Microarray quality control.
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.
Minor
James M
JM
Agilent Technologies, Inc., Santa Clara, CA, USA.
D000465:Algorithms; D000818:Animals; D003627:Data Interpretation, Statistical; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011786:Quality Control