What methods exist to calculate RNA expression profile similarity Some of the work in our lab requires a comparison of a strain across several experimental conditions. We are looking to identify most similar experimental conditions based on the gene transcription response similarity from the cell.

While we could easily invent and create home-grown methods to do it, their implementation and testing are a laborious project in themselves and are outside the scope of our current work.

Are there any methods for RNA expression profile similarity computation that has been already published? If yes, what is your experience using them?
There's a new paper that's just appeared on the subject of "proportionality", including a method by which RNA expression might be compared.

This is a new concept for me, and the article is not easy enough for me to read that I can write up a quick summary; the authors don't seem to devote a section in the paper to defining "proportionality". However, here's an interesting chunk from the article:


  We graphed the network of relationships between these mRNAs (S5 Fig.), an approach similar to gene co-expression network [12] or weighted gene co-expression analysis [13] but founded on proportionality and therefore valid for relative data. The network revealed one cluster of 96, and many other smaller clusters of mRNAs behaving proportionally across conditions.
  ...
  We are also keen to raise awareness that correlation (and other statistical methods that assume measurements come from real coordinate space) should not be applied to relative abundances. This is highly relevant to gene coexpression networks [12]. Correlation is at the heart of methods like Weighted Gene Co-expression Network Analysis [13] and heatmap visualization [14]. These methods are potentially misleading if applied to relative data.