Busca por estruturas causais no contexto de modelos mistos em genética quantitativa
AUTOR(ES)
Bruno Dourado Valente
DATA DE PUBLICAÇÃO
2010
RESUMO
Structural Equation Models (SEM) can be used to study recursive and simultaneous relationships in multivariate analyses. Nonetheless, the number of different recursive causal structures that can be used for fitting a SEM to multivariate data can be huge, even when only a few traits are considered. In recent applications of SEM in mixed model quantitative genetics settings, causal structures were preselected based on prior biological knowledge alone. Therefore, the wide range of possible causal structures has not been properly explored. Alternatively, causal structure spaces can be explored using algorithms which, using data driven evidence, can search for structures that are compatible with the joint distribution of the variables under study. However, the search cannot be performed directly on the joint distribution of the phenotypes as it is possibly confounded by genetic covariance among traits. In this thesis, we propose to search for recursive causal structures among phenotypes using the IC algorithm after adjusting the data for genetic effects. A standard multiple trait model is fitted to obtain a posterior covariance matrix of phenotypes conditional to unobservable additive genetic effects, which is then used as input for the IC algorithm.
ASSUNTO(S)
equações teses. genética animal teses. genética quantitativa teses analise multivariada teses.
ACESSO AO ARTIGO
http://hdl.handle.net/1843/BUBD-8B4E7XDocumentos Relacionados
- Diversidade genética em genótipos de Cedro Australiano selecionados via modelos mistos
- Estruturas causais
- Efeitos fixos ou aleatórios de repetições no contexto dos modelos mistos no melhoramento de plantas perenes.
- Simulação de modelos mistos no delineamento em blocos aumentado
- Variabilidade genética e seleção de progênies de pupunheira via modelos mistos (REML/BLUP)