Relevant bibliographies by topics / Statistical genetics

Academic literature on the topic 'Statistical genetics'

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Published: 4 June 2021
Last updated: 31 July 2024

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Journal articles on the topic "Statistical genetics"

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Dentine, M. R., and P. Narain. "Statistical Genetics." Biometrics 47, no. 2 (June 1991): 789. http://dx.doi.org/10.2307/2532180.

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Graver, Christopher. "Statistical Genetics." Medicine & Science in Sports & Exercise 40, no. 12 (December 2008): 2145. http://dx.doi.org/10.1249/01.mss.0000323663.04665.ec.

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Dries, David J. "STATISTICAL GENETICS." Shock 30, no. 4 (October 2008): 482. http://dx.doi.org/10.1097/01.shk.0000286294.71456.dc.

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Gomulkiewicz, Richard. "Statistical genetics." Mathematical Biosciences 110, no. 1 (June 1992): 133–35. http://dx.doi.org/10.1016/0025-5564(92)90020-w.

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Majumder, Partha P. "Statistical genetics." Journal of Genetics 72, no. 2-3 (December 1993): 103–4. http://dx.doi.org/10.1007/bf02927926.

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EGELAND, THORE, and PETTER F. MOSTAD. "Statistical Genetics and Genetical Statistics: a Forensic Perspective*." Scandinavian Journal of Statistics 29, no. 2 (June 2002): 297–307. http://dx.doi.org/10.1111/1467-9469.00284.

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Crusio, Wim E. "Handbook of Statistical Genetics." Genes, Brain and Behavior 7, no. 7 (October 2008): 832. http://dx.doi.org/10.1111/j.1601-183x.2008.00424_7.x.

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Shields, D. "Handbook of Statistical Genetics." Briefings in Bioinformatics 2, no. 3 (January 1, 2001): 305–7. http://dx.doi.org/10.1093/bib/2.3.305.

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Montana, G. "Statistical methods in genetics." Briefings in Bioinformatics 7, no. 3 (May 23, 2006): 297–308. http://dx.doi.org/10.1093/bib/bbl028.

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Fisher, R. "Statistical methods in genetics." International Journal of Epidemiology 39, no. 2 (February 22, 2010): 329–35. http://dx.doi.org/10.1093/ije/dyp379.

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Dissertations / Theses on the topic "Statistical genetics"

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Qiao, Dandi. "Statistical Approaches for Next-Generation Sequencing Data." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10689.

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During the last two decades, genotyping technology has advanced rapidly, which enabled the tremendous success of genome-wide association studies (GWAS) in the search of disease susceptibility loci (DSLs). However, only a small fraction of the overall predicted heritability can be explained by the DSLs discovered. One possible explanation for this ”missing heritability” phenomenon is that many causal variants are rare. The recent development of high-throughput next-generation sequencing (NGS) technology provides the instrument to look closely at these rare variants with precision and efficiency. However, new approaches for both the storage and analysis of sequencing data are in imminent needs. In this thesis, we introduce three methods that could be utilized in the management and analysis of sequencing data. In Chapter 1, we propose a novel and simple algorithm for compressing sequencing data that leverages on the scarcity of rare variant data, which enables the storage and analysis of sequencing data efficiently in current hardware environment. We also provide a C++ implementation that supports direct and parallel loading of the compressed format without requiring extra time for decompression. Chapter 2 and 3 focus on the association analysis of sequencing data in population-based design. In Chapter 2, we present a statistical methodology that allows the identification of genetic outliers to obtain a genetically homogeneous subpopulation, which reduces the false positives due to population substructure. Our approach is computationally efficient that can be applied to all the genetic loci in the data and does not require pruning of variants in linkage disequilibrium (LD). In Chapter 3, we propose a general analysis framework in which thousands of genetic loci can be tested simultaneously for association with complex phenotypes. The approach is built on spatial-clustering methodology, assuming that genetic loci that are associated with the target phenotype cluster in certain genomic regions. In contrast to standard methodology for multi-loci analysis, which has focused on the dimension reduction of data, the proposed approach profits from the availability of large numbers of genetic loci. Thus it will be especially relevant for whole-genome sequencing studies which commonly record several thousand loci per gene.
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Oldmeadow, Christopher. "Latent variable models in statistical genetics." Thesis, Queensland University of Technology, 2009. https://eprints.qut.edu.au/31995/1/Christopher_Oldmeadow_Thesis.pdf.

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Understanding the complexities that are involved in the genetics of multifactorial diseases is still a monumental task. In addition to environmental factors that can influence the risk of disease, there is also a number of other complicating factors. Genetic variants associated with age of disease onset may be different from those variants associated with overall risk of disease, and variants may be located in positions that are not consistent with the traditional protein coding genetic paradigm. Latent Variable Models are well suited for the analysis of genetic data. A latent variable is one that we do not directly observe, but which is believed to exist or is included for computational or analytic convenience in a model. This thesis presents a mixture of methodological developments utilising latent variables, and results from case studies in genetic epidemiology and comparative genomics. Epidemiological studies have identified a number of environmental risk factors for appendicitis, but the disease aetiology of this oft thought useless vestige remains largely a mystery. The effects of smoking on other gastrointestinal disorders are well documented, and in light of this, the thesis investigates the association between smoking and appendicitis through the use of latent variables. By utilising data from a large Australian twin study questionnaire as both cohort and case-control, evidence is found for the association between tobacco smoking and appendicitis. Twin and family studies have also found evidence for the role of heredity in the risk of appendicitis. Results from previous studies are extended here to estimate the heritability of age-at-onset and account for the eect of smoking. This thesis presents a novel approach for performing a genome-wide variance components linkage analysis on transformed residuals from a Cox regression. This method finds evidence for a dierent subset of genes responsible for variation in age at onset than those associated with overall risk of appendicitis. Motivated by increasing evidence of functional activity in regions of the genome once thought of as evolutionary graveyards, this thesis develops a generalisation to the Bayesian multiple changepoint model on aligned DNA sequences for more than two species. This sensitive technique is applied to evaluating the distributions of evolutionary rates, with the finding that they are much more complex than previously apparent. We show strong evidence for at least 9 well-resolved evolutionary rate classes in an alignment of four Drosophila species and at least 7 classes in an alignment of four mammals, including human. A pattern of enrichment and depletion of genic regions in the profiled segments suggests they are functionally significant, and most likely consist of various functional classes. Furthermore, a method of incorporating alignment characteristics representative of function such as GC content and type of mutation into the segmentation model is developed within this thesis. Evidence of fine-structured segmental variation is presented.
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Bruen, Trevor Cormac Vincent. "Discrete and statistical approaches to genetics." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102964.

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This thesis presents a number of major innovations in related but different areas of research. The contributions range along a continuum from mathematical phylogenetics, to development of statistical methodology for detecting recombination and finally to the application of statistical techniques to understand Feline Immunodeficiency Virus (FIV) an important pathogen. An underlying theme is the application of combinatorial and statistical ideas to problems in evolutionary biology and genetics.
Chapter 2 and Chapter 3 give a number of results relevant to mathematical phylogenetics, in particular maximum parsimony. Chapter 2 presents a new formulation of maximum parsimony in terms of character subdivision, providing a direct link with the character compatibility problem, also known as the perfect phylogeny problem. Specialization of this result to two characters gives a simple formula based on the intersection graph for calculating the parsimony score for a, pair of characters. Chapter 3 further explores maximum parsimony. In particular, it is shown that a maximum parsimony tree for a sequence of characters minimizes a subtree-prune and regraft (SPR) distance to the sets of trees on which each character is convex. Similar connections are also drawn between the Robinson-Foulds distance and a new variant of Dollo parsimony.
Chapter 4 presents an application of the work in Chapters 2 and 3 to develop a statistical test for detecting recombination. An extensive coalescent based simulation study shows that this new test is both robust and powerful in a variety of different circumstances compared to a number of current methods. In fact, a simple model of mutation rate correlation is shown to mislead a number of competing tests, causing recombination to be falsely inferred. Analysis of empirical data sets confirm that the new test is one of the best approaches to distinguish recurrent mutation from recombination.
Finally, Chapter 5 uses the test developed in Chapter 4 to localize recombinant breakpoints in 14 genomic strains of FIV taken from a wild population of cougars. Based on the technique, three recombinant strains of FIV are identified. Previous studies have focused on the epidemiology and population structure of the virus and this study shows that recombination has also played an important role in the evolution of FIV.
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Baillie, John Kenneth. "Statistical genetics in infectious disease susceptibility." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/17620.

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Death from infectious disease is common heritable, and in many cases a consequence of the host response, rather than direct effects of the pathogen. Since the host response in sepsis is orchestrated by the transmission of a variety of signals, both intra-cellular and inter-cellular, with which we have at least some capacity to intervene, it follows that it should be possible to prevent death through pharmaceutical modulation of inflammatory cascades. So far, it is not. The best candidate therapy for sepsis, activated protein C, failed to live up to initial promise and was ultimately withdrawn from the market in dismal failure. The premise of the work presented here is that a different approach – to develop an understanding of the host response at a genomic level – may yield more tractable insights, specifically into the problem of host susceptibility to influenza, a heritable cause of death in otherwise healthy people and a significant global threat. Since the sequencing of the human genome, it has become possible to identify genomic loci underlying host susceptibility to disease using genome-wide association studies (GWAS), best exemplified by the Wellcome Trust Case Control Consortium. This new technology creates substantial new challenges. The genetic markers associated with a phenotype are rarely causative, frequently in poorly-understood intergenic regions, and tend to have small effect sizes, such that tens or even hundreds of thousands of subjects must be recruited to have sufficient power to detect them. It is therefore not straightforward to translate these genotype-phenotype associations into useful understanding of the role of genes and gene products in disease pathogenesis. Attempts to overcome these challenges in order to discover genomic loci underlying individual susceptibility to infection form the core of this thesis. Ultimately these efforts converge with the development of a new computational method to detect phenotype-associated loci from genome-wide association studies (GWAS) using co-expression at regulatory regions of the genome.
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Mitchell, Brittany L. "Statistical genetic analyses of neuropsychological traits." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/227852/14/Brittany%20Mitchell%20Thesis.pdf.

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Neuropsychological traits affect both the brain and behaviour and are responsible for a large proportion of worldwide disability. This PhD thesis employs computational, statistical and genetic approaches to identify and understand the genetic and environmental influences on a wide range of psychiatric, neurological and cognitive disorders. The work presented in this thesis details novel findings on several fronts including new genetic marker discovery, using genetics to predict an individual’s disease risk, and disentangling pertinent risk factors that affect cognitive and mental health. This insight is an important step towards developing more effective treatments and intervention strategies.
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Hudson, Julie. "Maternal Gene-Environment Effects: An Evaluation of Statistical Approaches to Detect Effects and an Investigation of the Effect of Violations of Model Assumptions." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39637.

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Discovering the associations between genetic variables and disease status can help reduce the burden of disease on society. This thesis focuses on the methods required to detect maternal genetic effects (an effect where the genes of the mother affect the disease risk of the child) and interaction effects between these maternal genes and environmental variables in trio data consisting of parents and an affected child. A simulation study was conducted to determine the extent to which testing for these effects is affected by violations to the mating symmetry assumption required for two current methods when control parents are not available.. This study showed that methods for maternal effect estimation are not robust to these violations; however, the interaction test is robust to the violation. Finally, a candidate gene study on orofacial clefts was conducted to evaluate maternal gene-environment interactions in international consortium data. Significant effects were found but the large magnitude of the effect estimates raises concerns about the validity of the results. This thesis tries also discusses the lack of methods and software available to estimate maternal gene environment interactions.
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Casale, Francesco Paolo. "Multivariate linear mixed models for statistical genetics." Thesis, University of Cambridge, 2016. https://www.repository.cam.ac.uk/handle/1810/267465.

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In the last decade, genome-wide association studies have helped to advance our understanding of the genetic architecture of many important traits, including diseases. However, the statistical analysis of genotype-phenotype associations remains challenging due to multiple factors. First, many traits have polygenic architectures, which means that they are controlled by a large number of variants with small individual effects. Second, as increasingly deep phenotype data are being generated there is a need for multivariate analysis approaches to leverage multiple related phenotypes while retaining computational efficiency. Additionally, genetic analyses are confronted by strong confounding factors that can create spurious associations when not properly accounted for in the statistical model. We here derive more flexible methods that allow integrating genetic effects across variants and multiple quantitative traits. To do so, we build on the classical linear mixed model (LMM), a widely adopted framework for genetic studies. The first contribution of this thesis is mtSet, an efficient mixed-model approach that enables genome-wide association testing between sets of genetic variants and multiple traits while accounting for confounding factors. In both simulations and real-data applications we demonstrate that mtSet effectively combines the advantages of variant-set and multi-trait analyses. Next, we present a new model for gene-context interactions that builds on mtSet. The proposed interaction set test (iSet) yields increased statistical power for detecting polygenic interactions. Additionally, iSet enables the identification of genetic loci that are associated with different configurations of causal variants across contexts. After benchmarking the proposed method using simulated data, we consider two applications to real datasets, where we investigate genetic effects on gene expression across different cellular contexts and sex-specific genetic effects on lipid levels. Finally, we describe LIMIX, a software framework for the flexible implementation of different LMMs. Most of the models considered in this thesis, including mtSet and iSet, are implemented and available in LIMIX. A unique aspect of the software is an inference framework that allows a large class of genetic models to be defined and, in many cases, to be efficiently fitted by exploiting specific algebraic properties. We demonstrate the utility of this software suite in two applied collaboration projects. Taken together, this thesis demonstrates the value of flexible and integrative modelling in genetics and contributes new statistical methods for genetic analysis. These approaches generalise previous models, yet retain the computational efficiency that is needed to tackle large genetic datasets.
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Csilléry, Katalin. "Statistical inference in population genetics using microsatellites." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3865.

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Statistical inference from molecular population genetic data is currently a very active area of research for two main reasons. First, in the past two decades an enormous amount of molecular genetic data have been produced and the amount of data is expected to grow even more in the future. Second, drawing inferences about complex population genetics problems, for example understanding the demographic and genetic factors that shaped modern populations, poses a serious statistical challenge. Amongst the many different kinds of genetic data that have appeared in the past two decades, the highly polymorphic microsatellites have played an important role. Microsatellites revolutionized the population genetics of natural populations, and were the initial tool for linkage mapping in humans and other model organisms. Despite their important role, and extensive use, the evolutionary dynamics of microsatellites are still not fully understood, and their statistical methods are often underdeveloped and do not adequately model microsatellite evolution. In this thesis, I address some aspects of this problem by assessing the performance of existing statistical tools, and developing some new ones. My work encompasses a range of statistical methods from simple hypothesis testing to more recent, complex computational statistical tools. This thesis consists of four main topics. First, I review the statistical methods that have been developed for microsatellites in population genetics applications. I review the different models of the microsatellite mutation process, and ask which models are the most supported by data, and how models were incorporated into statistical methods. I also present estimates of mutation parameters for several species based on published data. Second, I evaluate the performance of estimators of genetic relatedness using real data from five vertebrate populations. I demonstrate that the overall performance of marker-based pairwise relatedness estimators mainly depends on the population relatedness composition and may only be improved by the marker data quality within the limits of the population relatedness composition. Third, I investigate the different null hypotheses that may be used to test for independence between loci. Using simulations I show that testing for statistical independence (i.e. zero linkage disequilibrium, LD) is difficult to interpret in most cases, and instead a null hypothesis should be tested, which accounts for the “background LD” due to finite population size. I investigate the utility of a novel approximate testing procedure to circumvent this problem, and illustrate its use on a real data set from red deer. Fourth, I explore the utility of Approximate Bayesian Computation, inference based on summary statistics, to estimate demographic parameters from admixed populations. Assuming a simple demographic model, I show that the choice of summary statistics greatly influences the quality of the estimation, and that different parameters are better estimated with different summary statistics. Most importantly, I show how the estimation of most admixture parameters can be considerably improved via the use of linkage disequilibrium statistics from microsatellite data.
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Sperrin, Matthew. "Statistical methodology motivated by problems in genetics." Thesis, Lancaster University, 2010. http://eprints.lancs.ac.uk/49088/.

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Sequencing the human genome has made vast amounts of potentially useful genetic data accessible. An important challenge in statistics is to develop methodology to extract information from this data. In this thesis, developments are made in two methodological areas that have wide applications in genetics. First, probabilistic methods to deal with the label switching problem in Bayesian mixture models are introduced. Mixture models are used in situations where populations may consist of a number of sub-populations, or as a semi-parametric modelling tool. The label switching problem can prevent meaningful interpretation of the output of Markov Chain Monte Carlo samplers. Specifically, inference on attributes specific to sub-populations can be difficult. Such attributes play an important role in understanding genetic effects. We introduce probabilistic relabelling strategies as a natural way of overcoming the label switching problem, and compare with existing strategies. The comparisons demonstrate that the advantages oered by probabilistic strategies come without loss in parameter estimation ability. Second, we introduce direct eect testing (DET), which is a novel method that distinguishes direct from indirect eects between binary predictors and a binary response. DET consists of two stages: the rst stage nds eects, the second stage infers the uncertainty in determining which predictors cause which eects. The method is useful when it is of interest to recover direct eects between a large number of predictors and the response. This is a common goal in genetics, where we are interested in the eects of variations in the genome on the prevalence of a phenotype. This work includes detailed simulations, comparing the ability of a number of methods at recovering direct eects. DET outperforms existing methods at recovering direct eects in situations where there is high correlation between predictors, and matches their performance when the correlation is moderate or small.
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Lange, Christoph. "Generalized estimating equation methods in statistical genetics." Thesis, University of Reading, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269921.

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Books on the topic "Statistical genetics"

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Prem, Narain. Statistical genetics. New York: Wiley, 1990.

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J, Balding D., Bishop M. J, and Cannings C. 1942-, eds. Handbook of statistical genetics. 3rd ed. Chichester, England: John Wiley & Sons, 2007.

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Elston, Robert C., Jaya M. Satagopan, and Shuying Sun, eds. Statistical Human Genetics. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-555-8.

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Elston, Robert C., ed. Statistical Human Genetics. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7274-6.

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1932-, Elston Robert C., Olson Jane M, and Palmer Lyle, eds. Biostatistical genetics and genetic epidemiology. Chichester, England: New York, NY, USA, 2002.

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Balding, D. J., M. Bishop, and C. Cannings, eds. Handbook of Statistical Genetics. Chichester, UK: John Wiley & Sons, Ltd, 2007. http://dx.doi.org/10.1002/9780470061619.

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Balding, D. J., M. Bishop, and C. Cannings, eds. Handbook of Statistical Genetics. Chichester: John Wiley & Sons, Ltd, 2004. http://dx.doi.org/10.1002/0470022620.

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Gordon, Derek, Stephen J. Finch, and Wonkuk Kim. Heterogeneity in Statistical Genetics. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61121-7.

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J, Balding D., Bishop M, and Cannings C. 1942-, eds. Handbook of statistical genetics. Chichester: Wiley, 2001.

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Sorensen, Daniel. Statistical Learning in Genetics. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-35851-7.

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Book chapters on the topic "Statistical genetics"

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Wilson, Susan R. "Statistical Genetics." In International Encyclopedia of Statistical Science, 1417–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_79.

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Goldstein, Darlene R. "Statistical Genetics." In Selected Works of Terry Speed, 471–533. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-1347-9_12.

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Beaumont, M. A. "Conservation Genetics." In Handbook of Statistical Genetics, 1021–66. Chichester, UK: John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch30.

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Teare, M. D. "Cancer Genetics." In Handbook of Statistical Genetics, 1286–300. Chichester, UK: John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch39.

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Bromek, Tadeusz, and Elżbieta Pleszczyńska. "Statistical problems of population genetics." In Statistical Inference, 137–59. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-009-0575-7_7.

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Morabito, A. "Log-Linear Models in Genetics." In Statistical Modelling, 242–49. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-3680-1_28.

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Walsh, B. "Evolutionary Quantitative Genetics." In Handbook of Statistical Genetics, 533–86. Chichester, UK: John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch17.

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Foulkes, Andrea S. "Elementary Statistical Principles." In Applied Statistical Genetics with R, 29–63. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-89554-3_2.

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Ewens, W. J. "Statistical Methods in Human Genetics." In Statistics in Genetics, 147–64. New York, NY: Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4757-3103-3_8.

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Ashcroft, R. E. "Ethics Issues in Statistical Genetics." In Handbook of Statistical Genetics, 1323–45. Chichester, UK: John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch41.

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Conference papers on the topic "Statistical genetics"

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Fan, QiaoChu, Zi jie Lu, and Yu chen Liu. "Statistical research methods for genetics." In 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), edited by Chi-Hua Chen, Xuexia Ye, and Hari Mohan Srivastava. SPIE, 2022. http://dx.doi.org/10.1117/12.2639273.

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Robinson, John-Paul, Purushotham Bangalore, Jelai Wang, and Tapan Mehta. "Powering statistical genetics with the grid." In the 15th ACM Mardi Gras conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1341811.1341856.

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Hollifield, M. K., M. Bermann, D. Lourenco, and I. Misztal. "329. Exploring the statistical nature of independent chromosome segments." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_329.

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"Statistical estimates of the transcription factor binding sites cluster in Arabidopsis and distant plant species genomes." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Novosibirsk ICG SB RAS 2021, 2021. http://dx.doi.org/10.18699/plantgen2021-149.

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Calderon Torres, Claudia Marissa. "WEBSITE FOR ONLINE OR BLENDED TEACHING OF GENETICS FOR THE DEVELOPMENT OF KNOWLEDGE AND SKILLS IN BIOLOGY STUDENTS." In EduCon Tokyo –International Conference on Education, 17-18 January 2024. Global Research & Development Services, 2024. http://dx.doi.org/10.20319/ictel.2024.3537.

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Genetics is the science that studies the transmission and variation of the hereditary information of organisms stored in DNA. Currently, Genetics encompasses a strategic set of knowledge and skills that biology professionals must have, in such a way that those who do not have this knowledge, techniques and even theories, run the risk of not entering a job position. Objective. This work presents a web page developed to facilitate the learning of Genetics knowledge. This project brings together participants who have carried out scientific and professional work, have taught genetics courses and know the problems of teaching and learning genetics. Results. The developed website (www.genetica.abaco2.org) incorporates: 1) Educational texts for the development of knowledge, skills and competencies on specific topics; 2) Multiple choice questionnaires for self-assessment; 3) Hardy-Weinberg simulator; and 4) Evaluation of the understanding of educational texts through the application of quick questionnaires. The texts are focused on undergraduate students of careers in the biological-medical area. The effect on learning of the contents of the website with the topic of genetic recombination was evaluated by comparing the learning in two groups of students: group A (133 students) with prior reading of the educational text and group B (119 students) without reading of the educational text. Through statistical analysis with the Z test it was found that group A had higher percentage (75.6% vs. 55.8%; P<0.01) of correct answers when answering a test of 10 questions. Conclusions: The designed website is a resource that teachers and students can benefit from by facilitating the teaching-learning process of Genetics.
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Fotokian, Mohammad H., Kamel Ariffin Mohd Atan, and Isthrinayagy S. Krishnarajah. "Genetics-Statistical Analysis of Traits Related to Grain in Rice (Oryza sativa L.)." In INTERNATIONAL CONFERENCE ON MATHEMATICAL BIOLOGY 2007: ICMB07. AIP, 2008. http://dx.doi.org/10.1063/1.2883843.

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Lutze, Margaret, Nancy J. Cox, Vivianne C. Smith, and Joel Pokorny. "Genetics of Rayleigh matches and photometric matches in normals." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1988. http://dx.doi.org/10.1364/oam.1988.mz3.

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At the 1988 ARVO meeting we presented Rayleigh match midpoint and photometric match data collected from a population of nonrelated males and from family members. Photometric matches between a 667- and 551-nm stimulus were obtained using heterochromatic modulation photometry (HMP). We employed statistical methods to determine whether the source of variation for each of these traits was due to allelic variation at a single gene locus, variation at multiple loci (polygenic), or environmental factors. Results indicated that variations in Rayleigh match midpoints and HMP photometric matches in observers with normal color vision were each consistent with allelic variation at a single gene locus.
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Sugiyama, Mahito, and Karsten Borgwardt. "Finding Statistically Significant Interactions between Continuous Features." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/484.

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The search for higher-order feature interactions that are statistically significantly associated with a class variable is of high relevance in fields such as Genetics or Healthcare, but the combinatorial explosion of the candidate space makes this problem extremely challenging in terms of computational efficiency and proper correction for multiple testing. While recent progress has been made regarding this challenge for binary features, we here present the first solution for continuous features. We propose an algorithm which overcomes the combinatorial explosion of the search space of higher-order interactions by deriving a lower bound on the p-value for each interaction, which enables us to massively prune interactions that can never reach significance and to thereby gain more statistical power. In our experiments, our approach efficiently detects all significant interactions in a variety of synthetic and real-world datasets.
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Ueno, Augusto Yoshiro, Ivo Emilio da Cruz Jung, Ivana Beatrice Mânica da Cruz, and Fernanda Barbisan. "Depression and psychological distress in elders are influenced by the antioxidant enzyme SOD2." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.003.

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Introduction: Depression and psychological stress have high prevalence and incidence rates, affecting the individual welfare and increasing the risks for non-infectious chronic diseases. Studies have shown relations between inflammation and oxidative stress. In genetics, the single nucleotide polymorphism (SNP), inside the superoxide dismutase gene (Val16Ala-SOD2), is an important study subject to comprehend the risks of developing depression because its different genotypes can impact the balance between superoxide and hydrogen peroxide. The genotype VV favors the superoxide, the AA favors the peroxide and the AV generates similar amounts. Objectives: Evaluate the relation between oxidative unbalance, generated by Val16Ala-SOD2 SNP, and the rates of depression in elders. Methods: The study, approved by the ethics committee of UFSM, was a case-control analysis to examine the association between Val16Ala-SOD2 SNP, depression and stress in elders. Genetical analysis was made by polymerase chain reactions. The sample had 612 elders from Gravataí (RS). Depression was diagnosed using the geriatric depression scale- 15 and the stress by self perception. Statistical analysis was made by SSPS. Results: From the 612 elders (with similar ages and lifestyles), 115 were diagnosed with depression; the other 497 composed the control group. The analyses showed significantly higher frequency of the genotype VV in those who had depression, compared with the allele A. Conclusion: The results indicate strong association of the Val16Ala-SOD2 SNP, the risks of depression and psychological stress, probably due to the increasing oxidative stress and inflammatory state associated with the recessive genotype, VV.
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Mézard, Marc. "Statistical physics and statistical inference." In GECCO '21: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3449639.3465420.

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Reports on the topic "Statistical genetics"

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Ott, Jurg. Statistical Genetics Methods for Localizing Multiple Breast Cancer Genes. Fort Belvoir, VA: Defense Technical Information Center, September 1996. http://dx.doi.org/10.21236/ada326461.

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Ott, Jurg. Statistical Genetics Methods for Localizing Multiple Breast Cancer Genes. Fort Belvoir, VA: Defense Technical Information Center, September 1997. http://dx.doi.org/10.21236/ada337861.

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Ott, Jurg. Statistical Genetic Methods for Localizing Multiple Breast Cancer Genes. Fort Belvoir, VA: Defense Technical Information Center, September 1995. http://dx.doi.org/10.21236/ada301699.

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Solvin, Thomas, and Inger Sundheim Fløistad. Statistics: Forest Seeds and Plants in the Nordic Region – Version 2023. The Nordic Genetic Resource Center (NordGen), August 2023. http://dx.doi.org/10.53780/qoub7866.

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The Nordic Genetic Resource Center (NordGen) is the joint genebank and knowledge center for genetic resources in the Nordic countries. Our mission is to conserve and promote the sustainable use of genetic diversity among animals, forests and plants that are important for Nordic agriculture and forestry. “Statistics: Forest Seeds and Plants in the Nordic Region – Version 2023” is the second edition in a biennial statistics report on forest seed and plant material in the Nordic countries. The first edition was published in 2021. This edition has been expanded by including more statistics and more species than the first report, as well as including more recent data from the years 2020 and 2021. The report compiles statistics and reports contributed by representatives of each country in the NordGen Forest Regeneration Council.
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Lers, Amnon, Majid R. Foolad, and Haya Friedman. genetic basis for postharvest chilling tolerance in tomato fruit. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7600014.bard.

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ABSTRACT Postharvest losses of fresh produce are estimated globally to be around 30%. Reducing these losses is considered a major solution to ensure global food security. Storage at low temperatures is an efficient practice to prolong postharvest performance of crops with minimal negative impact on produce quality or human health and the environment. However, many fresh produce commodities are susceptible to chilling temperatures, and the application of cold storage is limited as it would cause physiological chilling injury (CI) leading to reduced produce quality. Further, the primary CI becomes a preferred site for pathogens leading to decay and massive produce losses. Thus, chilling sensitive crops should be stored at higher minimal temperatures, which curtails their marketing life and in some cases necessitates the use of other storage strategies. Development of new knowledge about the biological basis for chilling tolerance in fruits and vegetables should allow development of both new varieties more tolerant to cold, and more efficient postharvest storage treatments and storage conditions. In order to improve the agricultural performance of modern crop varieties, including tomato, there is great potential in introgression of marker-defined genomic regions from wild species onto the background of elite breeding lines. To exploit this potential for improving tomato fruit chilling tolerance during postharvest storage, we have used in this research a recombinant inbred line (RIL) population derived from a cross between the red-fruited tomato wild species SolanumpimpinellifoliumL. accession LA2093 and an advanced Solanum lycopersicumL. tomato breeding line NCEBR-1, developed in the laboratory of the US co-PI. The original specific objectives were: 1) Screening of RIL population resulting from the cross NCEBR1 X LA2093 for fruit chilling response during postharvest storage and estimation of its heritability; 2) Perform a transcriptopmic and bioinformatics analysis for the two parental lines following exposure to chilling storage. During the course of the project, we learned that we could measure greater differences in chilling responses among specific RILs compared to that observed between the two parental lines, and thus we decided not to perform transcriptomic analysis and instead invest our efforts more on characterization of the RILs. Performing the transcriptomic analysis for several RILs, which significantly differ in their chilling tolerance/sensitivity, at a later stage could result with more significant insights. The RIL population, (172 lines), was used in field experiment in which fruits were examined for chilling sensitivity by determining CI severity. Following the field experiments, including 4 harvest days and CI measurements, two extreme tails of the response distribution, each consisting of 11 RILs exhibiting either high sensitivity or tolerance to chilling stress, were identified and were further examined for chilling response in greenhouse experiments. Across the RILs, we found significant (P < 0.01) correlation between field and greenhouse grown plants in fruit CI. Two groups of 5 RILs, whose fruits exhibited reproducible chilling tolerant/sensitive phenotypes in both field and greenhouse experiments, were selected for further analyses. Numerous genetic, physiological, biochemical and molecular variations were investigated in response to postharvest chilling stress in the selected RILs. We confirmed the differential response of the parental lines of the RIL population to chilling stress, and examined the extent of variation in the RIL population in response to chilling treatment. We determined parameters which would be useful for further characterization of chilling response in the RIL population. These included chlorophyll fluorescence Fv/Fm, water loss, total non-enzymatic potential of antioxidant activity, ascorbate and proline content, and expression of LeCBF1 gene, known to be associated with cold acclimation. These parameters could be used in continuation studies for the identification and genetic mapping of loci contributing to chilling tolerance in this population, and identifying genetic markers associated with chilling tolerance in tomato. Once genetic markers associated with chilling tolerance are identified, the trait could be transferred to different genetic background via marker-assisted selection (MAS) and breeding. The collaborative research established in this program has resulted in new information and insights in this area of research and the collaboration will be continued to obtain further insights into the genetic, molecular biology and physiology of postharvest chilling tolerance in tomato fruit. The US Co-PI, developed the RIL population that was used for screening and measurement of the relevant chilling stress responses and conducted statistical analyses of the data. Because we were not able to grow the RIL population under field conditions in two successive generations, we could not estimate heritability of response to chilling temperatures. However, we plan to continue the research, grow the RIL progeny in the field again, and determine heritability of chilling tolerance in a near future. The IS and US investigators interacted regularly and plan to continue and expand on this study, since combing the expertise of the Co-PI in genetics and breeding with that of the PI in postharvest physiology and molecular biology will have great impact on this line of research, given the significant findings of this one-year feasibility project.
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Guo, Boyun, Andrew Duguid, and Ronar Nygaard. Statistical Analysis of CO2 Exposed Wells to Predict Long Term Leakage through the Development of an Integrated Neural-Genetic Algorithm. Office of Scientific and Technical Information (OSTI), August 2017. http://dx.doi.org/10.2172/1373948.

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Weller, Joel, Harris Lewin, Micha Ron, George Wiggans, and Paul VanRaden. A Systematic Genome Search for Genes Affecting Economic Traits Dairy Cattle with the Aid of Genetic Markers. United States Department of Agriculture, April 1999. http://dx.doi.org/10.32747/1999.7695836.bard.

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The objectives were to continue collection of semen for the US dairy bull DNA repository, to conduct a systematic search of the Holstein genome for economically significant economic trait loci (ETL), to develop and refine statistical techniques for the analysis of the data generated, and to confirm significant effects by genotyping daughters i Israel and additional US sons. One-thousand-seventy-six sons of eight US grandsires were genotyped for 174 microsatellites located on all 29 autosomes. ETL were detected for milk production traits on seven chromosomes. ETL for milk and fat yield and fat and protein percentage on BTA3 was mapped to between the markers BL41 and TGLA263. The 95% confidence interval for the ETL affecting fat percentage on BTA14 localized this ETL between the contromere and chromosome position 11 cM. This ETL was verified in the Israeli cattle population by genotyping an independent sample of cows from seven families. The radiation hybrid data for the centromeric region of BTA14 is defined by a single linkage group. Order of Type I genes within this region, CYC-FADK-TG-SQLE, is conserved between human and cattle. Thus, HSA8, the human homologue of BTA14, can be used to identify candidate genes for the ETL.
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Allen, J., and S. Velsko. A Statistical Framework for Microbial Source Attribution: Measuring Uncertainty in Host Transmission Events Inferred from Genetic Data (Part 2 of a 2 Part Report). Office of Scientific and Technical Information (OSTI), November 2009. http://dx.doi.org/10.2172/971053.

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Hovav, Ran, Peggy Ozias-Akins, and Scott A. Jackson. The genetics of pod-filling in peanut under water-limiting conditions. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7597923.bard.

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Pod-filling, an important yield-determining stage is strongly influenced by water stress. This is particularly true for peanut (Arachishypogaea), wherein pods are developed underground and are directly affected by the water condition. Pod-filling in peanut has a significant genetic component as well, since genotypes are considerably varied in their pod-fill (PF) and seed-fill (SF) potential. The goals of this research were to: Examine the effects of genotype, irrigation, and genotype X irrigation on PF and SF. Detect global changes in mRNA and metabolites levels that accompany PF and SF. Explore the response of the duplicate peanut pod transcriptome to drought stress. Study how entire duplicated PF regulatory processes are networked within a polyploid organism. Discover locus-specific SNP markers and map pod quality traits under different environments. The research included genotypes and segregating populations from Israel and US that are varied in PF, SF and their tolerance to water deficit. Initially, an extensive field trial was conducted to investigate the effects of genotype, irrigation, and genotype X irrigation on PF and SF. Significant irrigation and genotypic effect was observed for the two main PF related traits, "seed ratio" and "dead-end ratio", demonstrating that reduction in irrigation directly influences the developing pods as a result of low water potential. Although the Irrigation × Genotype interaction was not statistically significant, one genotype (line 53) was found to be more sensitive to low irrigation treatments. Two RNAseq studies were simultaneously conducted in IL and the USA to characterize expression changes that accompany shell ("source") and seed ("sink") biogenesis in peanut. Both studies showed that SF and PF processes are very dynamic and undergo very rapid change in the accumulation of RNA, nutrients, and oil. Some genotypes differ in transcript accumulation rates, which can explain their difference in SF and PF potential; like cvHanoch that was found to be more enriched than line 53 in processes involving the generation of metabolites and energy at the beginning of seed development. Interestingly, an opposite situation was found in pericarp development, wherein rapid cell wall maturation processes were up-regulated in line 53. Although no significant effect was found for the irrigation level on seed transcriptome in general, and particularly on subgenomic assignment (that was found almost comparable to a 1:1 for A- and B- subgenomes), more specific homoeologous expression changes associated with particular biosynthesis pathways were found. For example, some significant A- and B- biases were observed in particular parts of the oil related gene expression network and several candidate genes with potential influence on oil content and SF were further examined. Substation achievement of the current program was the development and application of new SNP detection and mapping methods for peanut. Two major efforts on this direction were performed. In IL, a GBS approach was developed to map pod quality traits on Hanoch X 53 F2/F3 generations. Although the GBS approach was found to be less effective for our genetic system, it still succeeded to find significant mapping locations for several traits like testa color (linkage A10), number of seeds/pods (A5) and pod wart resistance (B7). In the USA, a SNP array was developed and applied for peanut, which is based on whole genome re-sequencing of 20 genotypes. This chip was used to map pod quality related traits in a Tifrunner x NC3033 RIL population. It was phenotyped for three years, including a new x-ray method to phenotype seed-fill and seed density. The total map size was 1229.7 cM with 1320 markers assigned. Based on this linkage map, 21 QTLs were identified for the traits 16/64 weight, kernel percentage, seed and pod weight, double pod and pod area. Collectively, this research serves as the first fundamental effort in peanut for understanding the PF and SF components, as a whole, and as influenced by the irrigation level. Results of the proposed study will also generate information and materials that will benefit peanut breeding by facilitating selection for reduced linkage drag during introgression of disease resistance traits into elite cultivars. BARD Report - Project4540 Page 2 of 10
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Hutchinson, M. L., J. E. L. Corry, and R. H. Madden. A review of the impact of food processing on antimicrobial-resistant bacteria in secondary processed meats and meat products. Food Standards Agency, October 2020. http://dx.doi.org/10.46756/sci.fsa.bxn990.

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For meat and meat products, secondary processes are those that relate to the downstream of the primary chilling of carcasses. Secondary processes include maturation chilling, deboning, portioning, mincing and other operations such as thermal processing (cooking) that create fresh meat, meat preparations and ready-to-eat meat products. This review systematically identified and summarised information relating to antimicrobial resistance (AMR) during the manufacture of secondary processed meatand meat products (SPMMP). Systematic searching of eight literature databases was undertaken and the resultantpapers were appraised for relevance to AMR and SPMMP. Consideration was made that the appraisal scores, undertaken by different reviewers, were consistent. Appraisal reduced the 11,000 initially identified documents to 74, which indicated that literature relating to AMR and SPMMP was not plentiful. A wide range of laboratory methods and breakpoint values (i.e. the concentration of antimicrobial used to assess sensitivity, tolerance or resistance) were used for the isolation of AMR bacteria.The identified papers provided evidence that AMR bacteria could be routinely isolated from SPMMP. There was no evidence that either confirmed or refuted that genetic materials capable of increasing AMR in non-AMR bacteria were present unprotected (i.e. outside of a cell or a capsid) in SPMMP. Statistical analyses were not straightforward because different authors used different laboratory methodologies.However, analyses using antibiotic organised into broadly-related groups indicated that Enterobacteriaceaeresistant to third generation cephalosporins might be an area of upcoming concern in SPMMP. The effective treatment of patients infected with Enterobacteriaceaeresistant to cephalosporins are a known clinical issue. No AMR associations with geography were observed and most of the publications identified tended to be from Europe and the far east.AMR Listeria monocytogenes and lactic acid bacteria could be tolerant to cleaning and disinfection in secondary processing environments. The basis of the tolerance could be genetic (e.g. efflux pumps) or environmental (e.g. biofilm growth). Persistent, plant resident, AMR L. monocytogenes were shown by one study to be the source of final product contamination. 4 AMR genes can be present in bacterial cultures used for the manufacture of fermented SPMMP. Furthermore, there was broad evidence that AMR loci could be transferred during meat fermentation, with refrigeration temperatures curtailing transfer rates. Given the potential for AMR transfer, it may be prudent to advise food business operators (FBOs) to use fermentation starter cultures that are AMR-free or not contained within easily mobilisable genetic elements. Thermal processing was seen to be the only secondary processing stage that served as a critical control point for numbers of AMR bacteria. There were significant linkages between some AMR genes in Salmonella. Quaternary ammonium compound (QAC) resistance genes were associated with copper, tetracycline and sulphonamide resistance by virtue of co-location on the same plasmid. No evidence was found that either supported or refuted that there was any association between AMR genes and genes that encoded an altered stress response or enhanced the survival of AMR bacteria exposed to harmful environmental conditions.
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