Jiang N.,University of Birmingham |
Wang M.,University of Birmingham |
Jia T.,University of Birmingham |
Wang L.,Fudan University |
And 5 more authors.
PLoS ONE | Year: 2011
Background: It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS) is statistical inference of linkage disequilibrium (LD) between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation. Methodology: We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations. Results/Conclusions: The analyses show that the new method confers an improved statistical power for detecting genuine genetic association in subpopulations and an effective control of spurious associations stemmed from population structure when compared with other two popularly implemented methods in the literature of GWAS. © 2011 Jiang et al.
Tolkamp B.J.,Animal Health Group |
Allcroft D.J.,BioSS |
Barrio J.P.,University of Leon |
Bley T.A.G.,University of Hohenheim |
And 7 more authors.
American Journal of Physiology - Regulatory Integrative and Comparative Physiology | Year: 2011
Meals have long been considered relevant units of feeding behavior. Large data sets of feeding behavior of cattle, pigs, chickens, ducks, turkeys, dolphins, and rats were analyzed with the aims of 1) describing the temporal structure of feeding behavior and 2) developing appropriate methods for estimating meal criteria. Longer (between-meal) intervals were never distributed as the negative exponential assumed by traditional methods, such as log-survivorship analysis, but as a skewed Gaussian, which can be (almost) normalized by log-transformation of interval lengths. Log-transformation can also normalize frequency distributions of within-meal intervals. Meal criteria, i.e., the longest interval considered to occur within meals, can be estimated after fitting models consisting of Gaussian functions alone or of one Weibull and one or more Gaussian functions to the distribution of log-transformed interval lengths. Nonuniform data sets may require disaggregation before this can be achieved. Observations from all species were in conflict with assumptions of random behavior that underlie traditional methods for criteria estimation. Instead, the observed structure of feeding behavior is consistent with 1) a decrease in satiety associated with an increase in the probability of animals starting a meal with time since the last meal and 2) an increase in satiation associated with an increase in the probability of animals ending a meal with the amount of food already consumed. The novel methodology proposed here will avoid biased conclusions from analyses of feeding behavior associated with previous methods and, as demonstrated, can be applied across a range of species to address questions relevant to the control of food intake. © 2011 the American Physiological Society.
Orcic D.Z.,University of Novi Sad |
Mimica-Dukic N.M.,University of Novi Sad |
Franciskovic M.M.,University of Novi Sad |
Petrovic S.S.,BioSS |
Jovin E.T.,University of Novi Sad
Chemistry Central Journal | Year: 2011
Background: The St John's Wort (Hypericum perforatum; Clusiaceae) has been used in traditional and modern medicine for a long time due to its high content of biologically active phenolics. The purpose of this work was to develop a method for their fractionation and identification, and to determine the most active antioxidant compounds in plant extract.Results: An LC-MS method which enables fast qualitative and semiquantitative analysis was developed. The composition determined is in agreement with the previous results, where 6 flavonoids, 4 naphthodianthrones and 4 phloroglucinols have been identified. Significant antioxidant activity was determined for most of the fractions by DPPH assay (the lowest IC50of 0.52 μg/ml), NO scavenging (6.11 μg/ml), superoxide scavenging (1.86 μg/ml), lipid peroxidation (0.0079 μg/ml) and FRAP (the highest reduction capacity of 104 mg Fe equivalents/g) assays.Conclusion: LC-MS technique has been successfully applied for a quick separation and identification of the major components of H. perforatum fractions. Majority of the fractions analyzed have expressed a very high antioxidative activity when compared to synthetic antioxidants. The antioxidant activity could be attributed to flavonoids and phenolic acids, while phloroglucinols and naphthodianthrones showed no significant activity. It is demonstrated that it is possible to obtain, by fractionation, H. perforatum preparations with significantly increased phloroglucinols-to-naphthodianthrones ratio (up to 95:5). © 2011 Orčić et al.
Poggio L.,James Hutton Institute |
Gimona A.,James Hutton Institute |
Geoderma | Year: 2013
Knowledge of soil properties with complete area coverage is needed for policy-making, land resource management, and monitoring environmental impacts. Remote sensing offers possibilities to support Digital Soil Mapping, especially in data-poor regions. The aim of this work was to test the potential of time-series of MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation and drought indices to provide relevant information to model topsoil properties in a Boreal-Atlantic region (Scotland) focussing on differentiation between soils with high and soils with low organic matter contents. For each of the three considered years, 345 MODIS data sets were included in the exploratory analysis; 15 data products for 23 dates (bi-weekly) per year. Terrain parameters derived from Shuttle Radar Topography Mission were also included. A methodology was implemented to exploit fully the high number of covariates, to identify the band, index or product that best correlates with the soil property of interest. In particular the proposed approach i. relies on freely globally available data-sets; ii. uses statistical criteria to select the combination of covariates providing the highest predictive capability, among the data considered and available; iii. deals with both continuous (using Generalized Additive Models, GAMs) and multinomial categorical (using Random Trees) types of variables; iv. takes into account fully the spatial autocorrelation of the data; v. provides estimates of the spatial uncertainty for each pixel; and vi. is computationally efficient when compared with methods such as forward stepwise. The models fitted show a fairly good agreement with existing data sets, presenting a consistent spatial pattern. The use of MODIS data as covariates increased the predictive capabilities of GAMs using only terrain parameters. The misclassification error for organic matter classes was between 25 and 35%. The assessment provided of the spatial uncertainty of the modelled values can be used in further modelling and in the assessment of consequences of climate-change and trade-off in land use changes. This approach can contribute to improving our understanding and modelling of soil processes and function over large, and relatively sparsely sampled, areas of the world. © 2013 Elsevier B.V.
McVittie A.,SAC |
Moran D.,SAC |
Regional Studies | Year: 2010
MCVITTIE A., MORAN D. and ELSTON D. Public preferences for rural policy reform: evidence from Scottish surveys, Regional Studies. Agricultural reform across the European Union has focused debate on how agriculture delivers wider rural objectives. The authors undertook economic valuation and multicriteria studies to explore public preferences for rural policy. The results suggest simultaneous preferences for both environmental and social benefits, notably locally grown food, water quality, wildlife habitats, and maintaining rural communities. The public assigned greatest weight to locally grown food, which is closely linked to them as a direct use and is also routinely transacted for. The multicriteria study yielded a different preference ordering potentially arising from the differing elicitation methods indicating a possible drawback of the approach employed. © 2010 Regional Studies Association.