Abstract
Microarray data has a linear relationship with mRNA levels in sample tissue within a particular range of signal intensity that is not affected by saturation or additive noise. Consequently, data have to be normalized prior to comparison, and the affected data should be identified. The normalization process influences experimental accuracy, and it determines the extent of experiments, i.e., a series of comparable data sets. In this article we introduce data normalization software that runs on Windows OS. It normalizes data according to a three-parameter lognormal distribution model, constituting an expansion of the previous one [2]. Since it treats data parametrically, a high level of accuracy can be expected. Being free from the common reference RNA samples, it can compare data between wide varieties of experiments.
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