School of Mathematics and Statistics - Research Publications

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    Normalization of boutique two-color microarrays with a high proportion of differentially expressed probes
    Oshlack, A ; Emslie, D ; Corcoran, LM ; Smyth, GK (BMC, 2007)
    Normalization is critical for removing systematic variation from microarray data. For two-color microarray platforms, intensity-dependent lowess normalization is commonly used to correct relative gene expression values for biases. Here we outline a normalization method for use when the assumptions of lowess normalization fail. Specifically, this can occur when specialized boutique arrays are constructed that contain a subset of genes selected to test particular biological functions.