An approximate bayesian computation approach to overcome biases that arise when using amplified fragment length polymorphism markers to study population structure

Genetics

Volumn 179, Issue 2, 2008, Pages 927-939

  Foll, Matthieu ^a,c   Beaumont, Mark A ^b   Gaggiotti, Oscar ^a  

^a CNRS   (France)

^b UNIVERSITY OF READING   (United Kingdom)

^c Zoology Institute ^*  (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

AMPLIFIED FRAGMENT LENGTH POLYMORPHISM; ARTICLE; BAYES THEOREM; BINOMIAL DISTRIBUTION; GENE FREQUENCY; GENETIC EPIDEMIOLOGY; GENETIC LINKAGE; GENETIC MARKER; GENETIC VARIABILITY; MUTATION RATE; PHENOTYPE; POPULATION GENETIC STRUCTURE; POPULATION STRUCTURE; PRIORITY JOURNAL; QUANTITATIVE TRAIT LOCUS; SYSTEMATIC ERROR; ALGORITHM; BIOLOGICAL MODEL; BIOMETRY; COMPUTER PROGRAM; EPIDEMIOLOGY; POPULATION GENETICS; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; STATISTICS;

ALGORITHMS; AMPLIFIED FRAGMENT LENGTH POLYMORPHISM ANALYSIS; BAYES THEOREM; BIAS (EPIDEMIOLOGY); BIOMETRY; GENETIC MARKERS; GENETICS, POPULATION; MODELS, GENETIC; MODELS, STATISTICAL; SENSITIVITY AND SPECIFICITY; SOFTWARE;

EID: 49849094302     PISSN: 00166731     EISSN: 00166731     Source Type: Journal    
DOI: 10.1534/genetics.107.084541     Document Type: Article

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