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Longitudinal Microbiome Dynamics & Time-Series Modeling Training | Trajectories, Mixed-Effects & Time Series

NTHRYS >> Services >> Academic Services >> Training Programs >> Bioinformatics Training >> Microbiome, Metagenomics & AMR Analytics >> Longitudinal Microbiome Dynamics & Time-Series Modeling Training | Trajectories, Mixed-Effects & Time Series

Longitudinal Microbiome Dynamics & Time-Series Modeling — Hands-on

Learn how to handle microbiome data collected over time rather than single snapshots. This module focuses on longitudinal study design, temporal diversity metrics, trajectories and transitions, and the use of mixed effects and basic time series models to relate microbiome dynamics with clinical or environmental variables.

Longitudinal Microbiome Dynamics & Time-Series Modeling
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Session 1
Fee: Rs 8800
Longitudinal Study Designs & Data Structures
  • Types of longitudinal microbiome designs
  • repeated measures cohorts intervention and crossover designs time varying exposures and outcomes
  • Data structures for longitudinal analysis
  • wide vs long tables subject identifiers and visit times handling irregular sampling and dropouts
  • Toolchain setup in R and Python
  • tidyverse / data.table pandas for long format data basic visual checks over time
Session 2
Fee: Rs 11800
Temporal Diversity, Trajectories & Visualisation
  • Tracking alpha and beta diversity over time
  • within subject diversity trajectories distance to baseline measures stability vs volatility metrics
  • Visualising longitudinal microbiome changes
  • spaghetti plots and smoothed lines stacked barplots over time animated or faceted ordination views
  • Simple transition and state summaries
  • state definitions for communities transition matrices overview time in state and switching frequency
Session 3
Fee: Rs 14800
Time-Series & Mixed-Effects Modeling
  • Mixed-effects models for repeated microbiome measures
  • random intercept and slope ideas lme4 / nlme style syntax in R handling time varying covariates
  • Basic time series concepts for microbiome data
  • autocorrelation and partial autocorrelation lagged features and simple AR style ideas smoothing and spline based time trends
  • Linking dynamics to outcomes and exposures
  • baseline vs change and rate of change simple joint models overview interpreting model coefficients and plots
Session 4
Fee: Rs 18800
Mini Capstone: Longitudinal Microbiome Story
  • Designing a longitudinal analysis for one dataset
  • guided theory plus practical
  • Building temporal diversity, trajectory and model outputs
  • per subject trajectories and summaries one mixed effects or time series model clear plots for manuscripts or presentations
  • Deliverables: longitudinal report and figure set
  • PDF or HTML summary time series figures and tables methods notes for reproducibility


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