Process / pipelineBioinformatics / omics

Time-series Microbiome Diversity Analysis — Longitudinal Microbiome Diversity Analysis

Time-series microbiome diversity analysis tracks how the richness, evenness, and community composition of microbial communities change across multiple time points within the same subjects. By combining standard diversity metrics with longitudinal statistical models, it separates true temporal dynamics from inter-individual variation, identifying when and how perturbations such as diet changes, antibiotic treatment, or disease onset reshape the microbiome.

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Sources

  1. Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., & Holmes, S. P. (2016). DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods, 13(7), 581–583. DOI: 10.1038/nmeth.3869
  2. Chen, Y., Lun, A. T. L., & Smyth, G. K. (2023). Differential abundance testing on single-cell data using quasi-likelihood methods. Genome Biology, 24(1), 188. link

Related methods

ScholarGateTime-series microbiome diversity analysis (Longitudinal Microbiome Diversity Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/bioinformatics/time-series-microbiome-diversity-analysis