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

Cited 144 time in webofscience Cited 0 time in scopus
  • Hit : 31
  • Download : 0
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.
Publisher
PUBLIC LIBRARY SCIENCE
Issue Date
2011-08
Language
English
Article Type
Article
Citation

PLOS ONE, v.6, no.8

ISSN
1932-6203
DOI
10.1371/journal.pone.0023525
URI
http://hdl.handle.net/10203/251717
Appears in Collection
BS-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 144 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0