An Eigenvalue test for spatial principal component analysis

An Eigenvalue test for spatial principal component analysis

Abstract 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; (...

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Bibliographic Details
Main Authors: V. Montano, T. Jombart
Format: Article
Language:English
Published: BMC 2017-12-01
Series:BMC Bioinformatics
Subjects:
Eigenvalues
sPCA
Spatial genetic patterns
Monte-Carlo
Online Access:http://link.springer.com/article/10.1186/s12859-017-1988-y

Internet

http://link.springer.com/article/10.1186/s12859-017-1988-y

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