UCSC XenaXena

Kaplan-Meier survival analysis on any data

Mary Goldman26 February 2019

Wondering if a gene (or probe, or clinical value, etc) affects survival? We have survival analyses complete with p-values, custom time variable cutoff, and multiple survival endpoints.

Whether you're looking at DNA, RNA, methylation or protein, we can help you determine if a gene affects survival. Stratify your samples by any genomic or phenotypic data (e.g. expression, copy number, subtype, age, etc) and determine if there is a statistically significant survival difference.

Start with our walk through, or jump in by going to the Xena Browser and use the wizard to add the data you would like to stratify your samples into the Visual Spreadsheet. Once your data is on the screen, click the three-dot caret menu at the top of the column and choose 'Kaplan Meier Plot'.

Example

example

Kaplan-Meier analysis of overall survival for TCGA lower grade glioma histological subtypes. Black boxes in the figure highlight, from top to bottom, a button to generate a PDF, the statistical analysis results, a dropdown menu to select different survival endpoints such as overall or recurrence-free survival, and a textbox to enter a custom survival time cutoff (currently set to 3,650 days, or 10 years). Patients characterized as having the astrocytoma histological subtype have significantly worse 10-year overall survival compared to the oligodendroglioma and oligoastrocytoma subtypes (p < 0.05).

View this example live in the Xena Browser.

Improve this page