biostudies-literatureUnknown15Luo QMetagenomic time-course studies provide valuable insights into the dynamics of microbial systems and have become increasingly popular alongside the reduction in costs of next-generation sequencing technologies. Normalization is a common but critical preprocessing step before proceeding with downstream analysis. To the best of our knowledge, currently there is no reported method to appropriately normalize microbial time-series data. We propose TimeNorm, a novel normalization method that considers the compositional property and time dependency in time-course microbiome data. It is the first method designed for normalizing time-series data within the same time point (intra-time normalization) and across time points (bridge normalization), separately. Intra-time normalization normalizes microbFrontiers in genetics1417533https://www.ebi.ac.uk/biostudies/studies/S-EPMC11458461biostudies-literatureTimeNorm: a novel normalization method for time course microbiome data.PMC11458461Luo QLu MDu RLytal NAn LJiang HButt HfalseTimeNorm: a novel normalization method for time course microbiome data.Metagenomic time-course studies provide valuable insights into the dynamics of microbial systems and have become increasingly popular alongside the reduction in costs of next-generation sequencing technologies. Normalization is a common but critical preprocessing step before proceeding with downstream analysis. To the best of our knowledge, currently there is no reported method to appropriately normalize microbial time-series data. We propose TimeNorm, a novel normalization method that considers the compositional property and time dependency in time-course microbiome data. It is the first method designed for normalizing time-series data within the same time point (intra-time normalization) and across time points (bridge normalization), separately. Intra-time normalization normalizes microb2024-01-01T00:00:00Z20242026-06-09T07:20:36.046Z2025-04-06T22:33:07.926ZS-EPMC114584613938114110.3389/fgene.2024.1417533