microSTASIS

microSTASIS assesses microbiota stability over time through iterative clustering of paired samples from the same individuals.

Key Features:

• Iterative Hartigan-Wong k-means clustering: The core function repeatedly applies the Hartigan-Wong k-means algorithm to stress paired samples from the same individuals and test whether they remain clustered together across multiple numbers of clusters over a whole data set of individuals.
• Paired sample subsetting: Functions subset samples from paired time points for targeted analysis.
• Result validation: Functions validate the stability assessment results.
• Output visualization: Functions visualize the clustering and stability output.

Scientific Applications:

• Microbiota temporal stability analysis: Evaluates whether an individual's microbiota composition remains stable between paired time points by testing if samples from the same individual cluster together under iterative k-means stress testing.

Methodology:

The method applies Hartigan-Wong k-means clustering iteratively to paired samples from the same individuals across multiple numbers of clusters to test whether they remain together.