BioinformaticsBioinformaticsPeer-reviewed journal article
SurvBal: Compositional Microbiome Balances for Survival Outcomes
Ying LiiD, Teresa LeeiD, Kai Marin, Xing HuaiD, Sujatha SrinivasaniD, David N. FredricksiD, John R. LeeiD, Wodan LingiD
Abstract
Identification of balances of bacterial taxa in relation to continuous and dichotomous outcomes is an increasingly frequent analytic objective in microbiome profiling experiments. SurvBal enables the selection of balances in relation to censored survival or time-to-event outcomes which are of considerable interest in many biomedical studies. The most commonly used survival models - the Cox proportional hazards and parametric survival models are included in the package, which are used in combination with step-wise selection procedures to identify the optimal associated balance of microbiome, i.e., the ratio of the geometric means of two groups of taxas relative abundances. Availability and implementationSurvBal is available as an R package and a Shiny app: https://github.com/yinglia/SurvBal, https://yinglistats.shinyapps.io/shinyapp-survbal/.
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