Detecting and measuring selection from gene frequency data

Genetics

Volumn 196, Issue 3, 2014, Pages 799-817

  Vitalis, Renaud ^a,b   Gautier, Mathieu ^a,b   Dawson, Kevin J ^c   Beaumont, Mark A ^d  

^a CIRAD   (France)

^b LIRMM   (France)

^c WELLCOME TRUST SANGER INSTITUTE   (United Kingdom)

^d UNIVERSITY OF BRISTOL   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

GLYCOSYLCERAMIDASE;

ARTICLE; BACKGROUND SELECTION; BALANCING SELECTION; BAYES THEOREM; CONTROLLED STUDY; DIPLOIDY; EUROPE; GENE; GENE FREQUENCY; GENE LOCUS; GENETIC ASSOCIATION; GENETIC MODEL; GENOTYPE; GEOGRAPHIC DISTRIBUTION; HIGH THROUGHPUT SEQUENCING; HUMAN; HUMAN GENOME; LACTASE DEFICIENCY; LCT GENE; MAJOR CLINICAL STUDY; MONTE CARLO METHOD; PHENOTYPE; PRIORITY JOURNAL; PROBABILITY; RECEIVER OPERATING CHARACTERISTIC; SELESTIM METHOD; SIMULATION; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL ANALYSIS; STOCHASTIC MODEL;

ADAPTATION; GENOME SCAN; HIERARCHICAL BAYESIAN MODEL; NATURAL SELECTION; POPULATION DIFFERENTIATION;

ALGORITHMS; BAYES THEOREM; CELL LINE; GENE FREQUENCY; GENETIC VARIATION; GENOME, HUMAN; GENOMICS; HUMANS; LACTASE-PHLORIZIN HYDROLASE; MARKOV CHAINS; POLYMORPHISM, SINGLE NUCLEOTIDE; POPULATION GROUPS; SELECTION, GENETIC;

EID: 84901350323     PISSN: 00166731     EISSN: 19432631     Source Type: Journal    
DOI: 10.1534/genetics.113.152991     Document Type: Article

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