Kolmogorov-Smirnov and Shapiro-Wilk single distribution analysis methods in examining sample structure, strength of genetic background, and effects of interventions in lifespan and aging studies

Abstract

The analysis of lifespan and ageing involves a variety of calculations based on survival data. One of these is the comparison of survival curves. However, inspection of survival curves provides little information about the frequency of phenotypes within samples. Here we propose to divide the distribution into intervals to obtain information about the sample structure. Then, we apply the normality criterion to the distributions using the Kolmogorov-Smirnov and Shapiro-Wilk tests. Using this approach, we reveal the destabilising effect of mutations on ontogenesis and lifespan, and estimate the strength of the genetic background of the lines. The proposed methodology allows effective estimation of sample structure and adds a new layer of information to longevity studies.