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Published byKallie Nutt Modified over 2 years ago

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SPAGeDi a program for Spatial Pattern Analysis of Genetic Diversity by Olivier J. Hardy and Xavier Vekemans SPAGeDi a program for Spatial Pattern Analysis of Genetic Diversity by Olivier J. Hardy and Xavier Vekemans Goal: characterise spatial genetic structure of mapped individuals or populations using genotype data of any ploidy level Compute: - inbreeding coef - pairwise relatedness/differentiation coef between indiv/pop averages / distance classes association with distance (regression with lin/log distance) ( isolation by distance, neighbourhood size estimates) - actual variance of relatedness coef Ritland’s approach for marker based estimate of h 2 Tests: - permutations (of genes, individuals, or spatial locations) - jackknife over loci ( SE for multilocus estimates) Option: - restricted analysis within or among categories of ind/pop

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Input data Input file with : - format #’s (#ind, #categ, #spat coord, #loci, #digits/allele, ploidy) - distance intervals - for each ind : - name - category (facultative) - spatial coordinates - genotype at each locus Analyses defined on keyboard while running the program : - indiv vs pop level - stat to compute (+ within/among categ) - tests, …

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2-genes coef : - "kinship" coef (Loiselle 1995; Ritland 1996) - "relationship" coef (Moran’s I; Lynch & Ritland 1999; Wang 2002) - kinship type coef based on allele size (Streiff et al. 1999) - a r distance measure (Rousset 2000) 4-genes coef : - "fraternity" coef (Lynch & Ritland 1999; Wang 2002) Statistics computed: "relatedness" coef at the individual level also for dominant marker (Hardy 2003)

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Estimates of the actual variance of pairwise kinship coef in natural populations

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Consistency among kinship coef estimators

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Reliable estimates of the actual variance of pairwise relatedness require - large data set (300 – 1000 individuals) - very polymorphic markers and/or many loci SSR AFLP ???

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