Academic literature on the topic 'Linkage disequilibrium'
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Journal articles on the topic "Linkage disequilibrium"
Tachida, Hidenori. "Decay of linkage disequilibrium in a finite island model." Genetical Research 64, no. 2 (October 1994): 137–44. http://dx.doi.org/10.1017/s0016672300032742.
Full textWeitzman, Jonathan B. "Linkage disequilibrium." Genome Biology 2 (2001): spotlight—20010514–01. http://dx.doi.org/10.1186/gb-spotlight-20010514-01.
Full textMiyashita, Naohiko T., Montserrat Aguadé, and Charles H. Langley. "Linkage disequilibrium in the white locus region of Drosophila melanogaster." Genetical Research 62, no. 2 (October 1993): 101–9. http://dx.doi.org/10.1017/s0016672300031694.
Full textWu, Rongling, and Zhao-Bang Zeng. "Joint Linkage and Linkage Disequilibrium Mapping in Natural Populations." Genetics 157, no. 2 (February 1, 2001): 899–909. http://dx.doi.org/10.1093/genetics/157.2.899.
Full textKuno, Shin-ichi. "Division of linkage disequilibrium between absolute linkage disequilibrium and linkage equilibrium." Journal of Human Genetics 50, no. 6 (June 2005): 315–16. http://dx.doi.org/10.1007/s10038-005-0256-6.
Full textBaird, Stuart J. E. "Exploring linkage disequilibrium." Molecular Ecology Resources 15, no. 5 (August 11, 2015): 1017–19. http://dx.doi.org/10.1111/1755-0998.12424.
Full textSchaeffer, S. W., and E. L. Miller. "Estimates of linkage disequilibrium and the recombination parameter determined from segregating nucleotide sites in the alcohol dehydrogenase region of Drosophila pseudoobscura." Genetics 135, no. 2 (October 1, 1993): 541–52. http://dx.doi.org/10.1093/genetics/135.2.541.
Full textLou, Xiang-Yang, George Casella, Ramon C. Littell, Mark C. K. Yang, Julie A. Johnson, and Rongling Wu. "A Haplotype-Based Algorithm for Multilocus Linkage Disequilibrium Mapping of Quantitative Trait Loci With Epistasis." Genetics 163, no. 4 (April 1, 2003): 1533–48. http://dx.doi.org/10.1093/genetics/163.4.1533.
Full textHsu, Fang-Chi, Kung-Yee Liang, and Terri H. Beaty. "Multipoint linkage disequilibrium mapping approach: Incorporating evidence of linkage and linkage disequilibrium from unlinked region." Genetic Epidemiology 25, no. 1 (June 11, 2003): 1–13. http://dx.doi.org/10.1002/gepi.10241.
Full textSabatti, Chiara, and Neil Risch. "Homozygosity and Linkage Disequilibrium." Genetics 160, no. 4 (April 1, 2002): 1707–19. http://dx.doi.org/10.1093/genetics/160.4.1707.
Full textDissertations / Theses on the topic "Linkage disequilibrium"
Hernandez-Sanchez, Jules. "Gene mapping using linkage disequilibrium." Thesis, University of Edinburgh, 2002. http://hdl.handle.net/1842/14058.
Full textVeroneze, Renata. "Linkage disequilibrium and genomic selection in pigs." Universidade Federal de Viçosa, 2015. http://www.locus.ufv.br/handle/123456789/7597.
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A seleção genômica (SG) e associação genômica ampla (GWAS) são métodos que exploram o desequilíbrio de ligação (LD) entre marcadores e loci de características quantitativas (QTL). Um dos fatores limitantes para a implementação da SG é a necessidade de um grande número de animais genotipados e fenotipados para obtenção de valores genéticos com alta acurácia. Essa limitação pode ser superada combinando dados de múltiplas populações ou utilizando dados de animais cruzados. O objetivo geral desta tese foi caracterizar os padrões de LD de diferentes populações de suínos. Além disso, avaliar em que medida as diferenças de LD se refletem na acurácia da seleção genômica quando utilizadas diferentes metodologias e arranjos para população de referência e validação. Os arranjos testados foram: utilização de subconjuntos da mesma população como referência e validação (within), populações diferentes nos conjuntos de referência e validação (across) e combinação de duas populações na referência (multi). Nessa tese foram utilizados dados de suínos de linhas puras e de animais cruzados, genotipados com o PorcineSNP60 BeadChip. A regressão Loess proporcionou melhor ajuste aos dados de LD, bem como em predições mais acuradas em comparação a regressão não linear. Mostrou-se também, que a regressão Loess pode ser utilizada para realizar uma comparação estatística do LD decay de diferentes populações. A persistência de fase do LD entre animais cruzados e as linhas puras parentais foi alta, o que nos leva a hipotetizar que associações marcador-QTL similares poderiam ser encontradas em animais cruzados e as linhas parentais e, portanto, esperava-se encontrar altas acurácias de predição genômica entre essas populações. Entre as linhas puras a persistência de fase foi baixa, logo painéis de SNPs de maior densidade deveriam ser utilizados para manter a mesma associação marcador-QTL entre essas linhas. Acurácias obtidas na predição genômica utilizando animais cruzados assim como os arranjos across e multi, não seguiram as expectativas baseadas em LD. Portanto, a consistência de fase de ligação entre populações pode não ser tão importante para a acurácia da seleção genômica como se pensava, mas sim a ação combinada de LD, arquitetura genética e frequências alélicas. Portanto, foi desenvolvida uma metodologia que leva em consideração differenças nas frequências alélicas, bem como informações dos GWAS para comtemplar a arquitetura genética da característica. Esta estratégia trouxe alguns benefícios para a predição genônima para os arranjos within e multi. Ponderações obtidas por meio de GWAS em diferentes conjuntos de dados (uma única população e combinando múltiplas populações) nem sempre resultou em aumento da acurácia, sendo dependente da linha que estava sob seleção. O uso de pesos advindos do GWAS ao se utilizar uma população combinada resultou nas melhores acurácias tanto para os arranjos within quanto multi. A avaliação e o entendimento de como diferenças de LD, frequências alélicas e arquitetura genética afetam a acurácia da predição genômica é fundamental para otimizar a inserção da seleção genômica no melhoramento de suínos.
Genomic selection and genomic wide association studies (GWAS) are widely used methods that aim to exploit the linkage disequilibrium (LD) between markers and quantitative trait loci (QTL). Securing a sufficiently large set of genotypes and phenotypes can be a limiting factor when implementing genomic selection that may be overcome by combining data from multiple populations or using crossbred information. The overall objective of this thesis was to characterize LD patterns in different pig populations and to evaluate whether the differences in LD determine the accuracy of genomic predictions when using different reference sets (within-, across- and multi- population) and methodologies. In this thesis I used data from pure lines and crossbred pig populations genotyped with PorcineSNP60 BeadChip. Loess regression provided a better fit to the real LD data, and more accurate LD predictions could be made, compared to nonlinear regression. It was also shown that Loess regression can be used to statistically compare the LD decay of different populations. The persistence of LD phase between crosses and the parental pig lines was found to be high, from which it was hypothesized that similar marker-QTL associations would be found in a cross and in their purebred parent populations and therefore accuracies of genomic prediction across these populations should be high. Between the pure lines the persistence of phase was low, thus higher density panels should be used to have the same marker-QTL associations across these lines. Accuracies obtained from across- and multi-population genomic prediction and from using crossbred data did however not follow the expectations based on LD. Having the same LD phase may therefore not be as important for genomic prediction accuracy as previously thought but rather the interplay between LD, genetic architecture and allele frequencies also plays a major role. Differences in allele frequencies between lines and information from GWAS on the genetic architecture of traits for the different lines were taken into account in analyses developed in the later chapters. The use of weights, based on GWAS results, was expected to lead the GBLUP model towards the real genetic architecture of the traits. This strategy was shown to have some benefit for the genomic predictions with single- and multi-population data sets. Weights obtained from GWAS in different data sets (within and combining populations) did not always lead to increased accuracies of prediction, depending on which lines the weights are applied to. Using weights from GWAS in a combined population was the best approach, resulting in higher accuracy of GBLUP predictions within single- as well as in multi-population analysis. Understanding and evaluating how the accuracy of within-, across- and multi-population genomic prediction is affected by differences in LD, in genetic architecture and in allele frequencies is key to optimize the accuracy of genomic prediction in pig breeding.
Liu-Cordero, Shau Neen 1970. "Patterns of linkage disequilibrium in the human genome." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/89344.
Full textIncludes bibliographical references.
Although enormous progress has occurred in the field of human genetics, the cloning of complex trait mutations remains a challenging and unresolved process. This continuing difficulty is responsible for an ever-increasing awareness of the phenomenon of linkage disequilibrium (LD). The principle behind LD is relatively simple. Over the lifetime of a population, the genetic markers that are adjacent to an ancestral mutation will recombine less often than more distant markers. Therefore, the ancestral alleles of the markers closest to the mutation should be most frequent in a collection of disease chromosomes. The allelic association should decrease as the distance from the ancestral disease mutation increases. This thesis is a collection of ideas and experiments aimed at dissecting the behavior of LD in the human genome. Specific studies examine LD in a variety of populations including isolated founder populations, as well as globally diverse population samples. A large number of regions throughout the genome are investigated using both pairwise comparisons of markers, as well as multimarker haplotypes. The X chromosome is more closely scrutinized because of its unique population history, as well as the advantages afforded to haplotyping due to hemizygosity of the X chromosome in males. Major conclusions include the observation that LD between pairs of markers is highly variable even at extremely close distances and multimarker haplotypes better serve to resolve the underlying haplotype structure of the genome.
(cont.) The genome appears to be structured as blocks of limited haplotype diversity that do not exhibit much internal recombination but which are separated by segments that show little or no LD. The lack of LD between haplotype blocks appears to be due to clustering of recombination events into specific hotspots. The size of the blocks and haplotype diversity varies slightly by population. In addition, the identity of the haplotypes varies between populations. The existence of 3-4 major haplotypes for specific regions in a diverse human population sample is a surprising finding that was originally believed to have only existed in very special isolated and young populations.
by Shau Neen Liu-Cordero.
Ph.D.
Li, Na. "Modeling and inference for linkage disequilibrium and recombination /." Thesis, Connect to this title online; UW restricted, 2003. http://hdl.handle.net/1773/9532.
Full textCummings, James Rowland Fraser. "Linkage Disequilibrium Mapping of Chromosome 19 on Crohn's Disease." Thesis, University of Oxford, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.531666.
Full textLawrence, Robert W. "Characterizing patterns of linkage disequilibrium in the human genome." Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.496992.
Full textHolloway, J. Kim. "Linkage disequilibrium and meiotic recombination in the human genome." Thesis, University of Leicester, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.426035.
Full textDale, Kuys Ruth. "Linkage disequilibrium in the South African abalone, Haliotis midae." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/97991.
Full textENGLISH ABSTRACT: Linkage disequilibrium (LD) is defined as the non-random association of alleles at two or more loci within a population. It is sensitive to a variety of locus-specific- and demographic factors, and can thus provide much insight into the micro-evolutionary factors that have shaped species of interest. It can also be exploited to identify the genomic regions determining complex traits of interest, which can then be applied as performance evaluation markers in marker-assisted selection (MAS). The South African abalone, Haliotis midae, supports a rapidly developing aquaculture production industry, in which genetic improvement potential is high. This species also represents an opportunistic model for studying the effects of early domestication in a shellfish species. The aim of this study was therefore to quantify and characterise levels of genome-wide LD within the South African abalone, and to demonstrate its utility within population genetic investigations and the characterisation of complex traits. Estimates of LD between 112 mapped microsatellite markers within wild and cultured H. midae revealed that levels of LD in abalone are high relative to other aquaculture species. This was attributed primarily to small effective population sizes produced by a combination of natural- and anthropogenic factors. The decay of LD with genetic distance was evident in both cultured cohorts, but almost absent in wild cohorts, likely reflecting the differences in size, age and sampling of wild populations relative to cultured. Putative evidence for the effects of recombination, selection, and epistasis were also evident in distinctive locus-specific patterns of LD on some of the linkage groups, many of which could represent the effects of domestication. The effects of selection associated with the domestication event were further investigated using a candidate locus LD mapping approach to determine the proportion of candidate loci under selection associated with artificial selection for faster growth rate in cultured abalone. Two loci (15%) were found to be significantly associated with differences in size of individual animals, both of which could be linked with genes potentially involved in growth and development. These markers could therefore find application in MAS programmes for abalone. Several promising candidates for natural selection were also identified based on similarity with known genes. As the latter represented the majority, natural selection, rather than artificial selection, appears to be predominant during the early stages of domestication in abalone. While some conclusions within the current study were speculative, both the direct and indirect applications of LD were clearly demonstrated. Linkage disequilibrium data can provide a unique perspective on many of the commonly used population genetic estimates, and is therefore of great value in population genetic investigations. Furthermore, these results also highlighted the effectiveness of the candidate locus approach in species with both limited molecular resources and extensive LD.
AFRIKAANSE OPSOMMING: Koppelingsonewewig (KO) word gedefinieer as die nie-lukrake assosiasie van allele by twee of meer lokusse binne 'n populasie. Koppelingsonewewig is sensitief vir 'n verskeidenheid van lokus-spesifieke- en demografiese faktore, en kan dus insiggewend wees m.b.t. mikro-evolusionêre faktore wat spesies van belang beïnvloed het. Dit kan ook benut word om die genoom-gebiede onderligend tot komplekse eienskappe te bespeur; wat dan aangewend kan word vir prestasie-evaluering m.b.v. merkerbemiddelde seleksie (MBS). Die Suid-Afrikaanse perlemoen, Haliotis midae, ondersteun 'n vinnig ontwikkelende akwakultuur produksie bedryf, waarin genetiese verbeteringspotensiaal hoog is. Hierdie spesie verteenwoordig ook 'n opportunistiese model vir die bestudering van die gevolge van vroeë domestiseering in 'n skulpvis spesie. Die doel van hierdie studie was dus om vlakke van genoom-wye KO binne die Suid-Afrikaanse perlemoen te kwantifiseer en te karakteriseer, en om die toepassing hiervan binne populasiegenetiese ondersoeke en die karakterisering van komplekse eienskappe te demonstreer. Ramings van KO tussen 112 gekarteerde mikrosatelliet-merkers binne wilde en gekultiveerde H. midae het aan die lig gebring dat die vlakke van KO in perlemoen hoog was, in vergelyking met ander akwakultuur spesies. Dit word hoofsaaklik toegeskryf aan klein effektiewe populasiegroottes wat deur 'n kombinasie van natuurlike- en antropogeniese faktore teweeg gebring word. Die verval van KO met genetiese afstand was duidelik waarneembaar in gekultiveerde kohorte, maar amper afwesig in die wilde kohorte, waarskynlik a.g.v. verskille in populasiegrootte, ouderdom, en streekproef-neemings metodieke van die verskeie populasies. Vermeende bewyse vir die gevolge van rekombinasie, seleksie en epistase kon ook gesien word a.g.v. lokus-spesifieke patrone van KO op sommige van die koppelingsgroepe, moontlik ‘n gevolg van domestisering. Die gevolge van seleksie wat verband hou met die domestiseringsgebeurtenis is verder ondersoek m.b.v 'n kandidaat-lokus KO karteringsbenadering om die verhouding van kandidaat lokusse wat geassosieer is met kunsmatige seleksie (vir vinniger groeikoers in perlemoen) te bepaal. Twee lokusse (15%) was beduidend geassosieer met verskille in grootte tussen individuele diere. Beide van die lokusse was gekoppel met gene wat potensieel betrokke is by groei en ontwikkeling. Hierdie merkers kan dus moontlik aangewend word in MBS programme vir perlemoen. Verskeie belowende kandidaat lokusse vir natuurlike seleksie is ook geïdentifiseer gebaseer op ooreenkoms met bekende gene. Gegewe dat die laasgenoemde die meerderheid van die merkers verteenwoordig, kan daar afgelei word dat natuurlike seleksie, eerder as kunsmatige seleksie, oorheersend is in die vroeë stadia van domestisering in perlemoen. Terwyl sommige gevolgtrekkings binne die huidige studie spekulatief was, is beide die direkte en indirekte toepassings van KO duidelik gedemonstreer. Koppelingsonewewig-data kan 'n unieke perspektief gee op baie van die algemeen gebruikte populasie genetiese skattings, en is dus van groot waarde in populasie genetiese ondersoeke. Verder demonstreer hierdie resultate ook die doeltreffendheid van die kandidaat lokus benadering in spesies met beide beperkte molekulêre hulpbronne en uitgebreide KO.
Sjölander, Anders. "Exploring linkage disequilibrium to date admixture using ancient DNA." Thesis, Uppsala universitet, Växtekologi och evolution, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-298198.
Full textWebb, Adam J. "Meiotic recombination and linkage disequilibrium in the human genome." Thesis, University of Leicester, 2006. http://hdl.handle.net/2381/30369.
Full textBooks on the topic "Linkage disequilibrium"
Andrew, Collins R. Linkage Disequilibrium and Association Mapping. New Jersey: Humana Press, 2007. http://dx.doi.org/10.1385/1597453897.
Full textCollins, Andrew R., ed. Linkage Disequilibrium and Association Mapping. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-389-9.
Full textCollins, Andrew R. Linkage Disequilibrium and Association Mapping. Gardners Books, 2010.
Find full textA, Collins, ed. Linkage disequilibrium and association mapping: Analysis and applications. Totowa, N.J: Humana Press, 2007.
Find full textLinkage disequilibrium and association mapping: Analysis and applications. Totowa, NJ: Humana Press, 2008.
Find full textXie, Fang. Simultaneous detection of linkage and linkage disequilibrium for families with an affected sib-pair. 2003.
Find full textCollins, Andrew R. Linkage Disequilibrium and Association Mapping: Analysis and Applications (Methods in Molecular Biology). Humana Press, 2007.
Find full textWalsh, Bruce, and Michael Lynch. Short-term Changes in the Variance: 1. Changes in the Additive Variance. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0016.
Full textWalsh, Bruce, and Michael Lynch. Selection Under Inbreeding. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0023.
Full textWalsh, Bruce, and Michael Lynch. Analysis of Short-term Selection Experiments: 2. Mixed-model and Bayesian Approaches. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198830870.003.0019.
Full textBook chapters on the topic "Linkage disequilibrium"
Oraguzie, Nnadozie C., Phillip L. Wilcox, Erik H. A. Rikkerink, and H. Nihal de Silva. "Linkage Disequilibrium." In Association Mapping in Plants, 11–39. New York, NY: Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-36011-9_2.
Full textEarp, Madalene A., and Ellen L. Goode. "Linkage Disequilibrium." In Encyclopedia of Cancer, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-27841-9_3368-3.
Full textEarp, Madalene A., and Ellen L. Goode. "Linkage Disequilibrium." In Encyclopedia of Cancer, 2496–502. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-46875-3_3368.
Full textGoode, Ellen L. "Linkage Disequilibrium." In Encyclopedia of Cancer, 2043–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-16483-5_3368.
Full textSlatkin, Montgomery. "Linkage Disequilibrium." In Human Population Genomics, 31–45. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-61646-5_2.
Full textMukhopadhyay, Amrita. "Linkage Disequilibrium." In Encyclopedia of Sexual Psychology and Behavior, 1–5. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-08956-5_1340-1.
Full textde Silva, H. Nihal, and Roderick D. Ball. "Linkage Disequilibrium Mapping Concepts." In Association Mapping in Plants, 103–32. New York, NY: Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-36011-9_7.
Full textCollins, Andrew R. "Linkage Disequilibrium and Association Mapping." In Linkage Disequilibrium and Association Mapping, 1–15. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-389-9_1.
Full textMcVean, G. "Linkage Disequilibrium, Recombination and Selection." In Handbook of Statistical Genetics, 909–44. Chichester, UK: John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch27.
Full textShugart, Yin Yao, Lina Chen, Rui Li, and Terri Beaty. "Family-Based Linkage Disequilibrium Tests Using General Pedigrees." In Linkage Disequilibrium and Association Mapping, 141–49. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-389-9_10.
Full textConference papers on the topic "Linkage disequilibrium"
Alachiotis, Nikolaos, and Gabriel Weisz. "High Performance Linkage Disequilibrium." In FPGA'16: The 2016 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2847263.2847271.
Full textAo, S. I., Sio-Iong Ao, Mahyar A. Amouzegar, and Su-Shing Chen. "Constructing Linkage Disequilibrium Map with Iterative Approach." In WORLD CONGRESS ON ENGINEERING AND COMPUTER SCIENCE. AIP, 2008. http://dx.doi.org/10.1063/1.2937607.
Full textLu, Jun, Jun Li, Ruiqing Jing, Qiong Wang, Cheng Chang, and Jiaxing Guo. "Research on Linkage Disequilibrium Method Based on OpenMP." In 2016 3rd International Conference on Information Science and Control Engineering (ICISCE). IEEE, 2016. http://dx.doi.org/10.1109/icisce.2016.230.
Full textYeo, Sang-Soo, and Sung Kwon Kim. "MarSelHR: A Haplotype Reconstruction System Using Linkage Disequilibrium." In 2007 Frontiers in the Convergence of Bioscience and Information Technologies. IEEE, 2007. http://dx.doi.org/10.1109/fbit.2007.142.
Full textCOLLINS, A. "LINKAGE DISEQUILIBRIUM MAPPING USING SINGLE NUCLEOTIDE POLYMORPHISMS -WHICH POPULATION?" In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 1999. http://dx.doi.org/10.1142/9789814447331_0063.
Full textIbrahim, Zina M., Stephen Newhouse, and Richard Dobson. "Detecting epistasis in the presence of linkage disequilibrium: A focused comparison." In 2013 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2013. http://dx.doi.org/10.1109/cibcb.2013.6595394.
Full textTheodoris, Charalampos, Nikolaos Alachiotis, Tze Meng Low, and Pavlos Pavlidis. "qLD: High-performance Computation of Linkage Disequilibrium on CPU and GPU." In 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE). IEEE, 2020. http://dx.doi.org/10.1109/bibe50027.2020.00019.
Full textRANNALA, B., and J. P. REEVE. "JOINT BAYESIAN ESTIMATION OF MUTATION LOCATION AND AGE USING LINKAGE DISEQUILIBRIUM." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812776303_0049.
Full textHernández-Lemus, Enrique, Jesús K. Estrada-Gil, Irma Silva-Zolezzi, J. Carlos Fernández-López, Alfredo Hidalgo-Miranda, Gerardo Jiménez-Sánchez, Leonardo Dagdug, and Leopoldo Gracía-Colin S. "Nonlinear Analysis of Time Series in Genome-Wide Linkage Disequilibrium Data." In COMPLIFE 2007: The Third International Symposium on Computational Life Science. AIP, 2008. http://dx.doi.org/10.1063/1.2891412.
Full textZHANG, SHUANGLIN, KUI ZHANG, JINMING LI, and HONGYU ZHAO. "ON A FAMILY-BASED HAPLOTYPE PATTERN MINING METHOD FOR LINKAGE DISEQUILIBRIUM MAPPING." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812799623_0010.
Full textReports on the topic "Linkage disequilibrium"
Sun, Xiaochen, Rohan L. Fernando, Dorian J. Garrick, and Jack C. M. Dekkers. Genomic Prediction Using Linkage Disequilibrium and Co-segregation. Ames (Iowa): Iowa State University, January 2013. http://dx.doi.org/10.31274/ans_air-180814-1253.
Full textMedrano, Juan, Adam Friedmann, Moshe (Morris) Soller, Ehud Lipkin, and Abraham Korol. High resolution linkage disequilibrium mapping of QTL affecting milk production traits in Israel Holstein dairy cattle. United States Department of Agriculture, March 2008. http://dx.doi.org/10.32747/2008.7696509.bard.
Full textSela, Hanan, Eduard Akhunov, and Brian J. Steffenson. Population genomics, linkage disequilibrium and association mapping of stripe rust resistance genes in wild emmer wheat, Triticum turgidum ssp. dicoccoides. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598170.bard.
Full textFoulkes, William D. Locating a Prostate Cancer Susceptibility Gene on the X Chromosome by Linkage Disequilibrium Mapping Using Three Founder Populationin Quebec and Switzerland. Fort Belvoir, VA: Defense Technical Information Center, March 2004. http://dx.doi.org/10.21236/ada426100.
Full textFoulkee, William D. Locating a Prostate Cancer Susceptibility Gene on the X Chromosome by Linkage Disequilibrium Mapping Using Three Founder Populations in Quebec and Switzerland. Fort Belvoir, VA: Defense Technical Information Center, March 2005. http://dx.doi.org/10.21236/ada443199.
Full textFoulkes, William D. Locating a Prostate Cancer Susceptibility Gene on the X Chromosome by Linkage Disequilibrium Mapping Using Three Founder Populations in Quebec and Switzerland. Fort Belvoir, VA: Defense Technical Information Center, March 2002. http://dx.doi.org/10.21236/ada405914.
Full textFoulkes, William D. Locating a Prostate Cancer Susceptibility Gene on the X Chromosome by Linkage Disequilibrium Mapping Using Three Founder Populations in Quebec and Switzerland. Fort Belvoir, VA: Defense Technical Information Center, March 2003. http://dx.doi.org/10.21236/ada415657.
Full textBeach, Erin, Behnam Abasht, Rohan L. Fernando, Jack C. M. Dekkers, Susan J. Lamont, Jesus Arango, Petek Settar, Janet Fulton, and Neil P. O'Sullivan. Extent and Consistency of Linkage Disequilibrium and Identification of DNA Markers for Production and Egg Quality Traits in Commercial Layer Chicken Populations. Ames (Iowa): Iowa State University, January 2009. http://dx.doi.org/10.31274/ans_air-180814-817.
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