Haploview: analysis and visualization of LD and haplotype maps. Research over the last few years has revealed significant haplotype structure in the human genome. The characterization of these patterns, particularly in the context of medical genetic association studies, is becoming a routine research activity. Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface.

References in zbMATH (referenced in 22 articles )

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  1. Kong, Dehan; An, Baiguo; Zhang, Jingwen; Zhu, Hongtu: L2RM: low-rank linear regression models for high-dimensional matrix responses (2020)
  2. Stephen Turner: qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots (2018) not zbMATH
  3. Teng, Yanbo; Ding, Yanjun; Zhang, Mingming; Chen, Xinren; Wang, Xizi; Yu, Hang; Liu, Chonghui; Lv, Hongchao; Zhang, Ruijie: Genome-wide haplotype association study identifies risk genes for non-small cell lung cancer (2018)
  4. Malov, Sergey V.; Antonik, Alexey; Tang, Minzhong; Berred, Alexandre; Zeng, Yi; O’Brien, Stephen J.: Signal localization: a new approach in signal discovery (2017)
  5. Wang, Charlotte; Ruggeri, Fabrizio; Hsiao, Chuhsing K.; Argiento, Raffaele: Bayesian nonparametric clustering and association studies for candidate SNP observations (2017)
  6. Zhang, Le; Zheng, Chunqiu; Li, Tian; Xing, Lei; Zeng, Han; Li, Tingting; Yang, Huan; Cao, Jia; Chen, Badong; Zhou, Ziyuan: Building up a robust risk mathematical platform to predict colorectal cancer (2017)
  7. Zhang, Yuan; Lin, Shili; Biswas, Swati: Detecting rare and common haplotype-environment interaction under uncertainty of gene-environment independence assumption (2017)
  8. Briollais, Laurent; Dobra, Adrian; Liu, Jinnan; Friedlander, Matt; Ozcelik, Hilmi; Massam, Hélène: A Bayesian graphical model for genome-wide association studies (GWAS) (2016)
  9. Sun, M.; Jobling, M. A.; Taliun, D.; Pramstaller, P. P.; Egeland, T.; Sheehan, N. A.: On the use of dense SNP marker data for the identification of distant relative pairs (2016)
  10. Manitz, Juliane: Statistical inference for propagation processes on complex networks (2014)
  11. Liu, Jia-Rou; Kuo, Po-Hsiu; Hung, Hung: A robust rerank approach for feature selection and its application to pooling-based GWA studies (2013)
  12. Marttinen, Pekka; Gillberg, Jussi; Havulinna, Aki; Corander, Jukka; Kaski, Samuel: Genome-wide association studies with high-dimensional phenotypes (2013)
  13. Han, Fang; Pan, Wei: A composite likelihood approach to latent multivariate Gaussian modeling of SNP data with application to genetic association testing (2012)
  14. Tomita, Makoto; Hashimoto, Noboru; Tanaka, Yutaka: Association study for the relationship between a haplotype or haplotype set and multiple quantitative responses (2011)
  15. Zhang, Yu; Zhang, Jing; Liu, Jun S.: Block-based Bayesian epistasis association mapping with application to WTCCC type 1 diabetes data (2011)
  16. Frommlet, Florian: Tag SNP selection based on clustering according to dominant sets found using replicator dynamics (2010)
  17. Bingham, Ella; Mannila, Heikki: Complexity control in a mixture model by the Hardy-Weinberg equilibrium (2009)
  18. Dai, James Y.; Leblanc, Michael; Smith, Nicholas L.; Psaty, Bruce; Kooperberg, Charles: SHARE: an adaptive algorithm to select the most informative set of SNPs for candidate genetic association (2009)
  19. Katanforoush, Ali; Sadeghi, Mehdi; Pezeshk, Hamid; Elahi, Elahe: Global haplotype partitioning for maximal associated SNP pairs (2009) ioport
  20. Li, Jing; Chen, Yixuan: Generating samples for association studies based on hapmap data (2008) ioport

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