Analysis of DNA microarray expression data.
DNA microarrays are powerful tools for studying biological mechanisms and for developing prognostic and predictive classifiers for identifying the patients who require treatment and are best candidates for specific treatments. Because microarrays produce so much data from each specimen, they offer great opportunities for discovery and great dangers or producing misleading claims. Microarray based studies require clear objectives for selecting cases and appropriate analysis methods. Effective analysis of microarray data, where the number of measured variables is orders of magnitude greater than the number of cases, requires specialized statistical methods which have recently been developed. Recent literature reviews indicate that serious problems of analysis exist a substantial proportion of publications. This manuscript attempts to provide a non-technical summary of the key principles of statistical design and analysis for studies that utilize microarray expression profiling.
Simon
Richard
R
Biometric Research Branch, Division of Cancer Treatment & Diagnosis, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892-7434, USA. rsimon@nih.gov
D035843:Biomedical Research / Q000379:methods; D005453:Fluorescence; D020869:Gene Expression Profiling / Q000379:methods*; D005796:Genes / Q000502:physiology; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012107:Research Design; D013223:Statistics as Topic / Q000379:methods*; D054928:Validation Studies as Topic
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