OASIS: Online Application for the Survival Analysis of Lifespan Assays Performed in Aging Research

BackgroundAging is a fundamental biological process. Characterization of genetic and environmental factors that influence lifespan is a crucial step toward understanding the mechanisms of aging at the organism level. To capture the different effects of genetic and environmental factors on lifespan, appropriate statistical analyses are needed.
Methodology/Principal FindingsWe developed an online application for survival analysis (OASIS) that helps conduct various novel statistical tasks involved in analyzing survival data in a user-friendly manner. OASIS provides standard survival analysis results including Kaplan-Meier estimates and mean/median survival time by taking censored survival data. OASIS also provides various statistical tests including comparison of mean survival time, overall survival curve, and survival rate at specific time point. To visualize survival data, OASIS generates survival and log cumulative hazard plots that enable researchers to easily interpret their experimental results. Furthermore, we provide statistical methods that can analyze variances among survival datasets. In addition, users can analyze proportional effects of risk factors on survival.
Conclusions/SignificanceOASIS provides a platform that is essential to facilitate efficient statistical analyses of survival data in the field of aging research. Web application and a detailed description of algorithms are accessible from http://sbi.postech.ac.kr/oasis.

背景
衰老是一种基础的生物学过程。对影响寿命的遗传与环境因素进行表征，是在机体层面理解衰老机制的关键步骤。为了揭示遗传与环境因素对寿命的不同影响，需要开展恰当的统计分析。

方法/主要结果
本研究开发了一款面向生存分析（survival analysis）的在线应用工具（OASIS），能够以友好的用户交互方式，完成分析生存数据所需的各类新型统计任务。OASIS可处理删失生存数据（censored survival data），并输出包括卡普兰-迈耶估计量（Kaplan-Meier estimates）、平均/中位生存时间在内的标准生存分析结果。该工具还提供多种统计检验功能，包括平均生存时间比较、总生存曲线比较以及特定时间点生存率比较。为实现生存数据的可视化，OASIS可生成生存曲线图与对数累积风险图（log cumulative hazard plots），便于研究人员直观解读实验结果。此外，本工具还支持针对多组生存数据集的差异分析，同时允许用户分析风险因子对生存的比例效应。

结论与意义
OASIS为衰老研究领域的生存数据高效统计分析提供了不可或缺的平台。该网页应用及其算法的详细说明可通过http://sbi.postech.ac.kr/oasis 获取。