PLINK is a free, open-source whole genome association analysis toolset, designed to perform a range of basic, large-scale analyses in a computationally efficient manner. The focus of PLINK is purely on analysis of genotype/phenotype data, so there is no support for steps prior to this (e.g. study design and planning, generating genotype or CNV calls from raw data). Through integration with gPLINK and Haploview, there is some support for the subsequent visualization, annotation and storage of results.

References in zbMATH (referenced in 24 articles )

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  1. Anderson, Eric C.; Ng, Thomas C.: Bayesian pedigree inference with small numbers of single nucleotide polymorphisms via a factor-graph representation (2016)
  2. Briollais, Laurent; Dobra, Adrian; Liu, Jinnan; Friedlander, Matt; Ozcelik, Hilmi; Massam, Hélène: A Bayesian graphical model for genome-wide association studies (GWAS) (2016)
  3. Gazal, Steven; Génin, Emmanuelle; Leutenegger, Anne-Louise: Relationship inference from the genetic data on parents or offspring: a comparative study (2016)
  4. Mikhchi, Abbas; Honarvar, Mahmood; Kashan, Nasser Emam Jomeh; Aminafshar, Mehdi: Assessing and comparison of different machine learning methods in parent-offspring trios for genotype imputation (2016)
  5. Stange, Jens; Dickhaus, Thorsten; Navarro, Arcadi; Schunk, Daniel: Multiplicity- and dependency-adjusted $p$-values for control of the family-wise error rate (2016)
  6. Thompson, Katherine L.; Linnen, Catherine R.; Kubatko, Laura: Tree-based quantitative trait mapping in the presence of external covariates (2016)
  7. Carmi, Shai; Wilton, Peter R.; Wakeley, John; Pe’er, Itsik: A renewal theory approach to IBD sharing (2014)
  8. Bryc, Katarzyna; Bryc, Wlodek; Silverstein, Jack W.: Separation of the largest eigenvalues in eigenanalysis of genotype data from discrete subpopulations (2013)
  9. Crossett, Andrew; Lee, Ann B.; Klei, Lambertus; Devlin, Bernie; Roeder, Kathryn: Refining genetically inferred relationships using treelet covariance smoothing (2013)
  10. Liu, Jia-Rou; Kuo, Po-Hsiu; Hung, Hung: A robust rerank approach for feature selection and its application to pooling-based GWA studies (2013)
  11. Zhao, Jing Hua; Luan, Jian’an: Mixed modeling with whole genome data (2012)
  12. Ashcroft, Michael: Does science influence the logic we ought to use: A reflection on the quantum logic controversy (2010)
  13. Garson, James W.: Expressive power and incompleteness of propositional logics (2010)
  14. Lee, Seunggeun; Zou, Fei; Wright, Fred A.: Convergence and prediction of principal component scores in high-dimensional settings (2010)
  15. Ertola, Rodolfo: On univocal connectives (2009)
  16. Foulkes, Andrea S.: Applied statistical genetics with R. For population-based association studies (2009)
  17. Peregrin, Jaroslav: What is the logic of inference? (2008)
  18. Wansing, Heinrich: Connectives stranger than tonk (2006)
  19. Cook, Roy T.: What’s wrong with tonk(?) (2005)
  20. Humberstone, Lloyd: The pleasures of anticipation: Enriching intuitionistic logic (2001)

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