How to choose the measure of dissimilarity between the expression patterns of two genes?

As a measure of dissimilarity between the expression patterns of two genes, no method outperforms Euclidean distance for ratio-based measurements, or Pearson distance for non-ratio-based measurements at the optimal choice of cluster number. The compared distance measures are: Euclidean, 3-norm, Manhattan or city-block, Hausdorff, and Pearson correlation.

See PMID: 12368250

This paper also concluded that clusters of genes derived from single- and average-linkage hierarchical clustering tend to produce worse-than-random results.