A Two-Way Semi-Linear Model for Normalization and Significant Analysis of cDNA Microarray Data

نویسنده

  • Jian Huang
چکیده

A basic question in analyzing cDNA microarray data is normalization. The purpose of normalization is to remove systematic bias in the observed expression values by establishing a normalization curve across the whole dynamic range. A proper normalization procedure ensures that the normalized intensity ratios provide meaningful measures of relative expression levels. We propose a two-way semi-linear model (TW-SLM) for normalization and significant analysis of microarray data. This method does not make the usual assumptions underlying some of the existing methods. For example, it does not assume that: (i) the percentage of differentially expressed genes is small; or (ii) there is symmetry in the expression levels of upand down-regulated genes, as required in the lowess normalization method. The TW-SLM also naturally incorporates uncertainty due to normalization into significant analysis of microarrays. We use a semiparametric approach based on polynomial splines in the TW-SLM to estimate the normalization curves and the normalized expression values. We also conduct simulation studies to evaluate the TW-SLM method and illustrate the proposed method using a published microarray data set.

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تاریخ انتشار 2005