The Annals of Applied Statistics

A statistical framework for the analysis of microarray probe-level data

Zhijin Wu and Rafael A. Irizarry

Full-text: Open access

Abstract

In microarray technology, a number of critical steps are required to convert the raw measurements into the data relied upon by biologists and clinicians. These data manipulations, referred to as preprocessing, influence the quality of the ultimate measurements and studies that rely upon them. Standard operating procedure for microarray researchers is to use preprocessed data as the starting point for the statistical analyses that produce reported results. This has prevented many researchers from carefully considering their choice of preprocessing methodology. Furthermore, the fact that the preprocessing step affects the stochastic properties of the final statistical summaries is often ignored. In this paper we propose a statistical framework that permits the integration of preprocessing into the standard statistical analysis flow of microarray data. This general framework is relevant in many microarray platforms and motivates targeted analysis methods for specific applications. We demonstrate its usefulness by applying the idea in three different applications of the technology.

Article information

Source
Ann. Appl. Stat. Volume 1, Number 2 (2007), 333-357.

Dates
First available in Project Euclid: 30 November 2007

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1196438021

Digital Object Identifier
doi:10.1214/07-AOAS116

Mathematical Reviews number (MathSciNet)
MR2415738

Zentralblatt MATH identifier
1126.62111

Keywords
Microarray preprocessing probe level models background noise normalization

Citation

Wu, Zhijin; Irizarry, Rafael A. A statistical framework for the analysis of microarray probe-level data. Ann. Appl. Stat. 1 (2007), no. 2, 333--357. doi:10.1214/07-AOAS116. https://projecteuclid.org/euclid.aoas/1196438021


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