I am CS major, please be patient if my question is not well-stated.
The dataset is quantitative mass spectrometry (MS) data. By labeling proteins of two different samples A and B, we get the relative abundance of 100 to thousands of proteins in A/B. Alongside with this ratio, we can estimate its variance based on the signal intensities.
Wanted: A list of proteins significantly different from the set of all protein ratios.
Most proteins remain unchanged between A and B. The population of log-ratios distributes around 1. The histogram shows a bell shape with fat tails. Two-term Gaussian mixture model has been found to provide a good fit to experimental noise. I suppose it would work good for this data - think of experimental and biological noise.
How to test for significantly different ratios on such a two-term Gaussian mixture model?
Thanks for your responses!