Analysis reveals genetic interventions impact aging and lifespan in Drosophila, suggesting deeper insights into longevity.
Research into longevity and aging involves comparing the size of cohorts at certain points on survival curves. However, this analysis is oversimplified because it provides limited information about the sample structure and the distribution of lifespan as a trait within the studied population. Here, we introduce a method for estimating lifespan across the entire data range using distribution analysis. More specifically, we propose dividing the lifespan series into intervals, obtaining the frequencies of phenotypes by lifespan within the sample, followed by distribution analysis using the normality crite-rion. Additionally, to visualize the differences, we propose describing the resulting distributions formally using the normal distribution function and the β-function. We demonstrate that the proposed methodology enables to extract additional information from survival data, providing new insights into the processes that occur in populations in response to genetic interventions and shedding light on their impact on ontogenesis. The proposed approach adds a new layer of information to studies of longevity and aging and expands the toolkit of methods used to analyze survival data.
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Yumuhova et al. (2025) studied this question.
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