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Two-stage clustering in genotype-by-environment analyses with missing data

Published online by Cambridge University Press:  15 October 2002

A. J. R. GODFREY
Affiliation:
Institute of Information Sciences and Technology, Massey University, Palmerston North, New Zealand
G. R. WOOD
Affiliation:
Institute of Information Sciences and Technology, Massey University, Palmerston North, New Zealand
S. GANESALINGAM
Affiliation:
Institute of Information Sciences and Technology, Massey University, Palmerston North, New Zealand
M. A. NICHOLS
Affiliation:
Institute of Natural Resources, Massey University, Palmerston North, New Zealand
C. G. QIAO
Affiliation:
Institute of Information Sciences and Technology, Massey University, Palmerston North, New Zealand

Abstract

Cluster analysis has been commonly used in genotype-by-environment (G×E) analyses, but current methods are inadequate when the data matrix is incomplete. This paper proposes a new method, referred to as two-stage clustering, which relies on a partitioning of squared Euclidean distance into two independent components, the G×E interaction and the genotype main effect. These components are used in the first and second stages of clustering respectively. Two-stage clustering forms the basis for imputing missing values in the G×E matrix, so that a more complete data array is available for other G×E analyses. Imputation for a given genotype uses information from genotypes with similar interaction profiles. This imputation method is shown to improve on an existing nearest cluster method that confounds the G×E interaction and the genotype main effect.

Type
Research Article
Copyright
© 2002 Cambridge University Press

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