| Normalization method | Summarization method |
---|---|---|
MAS | Global scaling – individual array normalization; moderate influence on expression levels, no effect on outliers. Non-parametric methods are potentially more reliable | Tukey biweight (robust average) – subtract MM from PM and adjust for negative values |
dChip | Average median scaling – individual array normalization; moderate influence on expression levels, no effect on outliers. Non-parametric methods are potentially more reliable | Model-based index estimate – subtract MM from PM, but take indivual probe variability, assessed over all available arrays, into account |
RMA | Quantile normalization – multiple array normalization; considerable influence on expression levels, with removal of outliers. Parametric methods are potentially more reliable | Median polish – only use MM for background adjustment; fit parameters of linear model robustly using median polish, taking into account all available arrays |
GCRMA | Quantile normalization – multiple array normalization; considerable influence on expression levels, with removal of outliers. Parametric methods are potentially more reliable | Median polish – only use MM for background adjustment; fit parameters of linear model robustly using median polish, taking into account all available arrays; fit extra GC-content parameter |