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OASIS：用于衰老研究中寿命分析的在线应用程序。

OASIS: online application for the survival analysis of lifespan assays performed in aging research.

机构信息

School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, Pohang, South Korea.

出版信息

PLoS One. 2011;6(8):e23525. doi: 10.1371/journal.pone.0023525. Epub 2011 Aug 15.

DOI:10.1371/journal.pone.0023525
PMID:21858155
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3156233/
Abstract

BACKGROUND

Aging 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 FINDINGS: We 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/SIGNIFICANCE: OASIS 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.

摘要

背景

衰老是一个基本的生物过程。对影响寿命的遗传和环境因素进行特征描述，是理解机体水平衰老机制的关键步骤。为了捕捉遗传和环境因素对寿命的不同影响，需要进行适当的统计分析。

方法/主要发现：我们开发了一个在线生存分析应用程序（OASIS），它以用户友好的方式帮助进行分析生存数据的各种新的统计任务。OASIS 提供了标准的生存分析结果，包括 Kaplan-Meier 估计和中位/平均生存时间，同时考虑了删失的生存数据。OASIS 还提供了各种统计检验，包括平均生存时间比较、总体生存曲线和特定时间点的生存率。为了可视化生存数据，OASIS 生成生存和对数累积风险图，使研究人员能够轻松解释他们的实验结果。此外，我们还提供了可以分析生存数据集之间差异的统计方法。此外，用户可以分析危险因素对生存的比例影响。

结论/意义：OASIS 提供了一个平台，对于促进衰老研究领域生存数据分析的高效统计分析至关重要。网络应用程序和算法的详细描述可从 http://sbi.postech.ac.kr/oasis 获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/130534923550/pone.0023525.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/450553e9e9ad/pone.0023525.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/2f6e520ccf09/pone.0023525.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/5c14f1f57270/pone.0023525.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/100b54fdec7a/pone.0023525.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/1e21dab3ec3a/pone.0023525.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/8cc26c4873bf/pone.0023525.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/130534923550/pone.0023525.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/450553e9e9ad/pone.0023525.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/2f6e520ccf09/pone.0023525.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/5c14f1f57270/pone.0023525.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/100b54fdec7a/pone.0023525.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/1e21dab3ec3a/pone.0023525.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/8cc26c4873bf/pone.0023525.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6dbe/3156233/130534923550/pone.0023525.g007.jpg

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