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Pre-processing Agilent microarray data |
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| Authors: | Marianna Zahurak Giovanni Parmigiani Wayne Yu Robert B Scharpf David Berman Edward Schaeffer Shabana Shabbeer Leslie Cope |
| Institution: | (1) Johns Hopkins University School of Medicine, Oncology Biostatistics, 550 N. Broadway, Baltimore, MD 21205, USA;(2) Johns Hopkins School of Medicine, Baltimore, MD 21231, USA;(3) Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe St., Room E3034, Baltimore, MD 21205, USA;(4) Johns Hopkins University School of Medicine, 1550 Orleans St., CRB II Room 5.45, Baltimore, MD 21231, USA;(5) Johns Hopkins University School of Medicine, 600 N. Wolfe St., Marburg 145, Baltimore, MD, 21287, USA;(6) Johns Hopkins University School of Medicine, 1650 Orleans St., CRB I, Baltimore, MD 21231, USA |
| Abstract: | BackgroundPre-processing methods for two-sample long oligonucleotide arrays, specifically the Agilent technology, have not been extensively studied. The goal of this study is to quantify some of the sources of error that affect measurement of expression using Agilent arrays and to compare Agilent's Feature Extraction software with pre-processing methods that have become the standard for normalization of cDNA arrays. These include log transformation followed by loess normalization with or without background subtraction and often a between array scale normalization procedure. The larger goal is to define best study design and pre-processing practices for Agilent arrays, and we offer some suggestions. |
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