1. 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 h2
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

2. 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, …

3. Statistics computed: "relatedness" coef at the individual level
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)
- ar distance measure
(Rousset 2000)
4-genes coef :
- "fraternity" coef
(Lynch & Ritland 1999; Wang 2002)
also for dominant marker
(Hardy 2003)

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

8. Consistency among kinship coef estimators

9. 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 ???