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The Bayesian revolution in genetics

Beaumont, M. A. and Rannala, B. (2004) The Bayesian revolution in genetics. Nature Reviews Genetics, 5 (4). pp. 251-261. ISSN 1471-0056

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To link to this item DOI: 10.1038/nrg1318

Abstract/Summary

Bayesian statistics allow scientists to easily incorporate prior knowledge into their data analysis. Nonetheless, the sheer amount of computational power that is required for Bayesian statistical analyses has previously limited their use in genetics. These computational constraints have now largely been overcome and the underlying advantages of Bayesian approaches are putting them at the forefront of genetic data analysis in an increasing number of areas.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Life Sciences > School of Biological Sciences
ID Code:10429
Uncontrolled Keywords:SINGLE-NUCLEOTIDE POLYMORPHISMS, MAXIMUM-LIKELIHOOD-ESTIMATION, LOCAL, SEQUENCE ALIGNMENT, CHAIN MONTE-CARLO, LINKAGE-DISEQUILIBRIUM, POPULATION-GROWTH, DNA-SEQUENCES, MARKOV-CHAIN, HUMAN GENOME, MICROSATELLITE ANALYSIS

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