SciELO - Scientific Electronic Library Online

 
vol.30 número1El impacto de la genética molecular en el mejoramiento genético vegetal: realidades y perspectivasDiversidad genotípica de 291 líneas de maíz de CIMMYT y caracterización fenotípica en el sur de Córdoba, Argentina índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

  • No hay articulos citadosCitado por SciELO

Links relacionados

Compartir


BAG. Journal of basic and applied genetics

versión On-line ISSN 1852-6233

Resumen

BRUNO, C; VIDELA, M.E  y  BALZARINI, M. Test of interaction in the analysis of molecular variance. BAG, J. basic appl. genet. [online]. 2019, vol.30, n.1, pp.17-23. ISSN 1852-6233.

The genomic diversity, expressed in the differences between molecular haplotypes of a group of individuals, can be divided into components of variability between and within some factor of classification of the individuals. For such variance partitioning, molecular analysis of variance (AMOVA) is used, which is constructed from the multivariate distances between pairs of haplotypes. The classical AMOVA allows the evaluation of the statistical significance of two or more hierarchical factors and consequently there is no interaction test between factors. However, there are situations where the factors that classify individuals are crossed rather than nested, that is, all the levels of a factor are represented in each level of the other one. This paper proposes a statistical test to evaluate the interaction between crossed factors in a Non-Hierarchical AMOVA. The null hypothesis of interaction establishes that the molecular differences between individuals of different levels of a factor are the same for all the levels of the other factor that classifies them. The proposed analysis of interaction in a Non- Hierarchical AMOVA includes: calculation of the distance matrix and partition of it into blocks, subsequent calculation of residuals and analysis of non-parametric variance on the residuals. Its implementation is illustrated in simulated and real scenarios. The results suggest that the proposed interaction test for the Non-Hierarchical AMOVA presents high power.

Palabras clave : Genetic variability; Non-parametric methods; Distances matrix; AMOVA.

        · resumen en Español     · texto en Español     · Español ( pdf )

 

Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons