@article {Beasley:2005:1175-2203:197,
	author = "Beasley, T. Mark",
	author = "Holt, Janet K.",
	author = "Allison, David B.",
	title = "Comparison of Linear Weighting Schemes for Perfect Match and Mismatch Gene Expression Levels from Microarray Data",
	journal = "American Journal of PharmacoGenomics",
	volume = "5",
	year = "2005",
	abstract = "<B>Background:</B> Data analytic approaches to Affymetrix<SUP>&#174;</SUP> microarray data include: (a) a covariate model, in which the observed signal is some estimated linear function of perfect match (PM) and mismatch (MM) signals; (b) a difference model [PM-MM]; and (c) a PM-only model, in which MM data is not utilized.<P></P><B>Methods:</B> By decomposing the correlations among the variables in the statistical model and making certain assumptions, we theoretically derive the statistical model that reflects the actual gene expression level under a variety of conditions expected in microarray data.<P></P><B>Results and conclusion:</B> When modeling non-systematic variation, the covariate model provides maximum flexibility and often reflects the actual gene expression levels better than the difference model. However, the PM-only model demonstrates superior power in an overwhelming majority of realistic situations, which provides theoretical support for the current trend to employ PM-only models in microarray data analyzes.",
	pages = "197-205(9)",
	url = "http://www.ingentaconnect.com/content/adis/apg/2005/00000005/00000003/art00006"
}