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Related Experiment Video

Updated: Jun 10, 2025

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SurvBal: compositional microbiome balances for survival outcomes.

Ying Li1, Teresa Lee2, Kai Marin2

  • 1Division of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065, United States.

Bioinformatics (Oxford, England)
|October 15, 2024
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Summary
This summary is machine-generated.

This study introduces SurvBal, a tool for analyzing microbiome data and survival outcomes. It helps identify bacterial balances linked to time-to-event data, crucial for biomedical research.

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Area of Science:

  • Microbiome research
  • Statistical bioinformatics
  • Survival analysis

Background:

  • Analyzing microbiome composition in relation to health outcomes is a growing field.
  • Identifying specific bacterial taxa or balances associated with disease progression or treatment response is critical.
  • Existing methods often struggle with complex survival data.

Purpose of the Study:

  • To introduce the SurvBal R package and Shiny app for microbiome survival analysis.
  • To enable the selection of bacterial balances associated with time-to-event outcomes.
  • To provide a user-friendly tool for researchers in microbiome and biomedical fields.

Main Methods:

  • Utilizes Cox proportional hazards and parametric survival models.
  • Incorporates step-wise selection procedures for identifying optimal microbial balances.
  • Defines microbial balance as the ratio of geometric means of relative abundances between two taxa groups.

Main Results:

  • SurvBal facilitates the identification of microbial balances linked to survival data.
  • The package supports analysis of censored survival and time-to-event outcomes.
  • Enables researchers to explore the relationship between specific bacterial ratios and patient survival.

Conclusions:

  • SurvBal is a valuable tool for microbiome profiling studies with survival endpoints.
  • It addresses a significant analytical gap in connecting microbial communities to time-to-event data.
  • The package enhances the ability to discover microbial biomarkers for survival prediction.