So I have a dataset (ELISA data) for quite a few analytes for patients and healthy controls. Almost all analytes are highly significantly different in patients vs. controls (non-parametric test). So I produced a heatmap and the clustering was okish. However, after log2 transformation it's very good (I add a very small constant to all values avoid -Inf values as I have quite a few 0). If I convert all ELISA data to the same unit before taking the log2 I get an almost perfect clustering, which I would have expected since almost all analytes are highly significantly different between the two groups. But I am a bit worried it's not ok what I did and I do not understand why the clustering improved so much.
Any advice/input is highly appreciated!