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Abstract:
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Though many novel microarray analysis methods contribute to biological discoveries, inability to properly evaluate the novel methods limits their ability to advance science. Because the underlying distribution of microarray data is unknown, novel methods are typically tested against the normal distribution. However, microarray data are not, in fact, normally distributed, and assuming so can have misleading consequences. Using an Affymetrix technical replicate Spike-In data set, we show that oligonucleotide expression values are not normally distributed for any of the standard methods for calculating expression values. The resulting data tend to have a large proportion of skew and heavy tailed values. Additionally, we show that standard methods can give unexpected and misleading results when the data are not well approximated by the normal distribution. Robust methods are recommended.
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