The Experts below are selected from a list of 553128 Experts worldwide ranked by ideXlab platform
Matthew Stephens - One of the best experts on this subject based on the ideXlab platform.
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efficient multivariate linear Mixed Model algorithms for genome wide association studies
Nature Methods, 2014Co-Authors: Xiang Zhou, Matthew StephensAbstract:Multivariate linear Mixed Models (mvLMMs) are powerful tools for testing associations between single-nucleotide polymorphisms and multiple correlated phenotypes while controlling for population stratification in genome-wide association studies. We present efficient algorithms in the genome-wide efficient Mixed Model association (GEMMA) software for fitting mvLMMs and computing likelihood ratio tests. These algorithms offer improved computation speed, power and P-value calibration over existing methods, and can deal with more than two phenotypes.
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genome wide efficient Mixed Model analysis for association studies
Nature Genetics, 2012Co-Authors: Xiang Zhou, Matthew StephensAbstract:Matthew Stephens and Xiang Zhou report an efficient exact method for accounting for population stratification and relatedness in genome-wide association analyses. Their method, genome-wide efficient Mixed-Model association (GEMMA) is implemented in freely available software. Linear Mixed Models have attracted considerable attention recently as a powerful and effective tool for accounting for population stratification and relatedness in genetic association tests. However, existing methods for exact computation of standard test statistics are computationally impractical for even moderate-sized genome-wide association studies. To address this issue, several approximate methods have been proposed. Here, we present an efficient exact method, which we refer to as genome-wide efficient Mixed-Model association (GEMMA), that makes approximations unnecessary in many contexts. This method is approximately n times faster than the widely used exact method known as efficient Mixed-Model association (EMMA), where n is the sample size, making exact genome-wide association analysis computationally practical for large numbers of individuals.
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genome wide efficient Mixed Model analysis for association studies
Nature Genetics, 2012Co-Authors: Xiang Zhou, Matthew StephensAbstract:Linear Mixed Models have attracted considerable attention recently as a powerful and effective tool for accounting for population stratification and relatedness in genetic association tests. However, existing methods for exact computation of standard test statistics are computationally impractical for even moderate-sized genome-wide association studies. To address this issue, several approximate methods have been proposed. Here, we present an efficient exact method, which we refer to as genome-wide efficient Mixed-Model association (GEMMA), that makes approximations unnecessary in many contexts. This method is approximately n times faster than the widely used exact method known as efficient Mixed-Model association (EMMA), where n is the sample size, making exact genome-wide association analysis computationally practical for large numbers of individuals.
Armin Scholl - One of the best experts on this subject based on the ideXlab platform.
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resequencing of Mixed Model assembly lines survey and research agenda
European Journal of Operational Research, 2012Co-Authors: Nils Boysen, Armin Scholl, Nico WoppererAbstract:Nowadays, Mixed-Model assembly lines are applied in a wide range of industries to mass-produce customized products to order, e.g., in automobile industry. An important decision problem in this context receiving a lot of attention from researchers and practitioners is the sequencing problem, which decides on the succession of workpieces launched down the line. However, if multiple departments with diverging sequencing objectives are to be passed or unforeseen disturbances like machine breakdowns or material shortages occur, a resequencing of a given production sequence often becomes equally essential. This paper reviews existing research on resequencing in a Mixed-Model assembly line context. Important problem settings, alternative buffer configurations, and resulting decision problems are described. Finally, future research needs are identified as some relevant real-world resequencing settings have not been dealt with in literature up to now.
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balancing Mixed Model assembly lines a computational evaluation of objectives to smoothen workload
International Journal of Production Research, 2010Co-Authors: Simon Emde, Nils Boysen, Armin SchollAbstract:Mixed-Model assembly lines are widely used in a range of production settings, such as the final assembly of the automotive and electronics industries, where they are applied to mass-produce standardised commodities. One of the greatest challenges when installing and reconfiguring these lines is the vast product variety modern Mixed-Model assembly lines have to cope with. Traditionally, product variety is bypassed during mid-term assembly line balancing by applying a joint precedence graph, which represents an (artificial) average Model and serves as the input data for a single Model assembly line balancing procedure. However, this procedure might lead to considerable variations in the station times, so that serious sequencing problems emerge and work overload threatens. To avoid these difficulties, different extensions of assembly line balancing for workload smoothing, i.e. horizontal balancing, have been introduced in the literature. This paper presents a multitude of known and yet unknown objectives for...
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the product rate variation problem and its relevance in real world Mixed Model assembly lines
European Journal of Operational Research, 2009Co-Authors: Nils Boysen, Malte Fliedner, Armin SchollAbstract:Production processes in a wide range of industries rely on modern Mixed-Model assembly systems, which allow an efficient manufacture of various Models of a common base product on the same assembly line. In order to facilitate a just-in-time supply of materials, the literature proposes various sequencing problems under the term "level scheduling", which all aim at evenly smoothing the part consumption induced by the production sequence over time. Among these approaches, the popular product rate variation (PRV) problem is considered to be an appropriate approximate Model, if either (i) all products require approximately the same number and mix of parts or (ii) part usages of all products are (almost completely) distinct. These statements are (iii) further specified by analytical findings, which prove the equivalence of product and material oriented level scheduling under certain conditions. These three prerequisites commonly cited in the literature when justifying the practical relevance of the PRV are evaluated by means of three simple computational experiments and are then discussed with regard to their relevance in practical settings. It is concluded that the PRV is in fact inappropriate for use in today's real world Mixed-Model assembly systems.
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production planning of Mixed Model assembly lines overview and extensions
Production Planning & Control, 2009Co-Authors: Nils Boysen, Malte Fliedner, Armin SchollAbstract:Mixed-Model assembly lines are of great practical relevance and are widely used in a range of industries, such as the final assembly of the automotive and electronics industries. Prior research mainly selected and discussed isolated problems rather than considering the whole planning process. In this article Mixed-Model production planning is decomposed into five steps: initial configuration of the line, master scheduling, reconfiguration planning, sequencing and resequencing. The paper reviews and discusses all relevant planning steps and proposes general planning instruments as well as formalized decision Models for those steps, which have not been thoroughly investigated in the literature thus far.
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Sequencing Mixed-Model assembly lines: Survey, classification and Model critique
European Journal of Operational Research, 2009Co-Authors: Nils Boysen, Malte Fliedner, Armin SchollAbstract:Manufacturers in a wide range of industries nowadays face the challenge of providing a rich product variety at a very low cost. This typically requires the implementation of cost efficient, flexible production systems. Often, so called Mixed-Model assembly lines are employed, where setup operations are reduced to such an extent that various Models of a common base product can be manufactured in interMixed sequences. However, the observed diversity of Mixed-Model lines makes a thorough sequence planning essential for exploiting the benefits of assembly line production. This paper reviews and discusses the three major planning approaches presented in the literature, Mixed-Model sequencing, car sequencing and level scheduling, and provides a hierarchical classification scheme to systematically record the academic efforts in each field and to deduce future research issues.
Xiang Zhou - One of the best experts on this subject based on the ideXlab platform.
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efficient multivariate linear Mixed Model algorithms for genome wide association studies
Nature Methods, 2014Co-Authors: Xiang Zhou, Matthew StephensAbstract:Multivariate linear Mixed Models (mvLMMs) are powerful tools for testing associations between single-nucleotide polymorphisms and multiple correlated phenotypes while controlling for population stratification in genome-wide association studies. We present efficient algorithms in the genome-wide efficient Mixed Model association (GEMMA) software for fitting mvLMMs and computing likelihood ratio tests. These algorithms offer improved computation speed, power and P-value calibration over existing methods, and can deal with more than two phenotypes.
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genome wide efficient Mixed Model analysis for association studies
Nature Genetics, 2012Co-Authors: Xiang Zhou, Matthew StephensAbstract:Matthew Stephens and Xiang Zhou report an efficient exact method for accounting for population stratification and relatedness in genome-wide association analyses. Their method, genome-wide efficient Mixed-Model association (GEMMA) is implemented in freely available software. Linear Mixed Models have attracted considerable attention recently as a powerful and effective tool for accounting for population stratification and relatedness in genetic association tests. However, existing methods for exact computation of standard test statistics are computationally impractical for even moderate-sized genome-wide association studies. To address this issue, several approximate methods have been proposed. Here, we present an efficient exact method, which we refer to as genome-wide efficient Mixed-Model association (GEMMA), that makes approximations unnecessary in many contexts. This method is approximately n times faster than the widely used exact method known as efficient Mixed-Model association (EMMA), where n is the sample size, making exact genome-wide association analysis computationally practical for large numbers of individuals.
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genome wide efficient Mixed Model analysis for association studies
Nature Genetics, 2012Co-Authors: Xiang Zhou, Matthew StephensAbstract:Linear Mixed Models have attracted considerable attention recently as a powerful and effective tool for accounting for population stratification and relatedness in genetic association tests. However, existing methods for exact computation of standard test statistics are computationally impractical for even moderate-sized genome-wide association studies. To address this issue, several approximate methods have been proposed. Here, we present an efficient exact method, which we refer to as genome-wide efficient Mixed-Model association (GEMMA), that makes approximations unnecessary in many contexts. This method is approximately n times faster than the widely used exact method known as efficient Mixed-Model association (EMMA), where n is the sample size, making exact genome-wide association analysis computationally practical for large numbers of individuals.
Nils Boysen - One of the best experts on this subject based on the ideXlab platform.
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resequencing of Mixed Model assembly lines survey and research agenda
European Journal of Operational Research, 2012Co-Authors: Nils Boysen, Armin Scholl, Nico WoppererAbstract:Nowadays, Mixed-Model assembly lines are applied in a wide range of industries to mass-produce customized products to order, e.g., in automobile industry. An important decision problem in this context receiving a lot of attention from researchers and practitioners is the sequencing problem, which decides on the succession of workpieces launched down the line. However, if multiple departments with diverging sequencing objectives are to be passed or unforeseen disturbances like machine breakdowns or material shortages occur, a resequencing of a given production sequence often becomes equally essential. This paper reviews existing research on resequencing in a Mixed-Model assembly line context. Important problem settings, alternative buffer configurations, and resulting decision problems are described. Finally, future research needs are identified as some relevant real-world resequencing settings have not been dealt with in literature up to now.
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balancing Mixed Model assembly lines a computational evaluation of objectives to smoothen workload
International Journal of Production Research, 2010Co-Authors: Simon Emde, Nils Boysen, Armin SchollAbstract:Mixed-Model assembly lines are widely used in a range of production settings, such as the final assembly of the automotive and electronics industries, where they are applied to mass-produce standardised commodities. One of the greatest challenges when installing and reconfiguring these lines is the vast product variety modern Mixed-Model assembly lines have to cope with. Traditionally, product variety is bypassed during mid-term assembly line balancing by applying a joint precedence graph, which represents an (artificial) average Model and serves as the input data for a single Model assembly line balancing procedure. However, this procedure might lead to considerable variations in the station times, so that serious sequencing problems emerge and work overload threatens. To avoid these difficulties, different extensions of assembly line balancing for workload smoothing, i.e. horizontal balancing, have been introduced in the literature. This paper presents a multitude of known and yet unknown objectives for...
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the product rate variation problem and its relevance in real world Mixed Model assembly lines
European Journal of Operational Research, 2009Co-Authors: Nils Boysen, Malte Fliedner, Armin SchollAbstract:Production processes in a wide range of industries rely on modern Mixed-Model assembly systems, which allow an efficient manufacture of various Models of a common base product on the same assembly line. In order to facilitate a just-in-time supply of materials, the literature proposes various sequencing problems under the term "level scheduling", which all aim at evenly smoothing the part consumption induced by the production sequence over time. Among these approaches, the popular product rate variation (PRV) problem is considered to be an appropriate approximate Model, if either (i) all products require approximately the same number and mix of parts or (ii) part usages of all products are (almost completely) distinct. These statements are (iii) further specified by analytical findings, which prove the equivalence of product and material oriented level scheduling under certain conditions. These three prerequisites commonly cited in the literature when justifying the practical relevance of the PRV are evaluated by means of three simple computational experiments and are then discussed with regard to their relevance in practical settings. It is concluded that the PRV is in fact inappropriate for use in today's real world Mixed-Model assembly systems.
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production planning of Mixed Model assembly lines overview and extensions
Production Planning & Control, 2009Co-Authors: Nils Boysen, Malte Fliedner, Armin SchollAbstract:Mixed-Model assembly lines are of great practical relevance and are widely used in a range of industries, such as the final assembly of the automotive and electronics industries. Prior research mainly selected and discussed isolated problems rather than considering the whole planning process. In this article Mixed-Model production planning is decomposed into five steps: initial configuration of the line, master scheduling, reconfiguration planning, sequencing and resequencing. The paper reviews and discusses all relevant planning steps and proposes general planning instruments as well as formalized decision Models for those steps, which have not been thoroughly investigated in the literature thus far.
-
Sequencing Mixed-Model assembly lines: Survey, classification and Model critique
European Journal of Operational Research, 2009Co-Authors: Nils Boysen, Malte Fliedner, Armin SchollAbstract:Manufacturers in a wide range of industries nowadays face the challenge of providing a rich product variety at a very low cost. This typically requires the implementation of cost efficient, flexible production systems. Often, so called Mixed-Model assembly lines are employed, where setup operations are reduced to such an extent that various Models of a common base product can be manufactured in interMixed sequences. However, the observed diversity of Mixed-Model lines makes a thorough sequence planning essential for exploiting the benefits of assembly line production. This paper reviews and discusses the three major planning approaches presented in the literature, Mixed-Model sequencing, car sequencing and level scheduling, and provides a hierarchical classification scheme to systematically record the academic efforts in each field and to deduce future research issues.
Magnus Nordborg - One of the best experts on this subject based on the ideXlab platform.
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a Mixed Model approach for genome wide association studies of correlated traits in structured populations
Nature Genetics, 2012Co-Authors: Arthur Korte, Vincent Segura, Bjarni J Vilhjalmsson, Alexander Platt, Quan Long, Magnus NordborgAbstract:Magnus Nordborg and colleagues report a parameterized multi-trait Mixed Model (MTMM) method applied to genome-wide association studies of correlated phenotypes. They test this approach, using both human and Arabidopsis thaliana data sets, and demonstrate how it can be used to identify pleiotropic loci and gene-by-environment interactions.
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a Mixed Model approach for genome wide association studies of correlated traits in structured populations
Nature Genetics, 2012Co-Authors: Arthur Korte, Vincent Segura, Bjarni J Vilhjalmsson, Alexander Platt, Quan Long, Magnus NordborgAbstract:Magnus Nordborg and colleagues report a parameterized multi-trait Mixed Model (MTMM) method applied to genome-wide association studies of correlated phenotypes. They test this approach, using both human and Arabidopsis thaliana data sets, and demonstrate how it can be used to identify pleiotropic loci and gene by environment interactions. Genome-wide association studies (GWAS) are a standard approach for studying the genetics of natural variation. A major concern in GWAS is the need to account for the complicated dependence structure of the data, both between loci as well as between individuals. Mixed Models have emerged as a general and flexible approach for correcting for population structure in GWAS. Here, we extend this linear Mixed-Model approach to carry out GWAS of correlated phenotypes, deriving a fully parameterized multi-trait Mixed Model (MTMM) that considers both the within-trait and between-trait variance components simultaneously for multiple traits. We apply this to data from a human cohort for correlated blood lipid traits from the Northern Finland Birth Cohort 1966 and show greatly increased power to detect pleiotropic loci that affect more than one blood lipid trait. We also apply this approach to an Arabidopsis thaliana data set for flowering measurements in two different locations, identifying loci whose effect depends on the environment.
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an efficient multi locus Mixed Model approach for genome wide association studies in structured populations
Nature Genetics, 2012Co-Authors: Vincent Segura, Bjarni J Vilhjalmsson, Alexander Platt, Arthur Korte, Umit Seren, Quan Long, Magnus NordborgAbstract:Magnus Nordborg and colleagues report a multi-locus Mixed-Model method (MLMM) for genome-wide association studies in structured populations. Their simulations show that MLMM offers increased power and a reduced false discovery rate, and applications to both human and Arabidopsis thaliana data sets identify new associations and allelic heterogeneity.
