TimeNorm: a novel normalization method for time course microbiome data

TimeNorm: a novel normalization method for time course microbiome data

Blog Article

Metagenomic time-course studies provide valuable insights into the dynamics of microbial systems and have become increasingly g35 coupe fender 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 microbial samples under the same condition based on common dominant features.

Bridge normalization detects and utilizes a group of most stable features across two adjacent time points for normalization.Through comprehensive simulation studies and application to a real study, we demonstrate that TimeNorm outperforms powell and mahoney bloody mary mix existing normalization methods and boosts the power of downstream differential abundance analysis.