002) proposed a (retrospective) likelihood ratio test based on an additive frailty model for genetic linkage analysis. From their model we derive a score statistic for selected samples which turns out to be a weighed NPL method. The weights depend on the marginal cumulative hazards and on the frailty parameter. A second approach is based on a simple gamma shared frailty model. Here, we simply test whether the score function of the frailty parameter depends on the excess IBD. We compare the performance of these methods using simulated data. Céline Bellenguez 1 , Carole Ober 2 , Catherine Bourgain 14 INSERM U535 and University Paris Sud, Villejuif, France 5 Department of Human Genetics, The University of Chicago, USA Keywords: Linkage analysis, linkage disequilibrium, high density SNP data Compared with microsatellite markers, high density SNP maps should be more informative for linkage analyses. However, because they are much closer, SNPs present important linkage disequilibrium (LD), which biases classical nonparametric multipoint analyses. This problem is even stronger in population isolates where LD extends over larger regions with a more stochastic pattern. We investigate the issue of linkage analysis with a 500K SNP map in a large and inbred 1840-member Hutterite pedigree, phenotyped for asthma. Using an efficient pedigree breaking strategy, we first identified linked regions with a 5cM microsatellite map, on which we focused to evaluate the SNP map. The only method that models LD in the NPL analysis is limited in both the pedigree size and the number of markers (Abecasis and Wigginton, 2005) and therefore could not be used. Instead, we studied methods that identify sets of SNPs with maximum linkage information content in our pedigree and no LD-driven bias. Both algorithms that directly remove pairs of SNPs in high LD and clustering methods were evaluated. Null simulations were performed to control that Zlr calculated with the SNP sets were not falsely inflated. Preliminary results suggest that although LD is strong in such populations, linkage information content slightly better than that of microsatellite maps can be extracted from dense SNP maps, provided that a careful marker selection is conducted. In particular, we show that the specific LD pattern requires considering LD between a wide range of marker pairs rather than only in predefined blocks. Peter Van Loo 1,2,3 , Stein Aerts 1,2 , Diether Lambrechts 4,5 , Bernard Thienpont 2 , Sunit Maity 4,5 , Bert Coessens 3 , Frederik De Smet 4,5 , Leon-Charles Tranchevent 3 , Bart De Moor 2 , Koen Devriendt 3 , Peter Marynen 1,2 , Bassem Hassan 1,2 , Peter Carmeliet 4,5 , Yves Moreau 36 Department of Molecular and Developmental Genetics, VIB, Belgium 7 Department of Human Genetics, University of Leuven, Belgium 8 Bioinformatics group, Department of Electrical Engineering, University of Leuven, Belgium 9 Department of Transgene Technology and Gene Therapy, VIB, Belgium 10 Center for Transgene Technology and Gene Therapy, University of Leuven, Belgium Keywords: Bioinformatics, gene prioritization, data fusion The identification of genes involved in health and disease remains a formidable challenge. Here, we describe a novel bioinformatics method to prioritize candidate genes underlying pathways or diseases, based on their similarity to genes known to be involved in these processes. It is freely accessible as an interactive software tool, ENDEAVOUR, at http://www.esat.kuleuven.be/endeavour. Unlike previous methods, ENDEAVOUR generates distinct prioritizations from multiple heterogeneous data sources, which are then integrated, or fused, into one global ranking using order statistics. ENDEAVOUR prioritizes candidate genes in a three-step process. First, information about a disease or pathway is gathered from a set of known "training" genes by consulting multiple data sources. Next, the candidate genes are ranked based on similarity with the training properties obtained in the first step, resulting in one prioritized list for each data source. Finally, ENDEAVOUR fuses each of these rankings into a single global ranking, providing an overall prioritization of the candidate genes. Validation of ENDEAVOUR revealed it was able to efficiently prioritize 627 genes in disease data sets and 76 genes in biological pathway sets, identify candidates of 16 mono- or polygenic diseases, and discover regulatory genes of myeloid differentiation. Furthermore, the approach identified YPEL1 as a novel gene involved in craniofacial development from a 2-Mb chromosomal region, deleted in some patients with DiGeorge-like birth defects. Finally, we are currently evaluating a pipeline combining array-CGH, ENDEAVOUR and in vivo validation in zebrafish to identify novel genes involved in congenital heart defects. Mark Broom 1 , Graeme Ruxton 2 , Rebecca Kilner 311 Mathematics Dept., University of Sussex, UK 12 Division of Environmental and Evolutionary Biology, University of Glasgow, UK 13 Department of Zoology, University of Cambridge, UK Keywords: Evolutionarily stable strategy, parasitism, asymmetric game Brood parasites chicks vary in the harm that they do to their companions in the nest. In this presentation we use game-theoretic methods to model this variation. Our model considers hosts which potentially abandon single nestlings and instead choose to re-allocate their reproductive effort to future breeding, irrespective of whether the abandoned chick is the host's young or a brood parasite's. The parasite chick must decide whether or not to kill host young by balancing the benefits from reduced competition in the nest against the risk of desertion by host parents. The model predicts that three different types of evolutionarily stable strategies can exist. (1) Hosts routinely rear depleted broods, the brood parasite always kills host young and the host never then abandons the nest. (2) When adult survival after deserting single offspring is very high, hosts always abandon broods of a single nestling and the parasite never kills host offspring, effectively holding them as hostages to prevent nest desertion. (3) Intermediate strategies, in which parasites sometimes kill their nest-mates and host parents sometimes desert nests that contain only a single chick, can also be evolutionarily stable. We provide quantitative descriptions of how the values given to ecological and behavioral parameters of the host-parasite system influence the likelihood of each strategy and compare our results with real host-brood parasite associations in nature. Martin Harrison 114 Mathematics Dept, University of Sussex, UK Keywords: Brood parasitism, games, host, parasite The interaction between hosts and parasites in bird populations has been studied extensively. Game theoretical methods have been used to model this interaction previously, but this has not been studied extensively taking into account the sequential nature of this game. We consider a model allowing the host and parasite to make a number of decisions, which depend on a number of natural factors. The host lays an egg, a parasite bird will arrive at the nest with a certain probability and then chooses to destroy a number of the host eggs and lay one of it's own. With some destruction occurring, either natural or through the actions of the parasite, the host chooses to continue, eject an egg (hoping to eject the parasite) or abandon the nest. Once the eggs have hatched the game then falls to the parasite chick versus the host. The chick chooses to destroy or eject a number of eggs. The final decision is made by the host, choosing whether to raise or abandon the chicks that are in the nest. We consider various natural parameters and probabilities which influence these decisions. We then use this model to look at real-world situations of the interactions of the Reed Warbler and two different parasites, the Common Cuckoo and the Brown-Headed Cowbird. These two parasites have different methods in the way that they parasitize the nests of their hosts. The hosts in turn have a different reaction to these parasites. Arne Jochens 1 , Amke Caliebe 2 , Uwe Roesler 1 , Michael Krawczak 215 Mathematical Seminar, University of Kiel, Germany 16 Institute of Medical Informatics and Statistics, University of Kiel, Germany Keywords: Stepwise mutation model, microsatellite, recursion equation, temporal behaviour We consider the stepwise mutation model which occurs, e.g., in microsatellite loci. Let X(t,i) denote the allelic state of individual i at time t. We compute expectation, variance and covariance of X(t,i), i=1,,,N, and provide a recursion equation for P(X(t,i)=z). Because the variance of X(t,i) goes to infinity as t grows, for the description of the temporal behaviour, we regard the scaled process X(t,i)-X(t,1). The results furnish a better understanding of the behaviour of the stepwise mutation model and may in future be used to derive tests for neutrality under this model. Paul O'Reilly 1 , Ewan Birney 2 , David Balding 117 Statistical Genetics, Department of Epidemiology and Public Health, Imperial, College London, UK 18 European Bioinformatics Institute, EMBL, Cambridge, UK Keywords: Positive selection, Recombination rate, LD, Genome-wide, Natural Selection In recent years efforts to develop population genetics methods that estimate rates of recombination and levels of natural selection in the human genome have intensified. However, since the two processes have an intimately related impact on genetic variation their inference is vulnerable to confounding. Genomic regions subject to recent selection are likely to have a relatively recent common ancestor and consequently less opportunity for historical recombinations that are detectable in contemporary populations. Here we show that selection can reduce the population-based recombination rate estimate substantially. In genome-wide studies for detecting selection we observe a tendency to highlight loci that are subject to low levels of recombination. We find that the outlier approach commonly adopted in such studies may have low power unless variable recombination is accounted for. We introduce a new genome-wide method for detecting selection that exploits the sensitivity to recent selection of methods for estimating recombination rates, while accounting for variable recombination using pedigree data. Through simulations we demonstrate the high power of the Ped/Pop approach to discriminate between neutral and adaptive evolution, particularly in the context of choosing outliers from a genome-wide distribution. Although methods have been developed showing good power to detect selection ,in action', the corresponding window of opportunity is small. In contrast, the power of the Ped/Pop method is maintained for many generations after the fixation of an advantageous variant Sarah Griffiths 1 , Frank Dudbridge 120 MRC Biostatistics Unit, Cambridge, UK Keywords: Genetic association, multimarker tag, haplotype, likelihood analysis In association studies it is generally too expensive to genotype all variants in all subjects. We can exploit linkage disequilibrium between SNPs to select a subset that captures the variation in a training data set obtained either through direct resequencing or a public resource such as the HapMap. These ,tag SNPs' are then genotyped in the whole sample. Multimarker tagging is a more aggressive adaptation of pairwise tagging that allows for combinations of two or more tag SNPs to predict an untyped SNP. Here we describe a new method for directly testing the association of an untyped SNP using a multimarker tag. Previously, other investigators have suggested testing a specific tag haplotype, or performing a weighted analysis using weights derived from the training data. However these approaches do not properly account for the imperfect correlation between the tag haplotype and the untyped SNP. Here we describe a straightforward approach to testing untyped SNPs using a missing-data likelihood analysis, including the tag markers as nuisance parameters. The training data is stacked on top of the main body of genotype data so there is information on how the tag markers predict the genotype of the untyped SNP. The uncertainty in this prediction is automatically taken into account in the likelihood analysis. This approach yields more power and also a more accurate prediction of the odds ratio of the untyped SNP. Anke Schulz 1 , Christine Fischer 2 , Jenny Chang-Claude 1 , Lars Beckmann 121 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany 22 Institute of Human Genetics, University of Heidelberg, Germany Keywords: Haplotype, haplotype sharing, entropy, Mantel statistics, marker selection We previously introduced a new method to map genes involved in complex diseases, using haplotype sharing-based Mantel statistics to correlate genetic and phenotypic similarity. Although the Mantel statistic is powerful in narrowing down candidate regions, the precise localization of a gene is hampered in genomic regions where linkage disequilibrium is so high that neighboring markers are found to be significant at similar magnitude and we are not able to discriminate between them. Here, we present a new approach to localize susceptibility genes by combining haplotype sharing-based Mantel statistics with an iterative entropy-based marker selection algorithm. For each marker at which the Mantel statistic is evaluated, the algorithm selects a subset of surrounding markers. The subset is chosen to maximize multilocus linkage disequilibrium, which is measured by the normalized entropy difference introduced by Nothnagel et al. (2002). We evaluated the algorithm with respect to type I error and power. Its ability to localize the disease variant was compared to the localization (i) without marker selection and (ii) considering haplotype block structure. Case-control samples were simulated from a set of 18 haplotypes, consisting of 15 SNPs in two haplotype blocks. The new algorithm gave correct type I error and yielded similar power to detect the disease locus compared to the alternative approaches. The neighboring markers were clearly less often significant than the causal locus, and also less often significant compared to the alternative approaches. Thus the new algorithm improved the precision of the localization of susceptibility genes. Mark M. Iles 123 Section of Epidemiology and Biostatistics, LIMM, University of Leeds, UK Keywords: tSNP, tagging, association, HapMap Tagging SNPs (tSNPs) are commonly used to capture genetic diversity cost-effectively. However, it is important that the efficacy of tSNPs is correctly estimated, otherwise coverage may be insufficient. If the pilot sample from which tSNPs are chosen is too small or the initial marker map too sparse, tSNP efficacy may be overestimated. An existing estimation method based on bootstrapping goes some way to correct for insufficient sample size and overfitting, but does not completely solve the problem. We describe a novel method, based on exclusion of haplotypes, that improves on the bootstrap approach. Using simulated data, the extent of the sample size problem is investigated and the performance of the bootstrap and the novel method are compared. We incorporate an existing method adjusting for marker density by ,SNP-dropping'. We find that insufficient sample size can cause large overestimates in tSNP efficacy, even with as many as 100 individuals, and the problem worsens as the region studied increases in size. Both the bootstrap and novel method correct much of this overestimate, with our novel method consistently outperforming the bootstrap method. We conclude that a combination of insufficient sample size and overfitting may lead to overestimation of tSNP efficacy and underpowering of studies based on tSNPs. Our novel approach corrects for much of this bias and is superior to the previous method. Sample sizes larger than previously suggested may still be required for accurate estimation of tSNP efficacy. This has obvious ramifications for the selection of tSNPs from HapMap data. Claudio Verzilli 1 , Juliet Chapman 1 , Aroon Hingorani 2 , Juan Pablo-Casas 1 , Tina Shah 2 , Liam Smeeth 1 , John Whittaker 124 Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, UK 25 Division of Medicine, University College London, UK Keywords: Meta-analysis, Genetic association studies We present a Bayesian hierarchical model for the meta-analysis of candidate gene studies with a continuous outcome. Such studies often report results from association tests for different, possibly study-specific and non-overlapping markers (typically SNPs) in the same genetic region. Meta analyses of the results at each marker in isolation are seldom appropriate as they ignore the correlation that may exist between markers due to linkage disequlibrium (LD) and cannot assess the relative importance of variants at each marker. Also such marker-wise meta analyses are restricted to only those studies that have typed the marker in question, with a potential loss of power. A better strategy is one which incorporates information about the LD between markers so that any combined estimate of the effect of each variant is corrected for the effect of other variants, as in multiple regression. Here we develop a Bayesian hierarchical linear regression that models the observed genotype group means and uses pairwise LD measurements between markers as prior information to make posterior inference on adjusted effects. The approach is applied to the meta analysis of 24 studies assessing the effect of 7 variants in the C-reactive protein (CRP) gene region on plasma CRP levels, an inflammatory biomarker shown in observational studies to be positively associated with cardiovascular disease. Cathryn M. Lewis 1 , Christopher G. Mathew 1 , Theresa M. Marteau 226 Dept. of Medical and Molecular Genetics, King's College London, UK 27 Department of Psychology, King's College London, UK Keywords: Risk, genetics, CARD15, smoking, model Recently progress has been made in identifying mutations that confer susceptibility to complex diseases, with the potential to use these mutations in determining disease risk. We developed methods to estimate disease risk based on genotype relative risks (for a gene G), exposure to an environmental factor (E), and family history (with recurrence risk ,R for a relative of type R). ,R must be partitioned into the risk due to G (which is modelled independently) and the residual risk. The risk model was then applied to Crohn's disease (CD), a severe gastrointestinal disease for which smoking increases disease risk approximately 2-fold, and mutations in CARD15 confer increased risks of 2.25 (for carriers of a single mutation) and 9.3 (for carriers of two mutations). CARD15 accounts for only a small proportion of the genetic component of CD, with a gene-specific ,S, CARD15 of 1.16, from a total sibling relative risk of ,S= 27. CD risks were estimated for high-risk individuals who are siblings of a CD case, and who also smoke. The CD risk to such individuals who carry two CARD15 mutations is approximately 0.34, and for those carrying a single CARD15 mutation the risk is 0.08, compared to a population prevalence of approximately 0.001. These results imply that complex disease genes may be valuable in estimating with greater precision than has hitherto been possible disease risks in specific, easily identified subgroups of the population with a view to prevention. Yurii Aulchenko 128 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Compression, information, bzip2, genome-wide SNP data, statistical genetics With advances in molecular technology, studies accessing millions of genetic polymorphisms in thousands of study subjects will soon become common. Such studies generate large amounts of data, whose effective storage and management is a challenge to the modern statistical genetics. Standard file compression utilities, such as Zip, Gzip and Bzip2, may be helpful to minimise the storage requirements. Less obvious is the fact that the data compression techniques may be also used in the analysis of genetic data. It is known that the efficiency of a particular compression algorithm depends on the probability structure of the data. In this work, we compared different standard and customised tools using the data from human HapMap project. Secondly, we investigate the potential uses of data compression techniques for the analysis of linkage, association and linkage disequilibrium Suzanne Leal 1 , Bingshan Li 129 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, USA Keywords: Consanguineous pedigrees, missing genotype data Missing genotype data can increase false-positive evidence for linkage when either parametric or nonparametric analysis is carried out ignoring intermarker linkage disequilibrium (LD). Previously it was demonstrated by Huang et al (2005) that no bias occurs in this situation for affected sib-pairs with unrelated parents when either both parents are genotyped or genotype data is available for two additional unaffected siblings when parental genotypes are missing. However, this is not the case for consanguineous pedigrees, where missing genotype data for any pedigree member within a consanguinity loop can increase false-positive evidence of linkage. The false-positive evidence for linkage is further increased when cryptic consanguinity is present. The amount of false-positive evidence for linkage is highly dependent on which family members are genotyped. When parental genotype data is available, the false-positive evidence for linkage is usually not as strong as when parental genotype data is unavailable. Which family members will aid in the reduction of false-positive evidence of linkage is highly dependent on which other family members are genotyped. For a pedigree with an affected proband whose first-cousin parents have been genotyped, further reduction in the false-positive evidence of linkage can be obtained by including genotype data from additional affected siblings of the proband or genotype data from the proband's sibling-grandparents. When parental genotypes are not available, false-positive evidence for linkage can be reduced by including in the analysis genotype data from either unaffected siblings of the proband or the proband's married-in-grandparents. Najaf Amin 1 , Yurii Aulchenko 130 Department of Epidemiology & Biostatistics, Erasmus Medical Centre Rotterdam, The Netherlands Keywords: Genomic Control, pedigree structure, quantitative traits The Genomic Control (GC) method was originally developed to control for population stratification and cryptic relatedness in association studies. This method assumes that the effect of population substructure on the test statistics is essentially constant across the genome, and therefore unassociated markers can be used to estimate the effect of confounding onto the test statistic. The properties of GC method were extensively investigated for different stratification scenarios, and compared to alternative methods, such as the transmission-disequilibrium test. The potential of this method to correct not for occasional cryptic relations, but for regular pedigree structure, however, was not investigated before. In this work we investigate the potential of the GC method for pedigree-based association analysis of quantitative traits. The power and type one error of the method was compared to standard methods, such as the measured genotype (MG) approach and quantitative trait transmission-disequilibrium test. In human pedigrees, with trait heritability varying from 30 to 80%, the power of MG and GC approach was always higher than that of TDT. GC had correct type 1 error and its power was close to that of MG under moderate heritability (30%), but decreased with higher heritability. William Astle 1 , Chris Holmes 2 , David Balding 131 Department of Epidemiology and Public Health, Imperial College London, UK 32 Department of Statistics, University of Oxford, UK Keywords: Population structure, association studies, genetic epidemiology, statistical genetics In the analysis of population association studies, Genomic Control (Devlin & Roeder, 1999) (GC) adjusts the Armitage test statistic to correct the type I error for the effects of population substructure, but its power is often sub-optimal. Turbo Genomic Control (TGC) generalises GC to incorporate co-variation of relatedness and phenotype, retaining control over type I error while improving power. TGC is similar to the method of Yu et al. (2006), but we extend it to binary (case-control) in addition to quantitative phenotypes, we implement improved estimation of relatedness coefficients, and we derive an explicit statistic that generalizes the Armitage test statistic and is fast to compute. TGC also has similarities to EIGENSTRAT (Price et al., 2006) which is a new method based on principle components analysis. The problems of population structure(Clayton et al., 2005) and cryptic relatedness (Voight & Pritchard, 2005) are essentially the same: if patterns of shared ancestry differ between cases and controls, whether distant (coancestry) or recent (cryptic relatedness), false positives can arise and power can be diminished. With large numbers of widely-spaced genetic markers, coancestry can now be measured accurately for each pair of individuals via patterns of allele-sharing. Instead of modelling subpopulations, we work instead with a coancestry coefficient for each pair of individuals in the study. We explain the relationships between TGC, GC and EIGENSTRAT. We present simulation studies and real data analyses to illustrate the power advantage of TGC in a range of scenarios incorporating both substructure and cryptic relatedness. References Clayton, D. G.et al. (2005) Population structure, differential bias and genomic control in a large-scale case-control association study. Nature Genetics37(11) November 2005. Devlin, B. & Roeder, K. (1999) Genomic control for association studies. Biometics55(4) December 1999. Price, A. L.et al. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nature Genetics38(8) (August 2006). Voight, B. J. & Pritchard, J. K. (2005) Confounding from cryptic relatedness in case-control association studies. Public Library of Science Genetics1(3) September 2005. Yu, J.et al. (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics38(2) February 2006. Hervé Perdry 1 , Marie-Claude Babron 1 , Françoise Clerget-Darpoux 133 INSERM U535 and Univ. Paris Sud, UMR-S 535, Villejuif, France Keywords: Modifier genes, case-parents trios, ordered transmission disequilibrium test A modifying locus is a polymorphic locus, distinct from the disease locus, which leads to differences in the disease phenotype, either by modifying the penetrance of the disease allele, or by modifying the expression of the disease. The effect of such a locus is a clinical heterogeneity that can be reflected by the values of an appropriate covariate, such as the age of onset, or the severity of the disease. We designed the Ordered Transmission Disequilibrium Test (OTDT) to test for a relation between the clinical heterogeneity, expressed by the covariate, and marker genotypes of a candidate gene. The method applies to trio families with one affected child and his parents. Each family member is genotyped at a bi-allelic marker M of a candidate gene. To each of the families is associated a covariate value; the families are ordered on the values of this covariate. As the TDT (Spielman et al. 1993), the OTDT is based on the observation of the transmission rate T of a given allele at M. The OTDT aims to find a critical value of the covariate which separates the sample of families in two subsamples in which the transmission rates are significantly different. We investigate the power of the method by simulations under various genetic models and covariate distributions. Acknowledgments H Perdry is funded by ARSEP. Pascal Croiseau 1 , Heather Cordell 2 , Emmanuelle Génin 134 INSERM U535 and University Paris Sud, UMR-S535, Villejuif, France 35 Institute of Human Genetics, Newcastle University, UK Keywords: Association, missing data, conditionnal logistic regression Missing data is an important problem in association studies. Several methods used to test for association need that individuals be genotyped at the full set of markers. Individuals with missing data need to be excluded from the analysis. This could involve an important decrease in sample size and a loss of information. If the disease susceptibility locus (DSL) is poorly typed, it is also possible that a marker in linkage disequilibrium gives a stronger association signal than the DSL. One may then falsely conclude that the marker is more likely to be the DSL. We recently developed a Multiple Imputation method to infer missing data on case-parent trios Starting from the observed data, a few number of complete data sets are generated by Markov-Chain Monte Carlo approach. These complete datasets are analysed using standard statistical package and the results are combined as described in Little & Rubin (2002). Here we report the results of simulations performed to examine, for different patterns of missing data, how often the true DSL gives the highest association score among different loci in LD. We found that multiple imputation usually correctly detect the DSL site even if the percentage of missing data is high. This is not the case for the naïve approach that consists in discarding trios with missing data. In conclusion, Multiple imputation presents the advantage of being easy to use and flexible and is therefore a promising tool in the search for DSL involved in complex diseases. Salma Kotti 1 , Heike Bickeböller 2 , Françoise Clerget-Darpoux 136 University Paris Sud, UMR-S535, Villejuif, France 37 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany Keywords: Genotype relative risk, internal controls, Family based analyses Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRRs. We will analytically derive the GRR estimators for the 1:1 and 1:3 matching and will present the results at the meeting. Family based analyses using internal controls are very popular both for detecting the effect of a genetic factor and for estimating the relative disease risk on the corresponding genotypes. Two different procedures are often applied to reconstitute internal controls. The first one considers one pseudocontrol genotype formed by the parental non-transmitted alleles called also 1:1 matching of alleles, while the second corresponds to three pseudocontrols corresponding to all genotypes formed by the parental alleles except the one of the case (1:3 matching). Many studies have compared between the two procedures in terms of the power and have concluded that the difference depends on the underlying genetic model and the allele frequencies. However, the estimation of the Genotype Relative Risk (GRR) under the two procedures has not been studied. Based on the fact that on the 1:1 matching, the control group is composed of the alleles untransmitted to the affected child and on the 1:3 matching, the control group is composed amongst alleles already transmitted to the affected child, we expect a difference on the GRR estimation. In fact, we suspect that the second procedure leads to biased estimation of the GRR. We will analytically derive the GRR estimator for the 1:1 and 1:3 matching and will present the results at the meeting. Luigi Palla 1 , David Siegmund 239 Department of Mathematics,Free University Amsterdam, The Netherlands 40 Department of Statistics, Stanford University, California, USA Keywords: TDT, assortative mating, inbreeding, statistical power A substantial amount of Assortative Mating (AM) is often recorded on physical and psychological, dichotomous as well as quantitative traits that are supposed to have a multifactorial genetic component. In particular AM has the effect of increasing the genetic variance, even more than inbreeding because it acts across loci beside within loci, when the trait has a multifactorial origin. Under the assumption of a polygenic model for AM dating back to Wright (1921) and refined by Crow and Felsenstein (1968,1982), the effect of assortative mating on the power to detect genetic association in the Transmission Disequilibrium Test (TDT) is explored as parameters, such as the effective number of genes and the allelic frequency vary. The power is reflected by the non centrality parameter of the TDT and is expressed as a function of the number of trios, the relative risk of the heterozygous genotype and the allele frequency (Siegmund and Yakir, 2007). The noncentrality parameter of the relevant score statistic is updated considering the effect of AM which is expressed in terms of an ,effective' inbreeding coefficient. In particular, for dichotomous traits it is apparent that the higher the number of genes involved in the trait, the lower the loss in power due to AM. Finally an attempt is made to extend this relation to the Q-TDT (Rabinowitz, 1997), which involves considering the effect of AM also on the phenotypic variance of the trait of interest, under the assumption that AM affects only its additive genetic component. References Crow, & Felsenstein, (1968). The effect of assortative mating on the genetic composition of a population. Eugen.Quart.15, 87,97. Rabinowitz,, 1997. A Transmission Disequilibrium Test for Quantitative Trait Loci. Human Heredity47, 342,350. Siegmund, & Yakir, (2007) Statistics of gene mapping, Springer. Wright, (1921). System of mating.III. Assortative mating based on somatic resemblance. Genetics6, 144,161. Jérémie Nsengimana 1 , Ben D Brown 2 , Alistair S Hall 2 , Jenny H Barrett 141 Leeds Institute of Molecular Medicine, University of Leeds, UK 42 Leeds Institute for Genetics, Health and Therapeutics, University of Leeds, UK Keywords: Inflammatory genes, haplotype, coronary artery disease Genetic Risk of Acute Coronary Events (GRACE) is an initiative to collect cases of coronary artery disease (CAD) and their unaffected siblings in the UK and to use them to map genetic variants increasing disease risk. The aim of the present study was to test the association between CAD and 51 single nucleotide polymorphisms (SNPs) and their haplotypes from 35 inflammatory genes. Genotype data were available for 1154 persons affected before age 66 (including 48% before age 50) and their 1545 unaffected siblings (891 discordant families). Each SNP was tested for association to CAD, and haplotypes within genes or gene clusters were tested using FBAT (Rabinowitz & Laird, 2000). For the most significant results, genetic effect size was estimated using conditional logistic regression (CLR) within STATA adjusting for other risk factors. Haplotypes were assigned using HAPLORE (Zhang et al., 2005), which considers all parental mating types consistent with offspring genotypes and assigns them a probability of occurence. This probability was used in CLR to weight the haplotypes. In the single SNP analysis, several SNPs showed some evidence for association, including one SNP in the interleukin-1A gene. Analysing haplotypes in the interleukin-1 gene cluster, a common 3-SNP haplotype was found to increase the risk of CAD (P = 0.009). In an additive genetic model adjusting for covariates the odds ratio (OR) for this haplotype is 1.56 (95% CI: 1.16-2.10, p = 0.004) for early-onset CAD (before age 50). This study illustrates the utility of haplotype analysis in family-based association studies to investigate candidate genes. References Rabinowitz, D. & Laird, N. M. (2000) Hum Hered50, 211,223. Zhang, K., Sun, F. & Zhao, H. (2005) Bioinformatics21, 90,103. Andrea Foulkes 1 , Recai Yucel 1 , Xiaohong Li 143 Division of Biostatistics, University of Massachusetts, USA Keywords: Haploytpe, high-dimensional, mixed modeling The explosion of molecular level information coupled with large epidemiological studies presents an exciting opportunity to uncover the genetic underpinnings of complex diseases; however, several analytical challenges remain to be addressed. Characterizing the components to complex diseases inevitably requires consideration of synergies across multiple genetic loci and environmental and demographic factors. In addition, it is critical to capture information on allelic phase, that is whether alleles within a gene are in cis (on the same chromosome) or in trans (on different chromosomes.) In associations studies of unrelated individuals, this alignment of alleles within a chromosomal copy is generally not observed. We address the potential ambiguity in allelic phase in this high dimensional data setting using mixed effects models. Both a semi-parametric and fully likelihood-based approach to estimation are considered to account for missingness in cluster identifiers. In the first case, we apply a multiple imputation procedure coupled with a first stage expectation maximization algorithm for parameter estimation. A bootstrap approach is employed to assess sensitivity to variability induced by parameter estimation. Secondly, a fully likelihood-based approach using an expectation conditional maximization algorithm is described. Notably, these models allow for characterizing high-order gene-gene interactions while providing a flexible statistical framework to account for the confounding or mediating role of person specific covariates. The proposed method is applied to data arising from a cohort of human immunodeficiency virus type-1 (HIV-1) infected individuals at risk for therapy associated dyslipidemia. Simulation studies demonstrate reasonable power and control of family-wise type 1 error rates. Vivien Marquard 1 , Lars Beckmann 1 , Jenny Chang-Claude 144 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Genotyping errors, type I error, haplotype-based association methods It has been shown in several simulation studies that genotyping errors may have a great impact on the type I error of statistical methods used in genetic association analysis of complex diseases. Our aim was to investigate type I error rates in a case-control study, when differential and non-differential genotyping errors were introduced in realistic scenarios. We simulated case-control data sets, where individual genotypes were drawn from a haplotype distribution of 18 haplotypes with 15 markers in the APM1 gene. Genotyping errors were introduced following the unrestricted and symmetric with 0 edges error models described by Heid et al. (2006). In six scenarios, errors resulted from changes of one allele to another with predefined probabilities of 1%, 2.5% or 10%, respectively. A multiple number of errors per haplotype was possible and could vary between 0 and 15, the number of markers investigated. We examined three association methods: Mantel statistics using haplotype-sharing; a haplotype-specific score test; and Armitage trend test for single markers. The type I error rates were not influenced for any of all the three methods for a genotyping error rate of less than 1%. For higher error rates and differential errors, the type I error of the Mantel statistic was only slightly and of the Armitage trend test moderately increased. The type I error rates of the score test were highly increased. The type I error rates were correct for all three methods for non-differential errors. Further investigations will be carried out with different frequencies of differential error rates and focus on power. Arne Neumann 1 , Dörthe Malzahn 1 , Martina Müller 2 , Heike Bickeböller 145 Department of Genetic Epidemiology, Medical School, University of Göttingen, Germany 46 GSF-National Research Center for Environment and Health, Neuherberg & IBE-Institute of Epidemiology, Ludwig-Maximilians University München, Germany Keywords: Interaction, longitudinal, nonparametric Longitudinal data show the time dependent course of phenotypic traits. In this contribution, we consider longitudinal cohort studies and investigate the association between two candidate genes and a dependent quantitative longitudinal phenotype. The set-up defines a factorial design which allows us to test simultaneously for the overall gene effect of the loci as well as for possible gene-gene and gene time interaction. The latter would induce genetically based time-profile differences in the longitudinal phenotype. We adopt a non-parametric statistical test to genetic epidemiological cohort studies and investigate its performance by simulation studies. The statistical test was originally developed for longitudinal clinical studies (Brunner, Munzel, Puri, 1999 J Multivariate Anal 70:286-317). It is non-parametric in the sense that no assumptions are made about the underlying distribution of the quantitative phenotype. Longitudinal observations belonging to the same individual can be arbitrarily dependent on one another for the different time points whereas trait observations of different individuals are independent. The two loci are assumed to be statistically independent. Our simulations show that the nonparametric test is comparable with ANOVA in terms of power of detecting gene-gene and gene-time interaction in an ANOVA favourable setting. Rebecca Hein 1 , Lars Beckmann 1 , Jenny Chang-Claude 147 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ) Heidelberg, Germany Keywords: Indirect association studies, interaction effects, linkage disequilibrium, marker allele frequency Association studies accounting for gene-environment interactions (GxE) may be useful for detecting genetic effects and identifying important environmental effect modifiers. Current technology facilitates very dense marker spacing in genetic association studies; however, the true disease variant(s) may not be genotyped. In this situation, an association between a gene and a phenotype may still be detectable, using genetic markers associated with the true disease variant(s) (indirect association). Zondervan and Cardon [2004] showed that the odds ratios (OR) of markers which are associated with the disease variant depend highly on the linkage disequilibrium (LD) between the variant and the markers, and whether the allele frequencies match and thereby influence the sample size needed to detect genetic association. We examined the influence of LD and allele frequencies on the sample size needed to detect GxE in indirect association studies, and provide tables for sample size estimation. For discordant allele frequencies and incomplete LD, sample sizes can be unfeasibly large. The influence of both factors is stronger for disease loci with small rather than moderate to high disease allele frequencies. A decline in D' of e.g. 5% has less impact on sample size than increasing the difference in allele frequencies by the same percentage. Assuming 80% power, large interaction effects can be detected using smaller sample sizes than those needed for the detection of main effects. The detection of interaction effects involving rare alleles may not be possible. Focussing only on marker density can be a limited strategy in indirect association studies for GxE. Cyril Dalmasso 1 , Emmanuelle Génin 2 , Catherine Bourgain 2 , Philippe Broët 148 JE 2492 , Univ. Paris-Sud, France 49 INSERM UMR-S 535 and University Paris Sud, Villejuif, France Keywords: Linkage analysis, Multiple testing, False Discovery Rate, Mixture model In the context of genome-wide linkage analyses, where a large number of statistical tests are simultaneously performed, the False Discovery Rate (FDR) that is defined as the expected proportion of false discoveries among all discoveries is nowadays widely used for taking into account the multiple testing problem. Other related criteria have been considered such as the local False Discovery Rate (lFDR) that is a variant of the FDR giving to each test its own measure of significance. The lFDR is defined as the posterior probability that a null hypothesis is true. Most of the proposed methods for estimating the lFDR or the FDR rely on distributional assumption under the null hypothesis. However, in observational studies, the empirical null distribution may be very different from the theoretical one. In this work, we propose a mixture model based approach that provides estimates of the lFDR and the FDR in the context of large-scale variance component linkage analyses. In particular, this approach allows estimating the empirical null distribution, this latter being a key quantity for any simultaneous inference procedure. The proposed method is applied on a real dataset. Arief Gusnanto 1 , Frank Dudbridge 150 MRC Biostatistics Unit, Cambridge UK Keywords: Significance, genome-wide, association, permutation, multiplicity Genome-wide association scans have introduced statistical challenges, mainly in the multiplicity of thousands of tests. The question of what constitutes a significant finding remains somewhat unresolved. Permutation testing is very time-consuming, whereas Bayesian arguments struggle to distinguish direct from indirect association. It seems attractive to summarise the multiplicity in a simple form that allows users to avoid time-consuming permutations. A standard significance level would facilitate reporting of results and reduce the need for permutation tests. This is potentially important because current scans do not have full coverage of the whole genome, and yet, the implicit multiplicity is genome-wide. We discuss some proposed summaries, with reference to the empirical null distribution of the multiple tests, approximated through a large number of random permutations. Using genome-wide data from the Wellcome Trust Case-Control Consortium, we use a sub-sampling approach with increasing density to estimate the nominal p-value to obtain family-wise significance of 5%. The results indicate that the significance level is converging to about 1e-7 as the marker spacing becomes infinitely dense. We considered the concept of an effective number of independent tests, and showed that when used in a Bonferroni correction, the number varies with the overall significance level, but is roughly constant in the region of interest. We compared several estimators of the effective number of tests, and showed that in the region of significance of interest, Patterson's eigenvalue based estimator gives approximately the right family-wise error rate. Michael Nothnagel 1 , Amke Caliebe 1 , Michael Krawczak 151 Institute of Medical Informatics and Statistics, University Clinic Schleswig-Holstein, University of Kiel, Germany Keywords: Association scans, Bayesian framework, posterior odds, genetic risk, multiplicative model Whole-genome association scans have been suggested to be a cost-efficient way to survey genetic variation and to map genetic disease factors. We used a Bayesian framework to investigate the posterior odds of a genuine association under multiplicative disease models. We demonstrate that the p value alone is not a sufficient means to evaluate the findings in association studies. We suggest that likelihood ratios should accompany p values in association reports. We argue, that, given the reported results of whole-genome scans, more associations should have been successfully replicated if the consistently made assumptions about considerable genetic risks were correct. We conclude that it is very likely that the vast majority of relative genetic risks are only of the order of 1.2 or lower. Clive Hoggart 1 , Maria De Iorio 1 , John Whittakker 2 , David Balding 152 Department of Epidemiology and Public Health, Imperial College London, UK 53 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: Genome-wide association analyses, shrinkage priors, Lasso Testing one SNP at a time does not fully realise the potential of genome-wide association studies to identify multiple causal variants of small effect, which is a plausible scenario for many complex diseases. Moreover, many simulation studies assume a single causal variant and so more complex realities are ignored. Analysing large numbers of variants simultaneously is now becoming feasible, thanks to developments in Bayesian stochastic search methods. We pose the problem of SNP selection as variable selection in a regression model. In contrast to single SNP tests this approach simultaneously models the effect of all SNPs. SNPs are selected by a Bayesian interpretation of the lasso (Tibshirani, 1996); the maximum a posterior (MAP) estimate of the regression coefficients, which have been given independent, double exponential prior distributions. The double exponential distribution is an example of a shrinkage prior, MAP estimates with shrinkage priors can be zero, thus all SNPs with non zero regression coefficients are selected. In addition to the commonly-used double exponential (Laplace) prior, we also implement the normal exponential gamma prior distribution. We show that use of the Laplace prior improves SNP selection in comparison with single -SNP tests, and that the normal exponential gamma prior leads to a further improvement. Our method is fast and can handle very large numbers of SNPs: we demonstrate its performance using both simulated and real genome-wide data sets with 500 K SNPs, which can be analysed in 2 hours on a desktop workstation. Mickael Guedj 1,2 , Jerome Wojcik 2 , Gregory Nuel 154 Laboratoire Statistique et Génome, Université d'Evry, Evry France 55 Serono Pharmaceutical Research Institute, Plan-les-Ouates, Switzerland Keywords: Local Replication, Local Score, Association In gene-mapping, replication of initial findings has been put forwards as the approach of choice for filtering false-positives from true signals for underlying loci. In practice, such replications are however too poorly observed. Besides the statistical and technical-related factors (lack of power, multiple-testing, stratification, quality control,) inconsistent conclusions obtained from independent populations might result from real biological differences. In particular, the high degree of variation in the strength of LD among populations of different origins is a major challenge to the discovery of genes. Seeking for Local Replications (defined as the presence of a signal of association in a same genomic region among populations) instead of strict replications (same locus, same risk allele) may lead to more reliable results. Recently, a multi-markers approach based on the Local Score statistic has been proposed as a simple and efficient way to select candidate genomic regions at the first stage of genome-wide association studies. Here we propose an extension of this approach adapted to replicated association studies. Based on simulations, this method appears promising. In particular it outperforms classical simple-marker strategies to detect modest-effect genes. Additionally it constitutes, to our knowledge, a first framework dedicated to the detection of such Local Replications. Juliet Chapman 1 , Claudio Verzilli 1 , John Whittaker 156 Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, UK Keywords: FDR, Association studies, Bayesian model selection As genomewide association studies become commonplace there is debate as to how such studies might be analysed and what we might hope to gain from the data. It is clear that standard single locus approaches are limited in that they do not adjust for the effects of other loci and problematic since it is not obvious how to adjust for multiple comparisons. False discovery rates have been suggested, but it is unclear how well these will cope with highly correlated genetic data. We consider the validity of standard false discovery rates in large scale association studies. We also show that a Bayesian procedure has advantages in detecting causal loci amongst a large number of dependant SNPs and investigate properties of a Bayesian FDR. Peter Kraft 157 Harvard School of Public Health, Boston USA Keywords: Gene-environment interaction, genome-wide association scans Appropriately analyzed two-stage designs,where a subset of available subjects are genotyped on a genome-wide panel of markers at the first stage and then a much smaller subset of the most promising markers are genotyped on the remaining subjects,can have nearly as much power as a single-stage study where all subjects are genotyped on the genome-wide panel yet can be much less expensive. Typically, the "most promising" markers are selected based on evidence for a marginal association between genotypes and disease. Subsequently, the few markers found to be associated with disease at the end of the second stage are interrogated for evidence of gene-environment interaction, mainly to understand their impact on disease etiology and public health impact. However, this approach may miss variants which have a sizeable effect restricted to one exposure stratum and therefore only a modest marginal effect. We have proposed to use information on the joint effects of genes and a discrete list of environmental exposures at the initial screening stage to select promising markers for the second stage [Kraft et al Hum Hered 2007]. This approach optimizes power to detect variants that have a sizeable marginal effect and variants that have a small marginal effect but a sizeable effect in a stratum defined by an environmental exposure. As an example, I discuss a proposed genome-wide association scan for Type II diabetes susceptibility variants based in several large nested case-control studies. Beate Glaser 1 , Peter Holmans 158 Biostatistics and Bioinformatics Unit, Cardiff University, School of Medicine, Heath Park, Cardiff, UK Keywords: Combined case-control and trios analysis, Power, False-positive rate, Simulation, Association studies The statistical power of genetic association studies can be enhanced by combining the analysis of case-control with parent-offspring trio samples. Various combined analysis techniques have been recently developed; as yet, there have been no comparisons of their power. This work was performed with the aim of identifying the most powerful method among available combined techniques including test statistics developed by Kazeem and Farrall (2005), Nagelkerke and colleagues (2004) and Dudbridge (2006), as well as a simple combination of ,2-statistics from single samples. Simulation studies were performed to investigate their power under different additive, multiplicative, dominant and recessive disease models. False-positive rates were determined by studying the type I error rates under null models including models with unequal allele frequencies between the single case-control and trios samples. We identified three techniques with equivalent power and false-positive rates, which included modifications of the three main approaches: 1) the unmodified combined Odds ratio estimate by Kazeem & Farrall (2005), 2) a modified approach of the combined risk ratio estimate by Nagelkerke & colleagues (2004) and 3) a modified technique for a combined risk ratio estimate by Dudbridge (2006). Our work highlights the importance of studies investigating test performance criteria of novel methods, as they will help users to select the optimal approach within a range of available analysis techniques. David Almorza 1 , M.V. Kandus 2 , Juan Carlos Salerno 2 , Rafael Boggio 359 Facultad de Ciencias del Trabajo, University of Cádiz, Spain 60 Instituto de Genética IGEAF, Buenos Aires, Argentina 61 Universidad Nacional de La Plata, Buenos Aires, Argentina Keywords: Principal component analysis, maize, ear weight, inbred lines The objective of this work was to evaluate the relationship among different traits of the ear of maize inbred lines and to group genotypes according to its performance. Ten inbred lines developed at IGEAF (INTA Castelar) and five public inbred lines as checks were used. A field trial was carried out in Castelar, Buenos Aires (34° 36' S , 58° 39' W) using a complete randomize design with three replications. At harvest, individual weight (P.E.), diameter (D.E.), row number (N.H.) and length (L.E.) of the ear were assessed. A principal component analysis, PCA, (Infostat 2005) was used, and the variability of the data was depicted with a biplot. Principal components 1 and 2 (CP1 and CP2) explained 90% of the data variability. CP1 was correlated with P.E., L.E. and D.E., meanwhile CP2 was correlated with N.H. We found that individual weight (P.E.) was more correlated with diameter of the ear (D.E.) than with length (L.E). Five groups of inbred lines were distinguished: with high P.E. and mean N.H. (04-70, 04-73, 04-101 and MO17), with high P.E. but less N.H. (04-61 and B14), with mean P.E. and N.H. (B73, 04-123 and 04-96), with high N.H. but less P.E. (LP109, 04-8, 04-91 and 04-76) and with low P.E. and low N.H. (LP521 and 04-104). The use of PCA showed which variables had more incidence in ear weight and how is the correlation among them. Moreover, the different groups found with this analysis allow the evaluation of inbred lines by several traits simultaneously. Sven Knüppel 1 , Anja Bauerfeind 1 , Klaus Rohde 162 Department of Bioinformatics, MDC Berlin, Germany Keywords: Haplotypes, association studies, case-control, nuclear families The area of gene chip technology provides a plethora of phase-unknown SNP genotypes in order to find significant association to some genetic trait. To circumvent possibly low information content of a single SNP one groups successive SNPs and estimates haplotypes. Haplotype estimation, however, may reveal ambiguous haplotype pairs and bias the application of statistical methods. Zaykin et al. (Hum Hered, 53:79-91, 2002) proposed the construction of a design matrix to take this ambiguity into account. Here we present a set of functions written for the Statistical package R, which carries out haplotype estimation on the basis of the EM-algorithm for individuals (case-control) or nuclear families. The construction of a design matrix on basis of estimated haplotypes or haplotype pairs allows application of standard methods for association studies (linear, logistic regression), as well as statistical methods as haplotype sharing statistics and TDT-Test. Applications of these methods to genome-wide association screens will be demonstrated. Manuela Zucknick 1 , Chris Holmes 2 , Sylvia Richardson 163 Department of Epidemiology and Public Health, Imperial College London, UK 64 Department of Statistics, Oxford Center for Gene Function, University of Oxford, UK Keywords: Bayesian, variable selection, MCMC, large p, small n, structured dependence In large-scale genomic applications vast numbers of markers or genes are scanned to find a few candidates which are linked to a particular phenotype. Statistically, this is a variable selection problem in the "large p, small n" situation where many more variables than samples are available. An additional feature is the complex dependence structure which is often observed among the markers/genes due to linkage disequilibrium or their joint involvement in biological processes. Bayesian variable selection methods using indicator variables are well suited to the problem. Binary phenotypes like disease status are common and both Bayesian probit and logistic regression can be applied in this context. We argue that logistic regression models are both easier to tune and to interpret than probit models and implement the approach by Holmes & Held (2006). Because the model space is vast, MCMC methods are used as stochastic search algorithms with the aim to quickly find regions of high posterior probability. In a trade-off between fast-updating but slow-moving single-gene Metropolis-Hastings samplers and computationally expensive full Gibbs sampling, we propose to employ the dependence structure among the genes/markers to help decide which variables to update together. Also, parallel tempering methods are used to aid bold moves and help avoid getting trapped in local optima. Mixing and convergence of the resulting Markov chains are evaluated and compared to standard samplers in both a simulation study and in an application to a gene expression data set. Reference Holmes, C. C. & Held, L. (2006) Bayesian auxiliary variable models for binary and multinomial regression. Bayesian Analysis1, 145,168. Dawn Teare 165 MMGE, University of Sheffield, UK Keywords: CNP, family-based analysis, MCMC Evidence is accumulating that segmental copy number polymorphisms (CNPs) may represent a significant portion of human genetic variation. These highly polymorphic systems require handling as phenotypes rather than co-dominant markers, placing new demands on family-based analyses. We present an integrated approach to meet these challenges in the form of a graphical model, where the underlying discrete CNP phenotype is inferred from the (single or replicate) quantitative measure within the analysis, whilst assuming an allele based system segregating through the pedigree. [source] Child abuse in South Africa: rights and wrongsCHILD ABUSE REVIEW, Issue 2 2008Linda M. Richter Abstract In a country in which human rights feature prominently in our discourse about who we are, as well as in the South African constitutional and legal framework, so many wrongs continue to be done to children. One category of wrongs is abuse, but it is not the only one. Poverty, patriarchy and gender violence, as well as the socialised obedience, dependency and silence of women and children, create conditions in which abuse can occur, often with few consequences. South Africa has extremely high rates of both physical and sexual abuse of children. Progressive, rights-based legislation exists to protect children, but it is not adequately supported or resourced by services to fulfil their provisions. Child abuse and neglect will not be significantly reduced in South Africa, without simultaneous improvements in the social and economic conditions in which very large numbers of children live. Copyright © 2008 John Wiley & Sons, Ltd. [source] | ||||||||||||||||||||||||||||||||||