Fig. 1.

The algorithm of SEG. SEG will: 1)normalize the data and exclude the log₂-ratio outliers (smooth data); 2)identify change-points; and 3)find CNAs (label segments).For change-point detection, SEG first depends upon the user's input to assign initial change-points, and then loops through the SSE (sum of squared error) to remove insignificant change-points using dynamic programming (see text).The program is implemented in C and can be downloaded from GitHub at https://github.com/ZhaoS-Lab/SEG.