Hi there,

So I'm processing some TruboID LFQ data in Proteomics package Perseus and using the 'replace missing values with normal distribution' function for the total matrix. The issue I have is that I want to repeat the imputation multiple times to confirm that significant changes are consistently significant with different randomly generated low abundance values, and isn't just a fluke of the imputation. Unfortunately, when I'm repeating the imputation step, I'm getting exactly the same values each time, even if I open a new instance of Perseus.

As far as I understand Perseus should be randomly pulling these numbers from a normal distribution of the lowest abundances in the matrix, but it's giving exactly the same values for NA values in the same positions. Am I missing something here?