Two pipelines are provided to study microbial turnover along a gradient, including the beta diversity and microbial abundance change. The 'betaturn' class consists of the steps of community dissimilarity matrix generation, matrix conversion, differential test and visualization. The workflow of 'taxaturn' class includes the taxonomic abundance calculation, abundance transformation, abundance change summary, statistical analysis and visualization. Multiple statistical approaches can contribute to the analysis of microbial turnover.

Implements the MEC-TX (MEchanistic Clustering - Treatment
    eXposure) framework for encoding, clustering, and survival analysis of
    real-world oncology treatment timelines. Provides functions for
    normalising medication records, computing treatment intervals, performing
    k-means clustering in PCA space, assigning line-of-therapy labels, and
    comparing survival outcomes across treatment groups. Designed for use
    with registry-based cohorts such as the ORIEN AVATAR dataset. Methods
    follow the digital-twin framework described in Dhrubo and Spakowicz (2026)
    <https://github.com/spakowiczlab/mec-tx>.
    treatment timelines using the MEC-TX digital-twin framework.

Nonparametric estimation and inference for natural direct and indirect effects by Chan, Imai, Yam and Zhang (2016) <arXiv:1601.03501>.

Provides an extensive collection of datasets related to medicine, 
    diseases, treatments, drugs, and public health. This package covers topics 
    such as drug effectiveness, vaccine trials, survival rates, 
    infectious disease outbreaks, and medical treatments. The included datasets 
    span various health conditions, including AIDS, cancer, bacterial infections, 
    and COVID-19, along with information on pharmaceuticals and vaccines. These 
    datasets are sourced from the R ecosystem and other R packages, remaining 
    unaltered to ensure data integrity. This package serves as a valuable 
    resource for researchers, analysts, and healthcare professionals interested 
    in conducting medical and public health data analysis in R.