Literature DB >> 12886284

On methods of spatial analysis for genotyped individuals.

K Shimatani1, M Takahashi.   

Abstract

Spatial autocorrelation methods have commonly been applied to individual-based spatial genetic studies, although their properties and the relations among the statistics have not been carefully examined. This paper first introduces a reformulation of widely used spatial statistics using point processes. When Moran's I statistics are applied to allele frequencies within an individual, the frequencies are no longer continuous variables but have only three discrete values and specific interpretations of Moran's I statistics and the number of alleles in common (NAC) can be expressed as the weighted sum of join-count statistics. The distributions of minor genotypes are amplified in Moran's I depending on the allele frequency in the population, while NAC uses a constant weighting system. Under the point process framework, spatial analysis can be conducted on the common theoretical base, from individual locations to genetic distributions of different levels, (for example, genotype and allele). The methodology is demonstrated by application to field data for molecular ecological studies of Fagus crenata population dynamics.

Entities:  

Mesh:

Year:  2003        PMID: 12886284     DOI: 10.1038/sj.hdy.6800295

Source DB:  PubMed          Journal:  Heredity (Edinb)        ISSN: 0018-067X            Impact factor:   3.821


  3 in total

1.  On the choice of genetic distance in spatial-genetic studies.

Authors:  Paul Fearnhead
Journal:  Genetics       Date:  2007-07-29       Impact factor: 4.562

2.  Development of a local size hierarchy causes regular spacing of trees in an even-aged Abies forest: analyses using spatial autocorrelation and the mark correlation function.

Authors:  Satoshi N Suzuki; Naoki Kachi; Jun-Ichirou Suzuki
Journal:  Ann Bot       Date:  2008-07-03       Impact factor: 4.357

3.  Ecological connectivity assessment in a strongly structured fire salamander (Salamandra salamandra) population.

Authors:  Luciano Bani; Giulia Pisa; Massimiliano Luppi; Giulia Spilotros; Elena Fabbri; Ettore Randi; Valerio Orioli
Journal:  Ecol Evol       Date:  2015-07-27       Impact factor: 2.912

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.