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PubMed · 16939793

Microarray quality control.

James M Minor
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Abstract

Physically separated groups of specific sequences (probes) provide useful high through put (HTP) measurements for the amount of selected DNA/RNA sequences in a biological target sample. Unfortunately, these measurements are impacted by various technical sources, such as platform production factors, target preparation processes, hybridization method/conditions, and signal-extraction devices and methods. Given the typically huge population of signals, statistical methods are especially effective at estimation and removal of such technical distortions (Churchill, 2002; Kerr et al., 2000; Yue et al., 2001), as well as providing metrics for computer-based quality control (QC), for example, autoQC (Minor et al., 2002a). This chapter reviews statistical procedures that have been validated by successful applications in both large-scale commercial ventures (Ganter et al., 2005) and individual research studies (Parisi et al., 2003, 2004) involving HTP projects. This chapter focuses on methods for spatially distributed probes on a flat medium surface such as glass, collectively known as a microarray.

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AlgorithmsAnimalsData Interpretation, StatisticalHumansOligonucleotide Array Sequence AnalysisQuality ControlJournal ArticleReview

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James M Minor. 2006. Microarray quality control.. https://doi.org/10.1016/s0076-6879(06)11012-5

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