Following is a scientist's responses to the question, "What's your top advice for designing a microarray-analysis experiment to ensure that your statistical analysis, control for error, and normalization procedures will give you an accurate end-answer?"
For a complete list of scientists' responses, read the November/December issue of Genome Technology, a GenomeWeb News sister publication.
"I'd say that the most important things are sufficient replication, preferably at the level of biological replicates.
"Understand your sources of non-biological variation, and try and design it such that those sources will not confound the biological variation. That is, if you are running 20 arrays, 10 from treated, and 10 from untreated samples, don't do all the treated on one day, and the untreated on another. The same idea holds for any potential source of variation, e.g. if you're using different microarray batches, or different hybridization chambers or water baths."
Director, Microarray Informatics