Is quantile normalization adequate for normalizing data with very few samples?

For example this microarray data. Typically after normalization we'd like to compare Cancer-1 with Normal and Cancer-2 with Normal for differential expression.

    mRNA     Cancer-Type-1   Cancer-Type-2  Normal
    mRNA1      30        49    12
    mRNA2     199        200   78
    ...        ...       ...  ....
    mRNA1000   13        40    88

If not what is the appropriate normalization method?


Quantile normalization works well when the samples are comparable (ie have a high correlation). We don't know whether that is the case with your data. There is nothing in the algorithm that requires a large number of arrays, but realistically with only 3 arrays your analysis is pretty limited no matter what the normalization method.

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  • $\begingroup$ Thanks. Why "high correlation" is needed? Any reference for that? $\endgroup$ – neversaint Feb 2 '13 at 12:07

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