Correlating High-dimensional longitudinal microbial features with time-varying outcomes with FLORAL
Teng Fei, Victoria Donovan, Tyler Funnell, Mirae Baichoo, Nicholas R. Waters, Jenny E. Paredes, Anqi Dai, Francesca Castro, Jennifer Haber, Ana Gradíssimo, Sandeep S. Raj, Alexander M. Lesokhin, Urvi Ashok Shah, Marcel R.M. van den Brink, Jonathan U. Peled
The paper introduces FLORAL, a method for analyzing longitudinal microbiome data to identify biomarkers associated with time-varying outcomes, showing improved sensitivity and FDR control in simulations and real-world applications.
bioRxiv · Feb 17, 2025 · PreprintBioinformatics