Title: On quality control standards to evaluate microarray studies

Authors: Justin R. Chimka, Jing Wu, Qin Hong

Addresses: Department of Industrial Engineering, University of Arkansas, 4207 Bell Engineering Centre, 800 W Dickson St., Fayetteville, AR 72701, USA. ' Department of Industrial Engineering, University of Arkansas, 4207 Bell Engineering Centre, 800 W Dickson St., Fayetteville, AR 72701, USA. ' Department of Industrial Engineering, University of Arkansas, 4207 Bell Engineering Centre, 800 W Dickson St., Fayetteville, AR 72701, USA

Abstract: We describe an effort to establish parameter thresholds for evaluation of gene expression data by imagining a multidimensional definition of quality that is subsequently used to assess classification errors associated with simple models of spot quality. Methods are dominated by K-means clustering and logistic regression. Results suggest that a consistent and objective definition of quality can be found, and statistical models of spot quality can be efficient and useful.

Keywords: K-means clustering; gene expression; logistic regression; microarrays; quality control; bioinformatics; microarray data; classification errors; statistical modelling; spot quality; data evaluation.

DOI: 10.1504/IJQET.2011.038721

International Journal of Quality Engineering and Technology, 2011 Vol.2 No.1, pp.45 - 53

Published online: 24 Feb 2011 *

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