Online survival analysis software to assess the prognostic value of biomarkers using transcriptomic data in non-small-cell lung cancer.

ABSTRACT: In the last decade, optimized treatment for non-small cell lung cancer had lead to improved prognosis, but the overall survival is still very short. To further understand the molecular basis of the disease we have to identify biomarkers related to survival. Here we present the development of an online tool suitable for the real-time meta-analysis of published lung cancer microarray datasets to identify biomarkers related to survival. We searched the caBIG, GEO and TCGA repositories to identify samples with published gene expression data and survival information. Univariate and multivariate Cox regression analysis, Kaplan-Meier survival plot with hazard ratio and logrank P value are calculated and plotted in R. The complete analysis tool can be accessed online at: www.kmplot.com/lung. All t

SUBMITTER: Gyorffy B 

PROVIDER: S-EPMC3867325 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature