Cargando…
An Eigenvalue test for spatial principal component analysis
BACKGROUND: The spatial Principal Component Analysis (sPCA, Jombart (Heredity 101:92-103, 2008) is designed to investigate non-random spatial distributions of genetic variation. Unfortunately, the associated tests used for assessing the existence of spatial patterns (global and local test; (Heredity...
Autores principales: | Montano, V., Jombart, T. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5732370/ https://www.ncbi.nlm.nih.gov/pubmed/29246102 http://dx.doi.org/10.1186/s12859-017-1988-y |
Ejemplares similares
-
Discriminant analysis of principal components: a new method for the analysis of genetically structured populations
por: Jombart, Thibaut, et al.
Publicado: (2010) -
Principal component gene set enrichment (PCGSE)
por: Frost, H. Robert, et al.
Publicado: (2015) -
Probabilistic principal component analysis for metabolomic data
por: Nyamundanda, Gift, et al.
Publicado: (2010) -
Ancestry inference using principal component analysis and spatial analysis: a distance-based analysis to account for population substructure
por: Byun, Jinyoung, et al.
Publicado: (2017) -
Testing association and maternally mediated genetic effects with the principal component analysis in case-parents studies
por: Li, Yumei, et al.
Publicado: (2016)