Methods for eliminating false data from comparative data matrices and for quantifying data matrix quality

A method for eliminating indistinguishable differentials from a direct comparison of a pair of data matrices comprising a plurality of data points, wherein each data point in the first matrix of the pair has a corresponding data point in the second matrix of the pair, the method comprising:

• (a) ranking the data points of each matrix from highest to lowest according to intensity such that a plot of rank versus intensity of the data points for each matrix provides an experimental curve for each matrix;
• (b) fitting a smooth curve to each experimental curve to provide a model curve for each matrix, each model curve comprising a first section separated from a second section by an inflection point;
• (c) eliminating any pair of corresponding data points for which each data point of the pair is below the inflection point of its model curve;
• and
• (d) eliminating any pair of corresponding data points for which the rank of each data point of the pair is below a selected cutoff rank between rmin and rmax, where rmin is the rank of the data point at the minimum of the derivative of one of the model curves and rmax is the rank of the highest ranking data point on the model curve.