Wavelet analysis of gene expression (WAGE)

The wavelet transform (WT) is the mathematical operator of choice for the analysis of nonstationary signals. At the same time, it is also a modelling operator that may be used to impose functional constraints on data to unveil hidden groupings and relationships. In this work, we apply the WT to the chromosomal sequences of gene expression values measured with microarray technology. The application of the wavelet operator aims to uncover clusters of genes that interact by vicinity, either because of a shared regulatory mechanism or because of common susceptibility to environmental factors. Application of the method to data on the expression of human brain genes in neuro-degeneration validates the technique and, at the same time, illustrates the potential of the method.

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