Cargando…
On modeling locus heterogeneity using mixture distributions
BACKGROUND: Locus heterogeneity poses a major difficulty in mapping genes that influence complex genetic traits. A widely used approach to deal with this problem involves modeling linkage data in terms of finite mixture distributions. In its simplest setup, also known as the admixture approach, a si...
Autores principales: | Lin, Shili, Biswas, Swati |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2004
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC524512/ https://www.ncbi.nlm.nih.gov/pubmed/15458576 http://dx.doi.org/10.1186/1471-2156-5-29 |
Ejemplares similares
-
A new Bayesian approach incorporating covariate information for heterogeneity and its comparison with HLOD
por: Biswas, Swati, et al.
Publicado: (2005) -
Multiplicative Decomposition of Heterogeneity in Mixtures of Continuous Distributions
por: Nunes, Abraham, et al.
Publicado: (2020) -
A Mixture Modeling Framework for Differential Analysis of High-Throughput Data
por: Taslim, Cenny, et al.
Publicado: (2014) -
Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions
por: Tokuda, Tomoki, et al.
Publicado: (2017) -
Integrative genome-wide chromatin signature analysis using finite mixture models
por: Taslim, Cenny, et al.
Publicado: (2012)