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Okay. I'm not sure if I'm phrasing it well but here is the problem. I have a set of data which comes out as a density measurement of proteins, these are expressed in a numerical values and correspond to the concentration mg/ml of protein in my sample. However, each sample tested had a difference density of cells to start with, so the measurement of protein will be affected positively with the higher density of cells. I would like to adjust my protein concertation measurements against the cell densities. As an example: Sample 1 has a protein concentration of 0.1 mg/ml and the density of cells is 0.500, sample 2 has a protein concentration of 0.003mg/ml but has a density of cells equal to 0.150. As you can see there is a strong correlation between these numbers. I thought about simply dividing protein concentration against the cell density and then compare these numbers between samples, but I'm not sure. Does anyone have a better idea? Thanks! Anna

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  • $\begingroup$ That's the first thought that occurs to me, as well. Another way (if you have enough data) is to group by original cell densities. That is, divide your data up by bins of cell densities, like a histogram, and then do your analysis within each bin, separately. $\endgroup$ – Adrian Keister Sep 9 '20 at 14:14

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