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  • 151.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Lee, Youngjo
    Hierarchical generalized linear models have a great potential in genetics and animal breeding2010Conference paper (Refereed)
  • 152.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    McFarlane, S. Eryn
    Uppsala universitet.
    Husby, Arlid
    University of Helsinki; Norwegian University of Science and Technology.
    Kawakami, Takeshi
    Uppsala universitet.
    Ellegren, Hans
    Uppsala universitet.
    Qvarnström, Anna
    Uppsala universitet.
    Increasing the power of genome wide association studies in natural populations using repeated measures: evaluation and implementation2016In: Methods in Ecology and Evolution, ISSN 2041-210X, E-ISSN 2041-210X, Vol. 7, no 7, p. 792-799Article in journal (Refereed)
    Abstract [en]

    1. Genomewide association studies (GWAS) enable detailed dissections of the genetic basis for organisms' ability to adapt to a changing environment. In long-term studies of natural populations, individuals are often marked at one point in their life and then repeatedly recaptured. It is therefore essential that a method for GWAS includes the process of repeated sampling. In a GWAS, the effects of thousands of single-nucleotide polymorphisms (SNPs) need to be fitted and any model development is constrained by the computational requirements. A method is therefore required that can fit a highly hierarchical model and at the same time is computationally fast enough to be useful.

    2. Our method fits fixed SNP effects in a linear mixed model that can include both random polygenic effects and permanent environmental effects. In this way, the model can correct for population structure and model repeated measures. The covariance structure of the linear mixed model is first estimated and subsequently used in a generalized least squares setting to fit the SNP effects. The method was evaluated in a simulation study based on observed genotypes from a long-term study of collared flycatchers in Sweden.

    3. The method we present here was successful in estimating permanent environmental effects from simulated repeated measures data. Additionally, we found that especially for variable phenotypes having large variation between years, the repeated measurements model has a substantial increase in power compared to a model using average phenotypes as a response.

    4. The method is available in the R package RepeatABEL. It increases the power in GWAS having repeated measures, especially for long-term studies of natural populations, and the R implementation is expected to facilitate modelling of longitudinal data for studies of both animal and human populations.

  • 153.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Mishchenko, Kateryna
    Holmgren, Sverker
    Efficient implementation of the AI-REML iteration variance component QTL analysis.2007Report (Other academic)
  • 154.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Mishchenko, Kateryna
    Holmgren, Sverker
    Carlborg, Örjan
    Increasing the efficiency of variance component quantitative trait loci analysis by using reduced-rank identity-by-descent matrices.2007In: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 176, no July, p. 1935-1938Article in journal (Refereed)
  • 155.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Pong-Wong, Ricardo
    Carlborg, Örjan
    Defining the assumptions underlying modelling of epistatic QTL using variance component methods.2008In: Journal of Heredity, ISSN 0022-1503, E-ISSN 1465-7333, Vol. 99, no 4, p. 421-425Article in journal (Refereed)
  • 156.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Statistics.
    Vinterkonferens i rumslig statistik i Dalarna2011In: Qvintensen, ISSN 2000-1819, Vol. 2011, no 4Article in journal (Other academic)
  • 157.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Sand, Håkan
    Andren, Henrik
    Månsson, Johan
    Pehrson, Åke
    Evaluation of four methods used to estimate population density of moose (Alces alces)2008In: Wildlife Biology, ISSN 0909-6396, E-ISSN 1903-220X, Vol. 14, no 3, p. 358-371Article in journal (Refereed)
    Abstract [en]

    Various survey methods are used to monitor and manage ungulate popualations. The choice of optimal method depends on estimation accuracy, management objective and financial constraints. Here we compare estimates produced by four different methods for estimating population size, i.e. aerial counts, hunter observations, pellet group counts and cohort analysis. A Swedish moose Alces alces population was studied during 1973-2005 in the Grimso Wildlife Research Area (135 km(2)). The highest correlation was found between cohort analysis and aerial counts (r = 0.69. P < 0.05). and the hunter observations and the aerial counts (r = 0.76. P < 0.10). The different methods produced relatively consistent trends in population estimates over years. Pellet group counts prior to 1997 were not significantly correlated with the other methods. probably due to unrepresentative spatial sampling. A comparison of the aerial and pellet group counts in 2002 and 2006, showed that the average defecation rate was estimated at approximately 14 pellet groups per day per moose. Our results show the importance of having representative spatial sampling in pellet group surveys and indicate that hunter observations can be a useful tool for estimating long-term population trends even in moderately sized areas.

  • 158.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Shen, Xia
    Dalarna University, School of Technology and Business Studies, Statistics.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Hglm: A package for fitting hierarchical generalized linear models2010In: The R Journal, ISSN 2073-4859, E-ISSN 2073-4859, Vol. 2, no 2, p. 20-28Article in journal (Refereed)
    Abstract [en]

    We present the hglm package for fitting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.

  • 159.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Valdar, William
    Detecting major genetic loci controlling phenotypic variability in experimental crosses2011In: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 188, no 2, p. 435-447Article in journal (Refereed)
    Abstract [en]

    Traditional methods for detecting genes that affect complex diseases in humans or animal models, milk production in livestock, or other traits of interest, have asked whether variation in genotype produces a change in that trait’s average value. But focusing on differences in the mean ignores differences in variability about that mean. The robustness, or uniformity, of an individual’s character is not only of great practical importance in medical genetics and food production but is also of scienti?c and evolutionary interest (e.g., blood pressure in animal models of heart disease, litter size in pigs, ?owering time in plants). We describe a method for detecting major genes controlling the phenotypic variance, referring to these as vQTL. Our method uses a double generalized linear model with linear predictors based on probabilities of line origin. We evaluate our method on simulated F2 and collaborative cross data, and on a real F2 intercross, demonstrating its accuracy and robustness to the presence of ordinary mean-controlling QTL. We also illustrate the connection between vQTL and QTL involved in epistasis, explaining how these concepts overlap. Our method can be applied to a wide range of commonly used experimental crosses and may be extended to genetic association more generally.

  • 160.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Valdar, William
    Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability2012In: BMC Genetics, ISSN 1471-2156, E-ISSN 1471-2156, Vol. 13, article id 63Article in journal (Refereed)
    Abstract [en]

    A number of recent works have introduced statistical methods for detecting genetic loci that affect phenotypic variability, which we refer to as variability-controlling quantitative trait loci (vQTL). These are genetic variants whose allelic state predicts how much phenotype values will vary about their expected means. Such loci are of great potential interest in both human and non-human genetic studies, one reason being that a detected vQTL could represent a previously undetected interaction with other genes or environmental factors. The simultaneous publication of these new methods in different journals has in many cases precluded opportunity for comparison. We survey some of these methods, the respective trade-offs they imply, and the connections between them. The methods fall into three main groups: classical non-parametric, fully parametric, and semi-parametric two-stage approximations. Choosing between alternatives involves balancing the need for robustness, flexibility, and speed. For each method, we identify important assumptions and limitations, including those of practical importance, such as their scope for including covariates and random effects. We show in simulations that both parametric methods and their semi-parametric approximations can give elevated false positive rates when they ignore mean-variance relationships intrinsic to the data generation process. We conclude that choice of method depends on the trait distribution, the need to include non-genetic covariates, and the population size and structure, coupled with a critical evaluation of how these fit with the assumptions of the statistical model.

  • 161.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Woolliams, J.A
    Predicted rates of inbreeding with additive maternal effects.2003In: Genetical Research, ISSN 0016-6723, E-ISSN 1469-5073, no 82, p. 67-77Article in journal (Refereed)
  • 162.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Woolliams, J.A.
    Danell, Ö.
    Breeding schemes in reindeer husbandry2003In: Rangifer, ISSN 1890-6729, Vol. 23, no 2, p. 45-55Article in journal (Refereed)
  • 163.
    Saqlain, Murshid
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Brandt, Daniel
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Stochastic differential equations modelling of levodopa concentration in patients with Parkinson's disease2018Conference paper (Other academic)
    Abstract [en]

    The purpose of this study is to investigate a pharmacokinetic model of levodopa concentration in patients with Parkinson's disease by introducing stochasticity so that inter-individual variability may be separated into measurement and system noise. It also aims to investigate whether the stochastic differential equations (SDE) model provide better fits than its ordinary differential equations (ODE) counterpart, by using a real data set. Westin et al. developed a pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion described by four ODEs, the first three of which define the pharmacokinetic model. In this study, system noise variables are added to the aforementioned first three equations through a standard Wiener process, also known as Brownian motion. The R package PSM for mixed-effects models is used on data from previous studies for modelling levodopa concentration and parameter estimation. First, the diffusion scale parameter, σ, and bioavailability are estimated with the SDE model. Second, σ is fixed to integer values between 1 and 5, and bioavailability is estimated. Cross-validation is performed to determine whether the SDE based model explains the observed data better or not by comparingthe average root mean squared errors (RMSE) of predicted levodopa concentration. Both ODE and SDE models estimated bioavailability to be about 88%. The SDE model converged at different values of σ that were signicantly different from zero while estimating bioavailability to be about 88%. The average RMSE for the ODE model wasfound to be 0.2980, and the lowest average RMSE for the SDE model was 0.2748 when σ was xed to 4. Both models estimated similar values for bioavailability, and the non-zero σ estimate implies that the inter-individual variability may be separated. However, the improvement in the predictive performance of the SDE model turned out to be rather small, compared to the ODE model.

  • 164.
    Shen, Xia
    Dalarna University, School of Technology and Business Studies, Statistics.
    A Monte Carlo Full Likelihood Approach in Variance Component Quantitative Trait Loci Analysis2009In: 13th QTLMAS Workshop, Wageningen, The Netherlands, 2009Conference paper (Other academic)
    Abstract [en]

    The identity-by-descent (IBD) matrix is the core of the variance component QTL model. The true IBD matrix comes from a distribution of IBD matrices given the marker information, but its expectation is normally used in QTL analysis. This gives incorrect likelihood values since the extra uncertainty in estimating the IBD matrix is not included. Previous studies have concentrated on small pedigrees where the correct likelihood can be derived. For large pedigrees this approach is not feasible. We therefore developed a Monte Carlo method for calculating the likelihood in- corporating the uncertainty of the estimated IBD matrix. The aim of this study is to implement the Monte Carlo Full Likelihood (MCFL) algorithm and to compare the true likelihood with the like- lihood based on the expected IBD matrix for large pedigrees. Our simulation results show that the likelihood based on the expected IBD matrix approximates the true likelihood well and may there- fore justify the use of the expected IBD matrix in empirical QTL analysis. Our MCFL method can actually be computationally more efficient than the expectation method for large pedigrees with a small founder generation, because the rank of the true IBD matrix is much lower than the rank of the expected IBD matrix, especially when the genetic markers are highly informative. Using the IBD matrices produced in our MCFL method we may also simplify the modeling of epistasis for linked QTL.

  • 165.
    Shen, Xia
    Dalarna University, School of Technology and Business Studies, Statistics.
    Novel Statistical Methods in Quantitative Genetics: Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation2012Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models.

    In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision. 

    Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction.

    A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes. 

    The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

  • 166.
    Shen, Xia
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Fikse, Freddy
    Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    A novel generalized ridge regression method for quantitative genetics2013In: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 193, no 4, p. 1255-1268Article in journal (Refereed)
    Abstract [en]

    As the molecular marker density grows, there is a strong need in both genome-wide association studies and genomic selection to fit models with a large number of parameters. Here we present a computationally efficient generalized ridge regression (RR) algorithmfor situations where the number of parameters largely exceeds the number of observations. The computationally demanding parts of the method depend mainly on the number ofobservations and not the number of parameters. The algorithm was implemented in the R package bigRR based on the previously developed package hglm. Using such an approach, a heteroscedastic effects model (HEM) was also developed, implemented and tested. Theefficiency for different data sizes were evaluated via simulation. The method was tested for a bacteria-hypersensitive trait in a publicly available Arabidopsis dataset including 84 inbred lines and 216 130 SNPs. The computation of all the SNP effects required less than10 seconds using a single 2.7 GHz core. The advantage in run-time makes permutationtest feasible for such a whole-genome model, so that a genome-wide significance threshold can be obtained. HEM was found to be more robust than ordinary RR (a.k.a. SNPBLUP) in terms of QTL mapping, because SNP specific shrinkage was applied instead of acommon shrinkage. The proposed algorithm was also assessed for genomic evaluation and was shown to give better predictions than ordinary RR.

  • 167.
    Shen, Xia
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics. Swedish University of Agricultural Sciences.
    Carlborg, Örjan
    Swedish University of Agricultural Sciences.
    Beware of risk for increased false positive rates in genome-wide association studies for phenotypic variability2013In: Frontiers in Genetics, ISSN 1664-8021, E-ISSN 1664-8021, no 4Article in journal (Refereed)
  • 168. Shen, Xia
    et al.
    Li, Ying
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Uden, Peter
    Carlborg, Orjan
    Application of a genomic model for high-dimensional chemometric analysis2014In: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 28, no 7, p. 548-557Article in journal (Refereed)
    Abstract [en]

    The rapid development of newtechnologies for large-scale analysis of genetic variation in the genomes of individuals and populations has presented statistical geneticists with a grand challenge to develop efficient methods for identifying the small proportion of all identified genetic polymorphisms that have effects on traits of interest. To address such a "large p small n" problem, we have developed a heteroscedastic effects model (HEM) that has been shown to be powerful in high-throughput genetic analyses. Here, we describe how this whole-genome model can also be utilized in chemometric analysis. As a proof of concept, we use HEM to predict analyte concentrations in silage using Fourier transform infrared spectroscopy signals. The results show that HEM often outperforms the classic methods and in addition to this presents a substantial computational advantage in the analyses of such high-dimensional data. The results thus show the value of taking an interdisciplinary approach to chemometric analysis and indicate that large-scale genomic models can be a promising new approach for chemometric analysis that deserve to be evaluated more by experts in the field. The software used for our analyses is freely available as an R package at http://cran.r-project.org/web/packages/bigRR/. Copyright (C) 2014 JohnWiley & Sons, Ltd.

  • 169.
    Shen, Xia
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Pettersson, Mats
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carlborg, Örjan
    Inheritance beyond plain heritability: variance-controlling genes in Arabidopsis thaliana2012In: PLOS Genetics, ISSN 1553-7390, E-ISSN 1553-7404, Vol. 8, no 8, article id e1002839Article in journal (Refereed)
    Abstract [en]

    The phenotypic effect of a gene is normally described by the mean-difference between alternative genotypes. A gene may, however, also influence the phenotype by causing a difference in variance between genotypes. Here, we reanalyze a publicly available Arabidopsis thaliana dataset [1] and show that genetic variance heterogeneity appears to be as common as normal additive effects on a genomewide scale. The study also develops theory to estimate the contributions of variance differences between genotypes to the phenotypic variance, and this is used to show that individual loci can explain more than 20% of the phenotypic variance. Two well-studied systems, cellular control of molybdenum level by the ion-transporter MOT1 and flowering-time regulation by the FRI-FLC expression network, and a novel association for Leaf serration are used to illustrate the contribution of major individual loci, expression pathways, and gene-by-environment interactions to the genetic variance heterogeneity.

  • 170.
    Shen, Xia
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Estimation of Parameters in Random Effect Models with Incidence Matrix Uncertainty2010Conference paper (Other academic)
    Abstract [en]

    Random effect models have been widely applied in many fields of research. However, models with uncertain design matrices for random effects have been little investigated before. In some applications with such problems, an expectation method has been used for simplicity. This method does not include the extra information of uncertainty in the design matrix is not included. The closed solution for this problem is generally difficult to attain. We therefore propose an two-step algorithm for estimating the parameters, especially the variance components in the model. The implementation is based on Monte Carlo approximation and a Newton-Raphson-based EM algorithm. As an example, a simulated genetics dataset was analyzed. The results showed that the proportion of the total variance explained by the random effects was accurately estimated, which was highly underestimated by the expectation method. By introducing heuristic search and optimization methods, the algorithm can possibly be developed to infer the 'model-based' best design matrix and the corresponding best estimates.

  • 171.
    Shen, Xia
    et al.
    SLUDivision of Computational Genetics, Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics. Division of Quantitative Genetics, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala.
    Issues with data transformation in genome-wide association studies for phenotypic variability2013In: F1000Research, ISSN 2046-1402, Vol. 2, no 200Article in journal (Refereed)
    Abstract [en]

    The purpose of this correspondence is to discuss and clarify a few points about data transformation used in genome-wide association studies, especially for phenotypic variability. By commenting on the recent publication by Sun et al. in the American Journal of Human Genetics, we emphasize the importance of statistical power in detecting functional loci and the real meaning of the scale of the phenotype in practice.

  • 172.
    Shen, Xia
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carlborg, Örjan
    Hierarchical likelihood opens a new way of estimating genetic values using genome-wide dense marker maps2011In: BMC Proceedings, ISSN 1753-6561, E-ISSN 1753-6561, Proc. 14th European Workshop on QTL Mapping and Marker Assisted Selection (QTL-MAS), no 5(Suppl 3)Article in journal (Refereed)
    Abstract [en]

    Background Genome-wide dense markers have been used to detect genes and estimate relative genetic values. Among many methods, Bayesian techniques have been widely used and shown to be powerful in genome-wide breeding value estimation and association studies. However, computation is known to be intensive under the Bayesian framework, and specifying a prior distribution for each parameter is always required for Bayesian computation. We propose the use of hierarchical likelihood to solve such problems. Results Using double hierarchical generalized linear models, we analyzed the simulated dataset provided by the QTLMAS 2010 workshop. Marker-specific variances estimated by double hierarchical generalized linear models identified the QTL with large effects for both the quantitative and binary traits. The QTL positions were detected with very high accuracy. For young individuals without phenotypic records, the true and estimated breeding values had Pearson correlation of 0.60 for the quantitative trait and 0.72 for the binary trait, where the quantitative trait had a more complicated genetic architecture involving imprinting and epistatic QTL. Conclusions Hierarchical likelihood enables estimation of marker-specific variances under the likelihoodist framework. Double hierarchical generalized linear models are powerful in localizing major QTL and computationally fast.

  • 173.
    Shen, Xia
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carlborg, Örjan
    How to deal with genotype uncertainty in variance component quantitative trait loci analyses2011In: Genetics Research, ISSN 0016-6723, Vol. 93, no 5, p. 333-342Article in journal (Refereed)
    Abstract [en]

    Dealing with genotype uncertainty is an ongoing issue in genetic analyses of complex traits. Here we consider genotype uncertainty in quantitative trait loci (QTL) analyses for large crosses in variance component models, where the genetic information is included in identity-by-descent (IBD) matrices. An IBD matrix is one realization from a distribution of potential IBD matrices given available marker information. In QTL analyses, its expectation is normally used resulting in potentially reduced accuracy and loss of power. Previously, IBD distributions have been included in models for small human full-sib families. We develop an Expectation–Maximization (EM) algorithm for estimating a full model based on Monte Carlo imputation for applications in large animal pedigrees. Our simulations show that the bias of variance component estimates using traditional expected IBD matrix can be adjusted by accounting for the distribution and that the calculations are computationally feasible for large pedigrees.

  • 174. Shukur, Ghazi
    et al.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Framtida utmaningar för forskarutbildningen i statistik2013In: Qvintensen, ISSN 2000-1819, no 4, p. 21-21Article in journal (Other (popular science, discussion, etc.))
  • 175. Silva, C. N. S
    et al.
    McFarlane, S. E
    Hagen, I. J
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics. Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala.
    Billing, A. M
    Kvalnes, T
    Kemppainen, P
    Rønning, B
    Ringsby, T. H
    Husby, A
    Insights into the genetic architecture of morphological traits in two passerine bird species2017In: Heredity, ISSN 0018-067X, E-ISSN 1365-2540, Vol. 119, no 3, p. 197-205Article in journal (Refereed)
    Abstract [en]

    Knowledge about the underlying genetic architecture of phenotypic traits is needed to understand and predict evolutionary dynamics. The number of causal loci, magnitude of the effects and location in the genome are, however, still largely unknown. Here, we use genome-wide single-nucleotide polymorphism (SNP) data from two large-scale data sets on house sparrows and collared flycatchers to examine the genetic architecture of different morphological traits (tarsus length, wing length, body mass, bill depth, bill length, total and visible badge size and white wing patches). Genomic heritabilities were estimated using relatedness calculated from SNPs. The proportion of variance captured by the SNPs (SNP-based heritability) was lower in house sparrows compared with collared flycatchers, as expected given marker density (6348 SNPs in house sparrows versus 38 689 SNPs in collared flycatchers). Indeed, after downsampling to similar SNP density and sample size, this estimate was no longer markedly different between species. Chromosome-partitioning analyses demonstrated that the proportion of variance explained by each chromosome was significantly positively related to the chromosome size for some traits and, generally, that larger chromosomes tended to explain proportionally more variation than smaller chromosomes. Finally, we found two genome-wide significant associations with very small-effect sizes. One SNP on chromosome 20 was associated with bill length in house sparrows and explained 1.2% of phenotypic variation (VP), and one SNP on chromosome 4 was associated with tarsus length in collared flycatchers (3% of VP). Although we cannot exclude the possibility of undetected large-effect loci, our results indicate a polygenic basis for morphological traits.

  • 176. Sivertsen, Therese R.
    et al.
    Åhman, Birgitta
    Steyaert, Sam M. J. G.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Frank, Jens
    Segerström, Peter
    Støen, Ole-Gunnar
    Skarin, Anna
    Reindeer habitat selection under the risk of brown bear predation during calving season2016In: Ecosphere, ISSN 2150-8925, E-ISSN 2150-8925, Vol. 7, no 11, article id e01583Article in journal (Refereed)
    Abstract [en]

    The depredation of semi-domesticated reindeer by large carnivores reflects an important human-wildlife conflict in Fennoscandia. Recent studies have revealed that brown bears (Ursus arctos) may kill substantial numbers of reindeer calves (Rangifer tarandus tarandus) in forest areas in Sweden. Several authors have suggested that predation risk is an important driver of habitat selection in wild Rangifer populations where predation is a limiting factor, but little is known about these mechanisms in semi-domesticated populations. We examined the habitat selection of female reindeer in relation to spatial and temporal variations in brown bear predation risk on the reindeer calving grounds and evaluated the simultaneous responses of brown bears and reindeer to landscape characteristics. We used GPS data from 110 reindeer years (97 individuals) and 29 brown bear years (19 individuals), from two reindeer herding districts in the forest area of northern Sweden. Our results did not indicate that reindeer alter their behavior in response to spatiotemporal variation in brown bear predation risk, on the scale of the calving range. Instead, we suggest that spatiotemporal behavioral adjustments by brown bears were the main driver of prey-predator interactions in our study system. Contrasting responses by brown bears and reindeer to clear-cuts and young forest indicate that forestry can influence species interactions and possibly yield negative consequences for the reindeer herd. Even if clear-cuts may be beneficial in terms of calf survival, logging activity will eventually cause greater abundance of young regenerating forest, reducing available reindeer habitats and increasing habitat preferred by brown bears. Domestication may have made semi-domesticated reindeer in Fennoscandia less adapted to cope with predators. Areal restrictions, limiting the opportunity for dispersion and escape, possibly make the calves more susceptible to predation. Also, a generally higher population density in semi-domesticated herds compared to wild populations can make dispersion a less efficient strategy and the reindeer calves easier prey. Overall, the lack of ability of the reindeer females to reduce brown bear encounter risk on the scale of the calving range is probably an important reason for the high brown bear predation rates on reindeer calves documented in our study areas. 

  • 177. Skarin, A.
    et al.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Reindeer habitat use in relation to two small wind farms, during preconstruction, construction, and operation2017In: Ecology and Evolution, ISSN 2045-7758, E-ISSN 2045-7758, Vol. 7, no 11, p. 3870-3882Article in journal (Refereed)
    Abstract [en]

    Worldwide there is a rush toward wind power development and its associated infrastructure. In Fennoscandia, large-scale wind farms comprising several hundred windmills are currently built in important grazing ranges used for Sámi reindeer husbandry. In this study, reindeer habitat use was assessed using reindeer fecal pellet group counts in relation to two relatively small wind farms, with 8 and 10 turbines, respectively. In 2009, 1,315 15-m2 plots were established and pellet groups were counted and cleaned from the plots. This was repeated once a year in May, during preconstruction, construction, and operation of the wind farms, covering 6 years (2009-2014) of reindeer habitat use in the area. We modeled the presence/absence of any pellets in a plot at both the local (wind farm site) and regional (reindeer calving to autumn range) scale with a hierarchical logistic regression, where spatial correlation was accounted for via random effects, using vegetation type, and the interaction between distance to wind turbine and time period as predictor variables. Our results revealed an absolute reduction in pellet groups by 66% and 86% around each wind farm, respectively, at local scale and by 61% at regional scale during the operation phase compared to the preconstruction phase. At the regional, scale habitat use declined close to the turbines in the same comparison. However, at the local scale, we observed increased habitat use close to the wind turbines at one of the wind farms during the operation phase. This may be explained by continued use of an important migration route close to the wind farm. The reduced use at the regional scale nevertheless suggests that there may be an overall avoidance of both wind farms during operation, but further studies of reindeer movement and behavior are needed to gain a better understanding of the mechanisms behind this suggested avoidance.

  • 178. Skarin, Anna
    et al.
    Helleman, Christian
    Sandström, Per
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Lundquist, Henrik
    Renar och vindkraft: Studie från anläggningen av två vindkraftparker i Malå sameby2013Report (Other academic)
    Abstract [sv]

    Studien undersöker hur renar påverkas under konstruktionsfasen när vindkraftverk byggs. Studien följer uppförandet av två nya vindparker i Malå kommun i Västerbotten. Sammanlagt byggdes 18 vindkraftverk i Malå samebys kalvnings- och försommarland. Inventering av renspillning samt positioner från renar med GPS-halsband visar att konstruktionen av vindkraftsparkerna har påverkat renarnas användning av området. Analysen visar att renarna under tiden för byggnationen har sökt sig bort från området. Spillningsinventeringen och GPS-data visar också att renarna undviker kraftledningar och större vägar när de ska beta.

    Rapport från kunskapsprogrammet Vindval.

  • 179.
    Skarin, Anna
    et al.
    Swedish Univ Agr Sci, Dept Anim Nutr & Management, Uppsala.
    Nellemann, Christian
    GRID Arendal, United Nations Environm Programme, Lillehammer, Norway..
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Sandstrom, Per
    Swedish Univ Agr Sci, Dept Forest Resource Management, Umea, Sweden.
    Lundqvist, Henrik
    Swedish Univ Agr Sci, Dept Anim Nutr & Management, Uppsala, Sweden.
    Wind farm construction impacts reindeer migration and movement corridors2015In: Landscape Ecology, ISSN 0921-2973, E-ISSN 1572-9761, Vol. 30, no 8, p. 1527-1540Article in journal (Refereed)
    Abstract [en]

    Over the last decade, we have seen a massive increase in the construction of wind farms in northern Fennoscandia. Wind farms comprising hundreds of wind turbines are being built, with little knowledge of the possible cumulative adverse effects on the habitat use and migration of semi-domesticated free-ranging reindeer. We assessed how reindeer responded to wind farm construction in an already fragmented landscape, with specific reference to the effects on use of movement corridors and reindeer habitat selection. We used GPS-data from reindeer during calving and post-calving in the MalAyen reindeer herding community in Sweden. We analysed data from the pre-development years compared to the construction years of two relatively small wind farms. During construction of the wind farms, use of original migration routes and movement corridors within 2 km of development declined by 76 %. This decline in use corresponded to an increase in activity of the reindeer measured by increased step lengths within 0-5 km. The step length was highest nearest the development and declining with distance, as animals moved towards migration corridors and turned around or were observed in holding patterns while not crossing. During construction, reindeer avoided the wind farms at both regional and landscape scale of selection. The combined construction activities associated with even a few wind turbines combined with power lines and roads in or close to central movement corridors caused a reduction in the use of such corridors and grazing habitat and increased the fragmentation of the reindeer calving ranges.

  • 180.
    Skarin, Anna
    et al.
    SLU.
    Sandström, Per
    SLU.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Out of sight of wind turbines — Reindeer response to wind farms in operation2018In: Ecology and Evolution, ISSN 2045-7758, E-ISSN 2045-7758, Vol. 8, p. 9906-9919Article in journal (Refereed)
    Abstract [en]

    To meet the expanding land use required for wind energy development, a better understanding of the effects on terrestrial animals’ responses to such development is required. Using GPS-data from 50 freely ranging female reindeer (Rangifer tarandus) in the Malå reindeer herding community, Sweden, we determined reindeer calving sites and estimated reindeer habitat selection using resource selection functions (RSF). RSFs were estimated at both second- (selection of home range) and third-order (selection within home range) scale in relation to environmental variables, wind farm (WF) development phase (before construction, construction, and operation), distance to the WFs and at the second-order scale whether the wind turbines were in or out of sight of the reindeer. We found that the distance between reindeer calving site and WFs increased during the operation phase, compared to before construction. At both scales of selection, we found a significant decrease in habitat selection of areas in proximity of the WFs, in the same comparison. The results also revealed a shift in home range selection away from habitats where wind turbines became visible toward habitats where the wind turbines were obscured by topography (increase in use by 79% at 5 km). We interpret the reindeer shift in home range selection as an effect of the wind turbines per se. Using topography and land cover information together with the positions of wind turbines could therefore help identify sensitive habitats for reindeer and improve the planning and placement of WFs. In addition, we found that operation phase of these WFs had a stronger adverse impact on reindeer habitat selection than the construction phase. Thus, the continuous running of the wind turbines making a sound both day and night seemed to have disturbed the reindeer more than the sudden sounds and increased human activity during construction work.

  • 181.
    Skarin, Anna
    et al.
    Sveriges lantbruksuniversitet.
    Sandström, Per
    Sveriges lantbruksuniversitet.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Buhot, Yann
    Sveriges lantbruksuniversitet.
    Nellemann, Christian
    Rhipto-Norwegian Center for Global Analyses.
    Renar och vindkraft II: Vindkraft i drift och effekter på renar och renskötsel2016Report (Other academic)
    Abstract [en]

    A surge in wind power development and associated road and powerline infrastructure is currently taking place worldwide. In Sweden and Fennoscandia, plans of large-scale wind power mill farms counting several hunderd windmills and their associated infrastructure of roads and powerlines are being implemented. In this report we describe how wind farms not only during construction, but also during operational phases impact reindeer and reindeer husbandry.

    Reindeer behaviour in relation to wind farms were studied in three different study areas in Västerbotten County in northern Sweden. In the Malå reindeer herding community the effects of Storliden and Jokkmokkliden wind farms were assessed during the calving and summer grazing period. In Vilhelmina Norra reindeer herding community, use of the winter grazing range around Stor-Rotliden wind farm was studied.

    Finally, the use of the Lögdeålandets winter grazing range by reindeer from the Byrkije reindeer herding community from Norway was assessed in relation to the Gabrielbergets wind farm. Reindeer habitat use was assessed through reindeer fecal pellet-group counts and by the use of GPS-collars. Data were before and during the construction phase and during the operational phase. We estimated reindeer habitat selection by developing resource selection function (RSF) models for each area in relation to the wind farm areas before, during and after construction. In addition, reindeer use was assessed around Gabrielsberget when 1) the wind farm was turned off for 40 days; 2) during operation when the reindeer were supplementary fed, and 3) during operation without supplementary feeding. Finally, the perception, experiences and views of reindeer herders were assessed through qualitative interviews.

    Our results showed that the reindeer in both calving and winter grazing areas were negatively affected by the wind farm developments. The reindeer avoided grazing in areas where they could see and/or hear the wind turbines and preferred to use areas where the wind turbines were topographically sheltered. In Malå, the reindeer increased the use by 60% of areas topographically sheltered away from the operating wind farms compared to before construction. In winter at Gabrielsberget wind farm, with no supplementary feeding, reindeer largely avoided a 3 km zone.

    When the reindeer were fed inside the wind farm and intensively perimeter herded to stay close to the wind farm, the reindeer still increased their use of areas locally where the wind turbines were sheltered by the topography with 13 %, compared to when they were not fed nor intensively herded. In the calving area in Malå, the use decreased with 16-20 % within 5 km from the wind farm. Moreover, the reindeer significantly increased their movement rate by 18 % within 4 km from the wind farm area during operation phase, compared to before the wind farms were developed.

    Reindeer actively avoid or reduce use of areas within 3 km from wind power farms both during construction and operational phases. Reindeer are more active or vigilant when close to wind power farms. Finally, reindeer tend to – but at more modest extent – to select more sheltered areas close to windmills if forced through supplementary feeding and herding.

    During winter, wind farms situated in upland terrain may reduce the availability and access to reindeer of important higher-altitude winter grazing areas. This may have particular adverse effects and reduce the resilience of reindeer husbandry against extreme weather such as icing by restraining range accessibility. As extreme weather events are expected to be more frequent with climate change, also the ability of reindeer husbandry to adapt becomes reduced with continuing piecemeal infrastructure development.

    The results from our projects have shown that wind farm developments have considerable impacts on reindeer and reindeer husbandry both during the calving season and during the winter season. The impacts for reindeer husbandry may be expected to be most severe in the winter grazing areas, where it often is difficult to find alternative grazing areas. A direct effect of a wind farm in the middle of the winter grazing area, such as Gabrielsberget wind farm, may be that the reindeer need to be supplementary fed and intensively herded to keep the reindeer in the area, subsequently increasing the work load on the reindeer herders. It also reduces the ability of herders to mitigate extreme weather by moving reindeer to dwindling alternative grazing sites.

    Other infrastructure, such as roads and power lines, also affect the reindeer habitat selection. Prior to wind farm development, reindeer avoided areas in the vicinity of larger (>5 m wide) roads. After the wind farm was developed, the reindeer at Stor-Rotliden stopped avoiding the large roads and instead increased the habitat use closer to the large roads in the only alternative foraging areas. At Gabrielsberget, the reindeer also used areas close to the large roads, including the highway E4, when the reindeer were freely ranging in order to avoid the wind farm. This obviously increases the risk of traffic accidents and herders are subsequently required to intensify herding.

    Mitigation measures for herders and developers in areas where wind farms are already established are presented. Especially, established associated road infrastructure to the windmills should be closed for public use to avoid recreational activities, whether by ATVs or snowmobiles, or by hunters. Furthermore, a close contact should be maintained between the power company and the reindeer herding community to prevent road or mill maintenance work during sensitive periods for the reindeer. Other more regional measures to facilitate reindeer movement and migration between different grazing ranges may be to establish fences along major roads and railways (eg. E4 or the main railroad through Sweden) combined with strategically placed ecoducts.

  • 182. Sonesson, Anna K
    et al.
    Odegård, Jørgen
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar)2013In: Genetics Selection Evolution, ISSN 0999-193X, E-ISSN 1297-9686, Vol. 45, article id 41Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects.

    RESULTS: Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects.

    CONCLUSIONS: Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro-environmental changes (diet, climatic region, etc.) may make genetic heterogeneity of variance a less stable trait over time and space.

  • 183.
    Strandberg, E
    et al.
    SLU.
    Felleki, Majbritt
    Dalarna University, School of Technology and Business Studies, Statistics.
    Fikse, W F
    SLU.
    Franzén, J
    Stockholms Universitet.
    Mulder, H A
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Urioste, J I
    Windig, J J
    Statistical tools to select for robustness and milk quality2013In: Advances in Animal Biosciences, ISSN 2040-4719, Vol. 4, no 3, p. 606-611Article in journal (Refereed)
    Abstract [en]

    This work was part of the EU RobustMilk project. In this work package, we have focused on two aspects of robustness, micro- and macro-environmental sensitivity and applied these to somatic cell count (SCC), one aspect of milk quality. We showed that it is possible to combine both categorical and continuous descriptions of the environment in one analysis of genotype by environment interaction. We also developed a method to estimate genetic variation in residual variance and applied it to both simulated and a large field data set of dairy cattle. We showed that it is possible to estimate genetic variation in both micro- and macro-environmental sensitivity in the same data, but that there is a need for good data structure. In a dairy cattle example, this would mean at least 100 bulls with at least 100 daughters each. We also developed methods for improved genetic evaluation of SCC. We estimated genetic variance for some alternative SCC traits, both in an experimental herd data and in field data. Most of them were highly correlated with subclinical mastitis (>0.9) and clinical mastitis (0.7 to 0.8), and were also highly correlated with each other. We studied whether the fact that animals in different herds are differentially exposed to mastitis pathogens could be a reason for the low heritabilities for mastitis, but did not find strong evidence for that. We also created a new model to estimate breeding values not only for the probability of getting mastitis but also for recovering from it. In a progeny-testing situation, this approach resulted in accuracies of 0.75 and 0.4 for these two traits, respectively, which means that it is possible to also select for cows that recover more quickly if they get mastitis.

  • 184.
    Svenson, Kristin
    Dalarna University, School of Technology and Business Studies, Statistics.
    Estimated lifetimes of road pavements in Sweden using time-to-event analysis2013Report (Other academic)
    Abstract [en]

    Maintenance planning of road pavement requires reliable estimates of roads’ lifetimes. In determining the lifetime of a road, this study combines maintenance activities and road condition measurements. The scope of the paper is to estimate lifetimes of road pavements in Sweden with time to event analysis. The model used includes effects of pavement type, road type, bearing capacity, road width, speed limit, stone size and climate zone, where the model is stratified according to traffic load. Among the nine analyzed pavement types, stone mastic had the longest expected lifetime, 32 percent longer than asphalt concrete. Among road types, ordinary roads with cable barriers had 30 percent shorter lifetime than ordinary roads. Increased speed lowered the lifetime, while increased stone size (up to 20 mm) and increased road width lengthened the lifetime. The results are of importance for life cycle cost analysis and road management.

  • 185.
    Svenson, Kristin
    Dalarna University, School of Technology and Business Studies, Statistics.
    Estimated lifetimes of road pavements in Sweden using time-to-event analysis2014In: Journal of transportation engineering, ISSN 0733-947X, E-ISSN 1943-5436, Vol. 140, no 11, article id 04014056Article in journal (Refereed)
    Abstract [en]

    Maintenance planning of road pavement requires reliable estimates of roads' lifetimes. In determining the lifetime of a road, this study combines maintenance activities and road condition measurements. The scope of the paper is to estimate lifetimes of road pavements in Sweden with time-to-event analysis. The model is stratified according to traffic load and includes effects of pavement type, road type, bearing capacity, road width, speed limit, stone size, and climate zone. Among the nine analyzed pavement types, stone mastic had the longest expected lifetime with a hazard ratio (risk of needing maintenance) estimated to be 36% lower than asphalt concrete. Among road types, 2+1 roads had 22% higher hazard ratio than ordinary roads indicating significantly lower lifetimes. Increased speed lowered the lifetime, while increased stone size (up to 20 mm) and increased road width lengthened the lifetime. The results are of importance for life-cycle cost analysis and road management. (C) 2014 American Society of Civil Engineers.

  • 186.
    Svenson, Kristin
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Li, Yujiao
    Dalarna University, School of Technology and Business Studies, Statistics.
    Macuchova, Zuzana
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Evaluating needs of road maintenance in Sweden with the mixed proportional hazards model2016In: Transportation Research Record, ISSN 0361-1981, E-ISSN 2169-4052, no 2589, p. 51-58Article in journal (Refereed)
    Abstract [en]

    National road databases often lack important information for long-term maintenance planning of paved roads. In the Swedish case, latent variables of which there are no recordings in the pavement management systems database are, for example, underlying road construction, subsoil conditions, and amount of heavy traffic measured by the equivalent single-axle load. The mixed proportional hazards model with random effects was used to capture the effect of these latent variables on a road's risk of needing maintenance. Estimation of random effects makes it possible to identify sections that have shorter or longer lifetimes than could be expected from the observed explanatory variables (traffic load, pavement type, road type, climate zone, road width, speed limit, and bearing capacity restrictions). The results indicate that the mixed proportional hazards model is useful for maintenance planning because the weakest and strongest sections in a road network can be identified. The effect of the latent variables was visualized by,plotting the random effect of each section in a map of the road network. In addition, the spatial correlation between road sections was evaluated by fitting the random effects in an intrinsic conditional autoregressive model. The spatial correlation was estimated to explain 17% of the variation in lifetimes of roads that occur because of the latent variables. The Swedish example shows that the mixed proportional hazards and intrinsic conditional autoregressive models are suitable for analyzing the effect of latent variables in national road databases.

  • 187.
    Svenson, Kristin
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    McRobbie, S.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Detecting road pavement deterioration with finite mixture models2019In: The international journal of pavement engineering, ISSN 1029-8436, E-ISSN 1477-268X, Vol. 20, no 4, p. 458-465Article in journal (Refereed)
    Abstract [en]

    Budget restrictions often limit the number of possible maintenance activities in a road network each year. To effectively allocate resources, the rate of road pavement deterioration is of great importance. If two maintenance candidates have an equivalent condition, it is reasonable to maintain the segment with the highest deterioration rate first. To identify such segments, finite mixture models were applied to road condition data from a part of the M4 highway in England. Assuming that data originates from two different normal distributions – defined as a ‘change’ distribution and an ‘unchanged’ distribution – all road segments were classified into one of the groups. Comparisons with known measurement errors and maintenance records showed that segments in the unchanged group had a stationary road condition. Segments classified into the change group showed either a rapid deterioration, improvement in condition because of previous maintenance or unusual measurement errors. Together with additional information from maintenance records, finite mixture models can identify segments with the most rapid deterioration rate, and contribute to more efficient maintenance decisions.

  • 188.
    Thomas, Fridtjof
    Dalarna University, School of Technology and Business Studies, Statistics.
    Assessing Heavy-Vehicle Accident Rates for Marginal Cost Calculations: Outline of a Full Probability Modelling Approach2003Report (Other academic)
  • 189.
    Thomas, Fridtjof
    Dalarna University, School of Technology and Business Studies, Statistics.
    Marginal Costs for Wear and Tear Attributable to Heavy Vehicles Inherent in ’Effektsamband 2000’2003Report (Other academic)
  • 190.
    Thomas, Fridtjof
    Dalarna University, School of Technology and Business Studies, Statistics.
    Statistical Approach to Road Segmentation2003In: Journal of transportation engineering, ISSN 0733-947X, E-ISSN 1943-5436, Vol. 129, no 3, p. 300-308Article in journal (Refereed)
  • 191.
    Thomas, Fridtjof
    Dalarna University, School of Technology and Business Studies, Statistics.
    Swedish Road Account – Mälardalen: 1998-20022004Report (Other academic)
  • 192.
    Thomas, Fridtjof
    Dalarna University, School of Technology and Business Studies, Statistics.
    Tillståndsstyrd Sträckindelning: Beskrivning av Tillgängliga Metoder2003Report (Other academic)
  • 193.
    Thomas, Fridtjof
    Dalarna University, School of Technology and Business Studies, Statistics.
    Vägkostnadsdata – Mälardalen: 1998-20022004Report (Other academic)
  • 194.
    Thomas, Fridtjof
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Weninger-Vycudil, A.
    Simanek, P.
    Automated Segmentation of Pavement Measurements Based on Bayesian Ideas: Experiences from Austria2004In: Proceedings 6th International Conference on Managing Pavements, Brisbane, Queensland, Australia, 2004Conference paper (Refereed)
  • 195.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Bergquist, Filip
    Johansson, Dongni
    Memedi, Mevludin
    Nyholm, Dag
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Sensor-based algorithmic dosing suggestions for oral administration of levodopa/carbidopa microtablets for Parkinson's disease: a first experience2019In: Journal of Neurology, ISSN 0340-5354, E-ISSN 1432-1459, Vol. 266, no 3, p. 651-658Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: Dosing schedules for oral levodopa in advanced stages of Parkinson's disease (PD) require careful tailoring to fit the needs of each patient. This study proposes a dosing algorithm for oral administration of levodopa and evaluates its integration into a sensor-based dosing system (SBDS).

    MATERIALS AND METHODS: In collaboration with two movement disorder experts a knowledge-driven, simulation based algorithm was designed and integrated into a SBDS. The SBDS uses data from wearable sensors to fit individual patient models, which are then used as input to the dosing algorithm. To access the feasibility of using the SBDS in clinical practice its performance was evaluated during a clinical experiment where dosing optimization of oral levodopa was explored. The supervising neurologist made dosing adjustments based on data from the Parkinson's KinetiGraph™ (PKG) that the patients wore for a week in a free living setting. The dosing suggestions of the SBDS were compared with the PKG-guided adjustments.

    RESULTS: The SBDS maintenance and morning dosing suggestions had a Pearson's correlation of 0.80 and 0.95 (with mean relative errors of 21% and 12.5%), to the PKG-guided dosing adjustments. Paired t test indicated no statistical differences between the algorithmic suggestions and the clinician's adjustments.

    CONCLUSION: This study shows that it is possible to use algorithmic sensor-based dosing adjustments to optimize treatment with oral medication for PD patients.

  • 196.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Bergquist, Filip
    Senek, Marina
    Nyholm, Dag
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Individual levodopa dosing suggestions based on a single dose test2016Conference paper (Other academic)
  • 197.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nyholm, Dag
    Senek, Marina
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Individual dose-response models for levodopa infusion dose optimization2018In: International Journal of Medical Informatics, ISSN 1386-5056, E-ISSN 1872-8243, Vol. 112, p. 137-142Article in journal (Refereed)
    Abstract [en]

    Background and Objective

    To achieve optimal effect with continuous infusion treatment in Parkinson’s disease (PD), the individual doses (morning dose and continuous infusion rate) are titrated by trained medical personnel. This study describes an algorithmic method to derive optimized dosing suggestions for infusion treatment of PD, by fitting individual dose-response models. The feasibility of the proposed method was investigated using patient chart data.

    Methods

    Patient records were collected at Uppsala University hospital which provided dosing information and dose-response evaluations. Mathematical optimization was used to fit individual patient models using the records’ information, by minimizing an objective function. The individual models were passed to a dose optimization algorithm, which derived an optimized dosing suggestion for each patient model.

    Results

    Using data from a single day’s admission the algorithm showed great ability to fit appropriate individual patient models and derive optimized doses. The infusion rate dosing suggestions had 0.88 correlation and 10% absolute mean relative error compared to the optimal doses as determined by the hospital’s treating team. The morning dose suggestions were consistency lower that the optimal morning doses, which could be attributed to different dosing strategies and/or lack of on-off evaluations in the morning.

    Conclusion

    The proposed method showed promise and could be applied in clinical practice, to provide the hospital personnel with additional information when making dose adjustment decisions.

  • 198.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Senek, Marina
    Uppsala University Hospital.
    Dag, Nyholm
    Uppsala University Hospital.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Minimizing levodopa titration period for Parkinson’s disease2016Conference paper (Other academic)
  • 199.
    Thomas, Ilias
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Bergquist, F.
    Nyholm, D.
    Senek, M.
    Memedi, Mevludin
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    A treatment–response index from wearable sensors for quantifying Parkinson's disease motor states2018In: IEEE journal of biomedical and health informatics, ISSN 2168-2194, E-ISSN 2168-2208, Vol. 22, no 5, p. 1341-1349Article in journal (Refereed)
    Abstract [en]

    The goal of this study was to develop an algorithm that automatically quantifies motor states (off,on,dyskinesia) in Parkinson's disease (PD), based on accelerometry during a hand pronation-supination test. Clinician's ratings using the Treatment Response Scale (TRS), ranging from -3 (very Off) to 0 (On) to +3 (very dyskinetic), was used as target. For that purpose, 19 participants with advanced PD and 22 healthy persons were recruited in a single center open label clinical trial in Uppsala, Sweden. The trial consisted of single levodopa dose experiments for the people with PD (PwP), where participants were asked to perform standardized wrist rotation tests, using each hand, before and at pre-specified time points after the dose. The participants used wrist sensors containing a 3D accelerometer and gyroscope. Features to quantify the level, variation and asymmetry of the sensor signals, three-level Discrete Wavelet Transform features and approximate entropy measures were extracted from the sensors data. At the time of the tests, the PwP were video recorded. Three movement disorder specialists rated the participants’ state on the TRS scale. A Treatment Response Index from Sensors (TRIS) was constructed to quantify the motor states based on the wrist rotation tests. Different machine learning algorithms were evaluated to map the features derived from the sensor data to the ratings provided by the three specialists. Results from cross validation, both in 10-fold and a leave-one-individual out setting, showed good predictive power of a support vector machine model and high correlation to the TRS scale. Values at the end tails of the TRS scale were under and over predicted due to the lack of observations at those values but the model managed to accurately capture the dose - effect profiles of the patients. In addition, the TRIS had good test-retest reliability on the baseline levels of the PD participants (Intraclass correlation coefficient of 0.83) and reasonable sensitivity to levodopa treatment (0.33 for the TRIS). For a series of test occasions the proposed algorithms provided dose - effect time profiles for participants with PD, which could be useful during therapy individualization of people suffering from advanced PD

  • 200.
    Wang, Yu
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    High school student's summer jobs and their ensuing labour market achievement2006Report (Other academic)
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