# 3.7. Detection of Change Points in Age-Related Modules

To analyze the behaviour of the processes identified in this work, a moving average transformation with a 5-year window was applied to each transcript of ageCollapsed. Then, the expression profile of each AgingGenes class and AgingNet sub-modules was calculated through the median of the expression values of their transcripts by age, obtaining a condensed expression time series for each class/sub-module. Subsequently, a point detection analysis was carried out on the expression profile of each module to identify important changes in its behaviour throughout life. This test was performed using the cpm package (MATTHEWS; FOULKES, 2015) of R, with the Cramer-von-Mises method in which it detects statistically significant changes (p-value < 0.01) both in the mean and in the variance between temporal phases.


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