Dear organizers, We are working on parametric models for the single-cell phosphorylation data, and we have a question on how to properly interpret the distribution data for the markers. If we aggregate the markers measurements by cell-line, most of their expression distribution presents a peak in the very initial value; taking as example the p.RB marker 100-bin expression distribution for the HCC1187 cell-line, under the EGF treatment in time 0.0: https://drive.google.com/file/d/1YhN7vJXVUVRRkOu-NUONVclmDP3SdH-L/view?usp=sharing From the 12,738 measured cells, 644 presented the p.RB expression of 1.65488, which converting back to the original values represents a count of 13 ions. This is way more (roughly 10 times) from the following reading. Checking the other cell-lines for the same marker, we identified the initial value of 2.168072 (22 ions), which is even more frequent (roughly 20 times the next reading). We are trying to understand why those peaks occur, to define how to better treat them on the data distribution. They seem to accommodate lower counts which, for some reason, could not be properly expressed by the Mass Cytometry data pipeline, but as we are new to this kind of data, we are not sure. Some questions we have so far: 1. Are the initial peak expression counts accumulating lower counts which, if not accumulated, would follow the same distribution of the expression counts? 2. Why does the initial value varies according to the cell-line analyzed? Is due to a parameter setting (or calibration) of each Mass Cytometry run? Can someone help us better understand this phenomena? Thanks!