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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?

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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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