Facilitates population-level analysis of ligand-receptor (LR) interactions 
    using large-scale single-cell transcriptomic data. Identifies significant LR pairs 
    and quantifies their interactions through correlation-based filtering and projection score 
    computations. Designed for large-sample single-cell studies, the package employs 
    statistical modeling, including linear regression, to investigate LR relationships 
    between cell types. It provides a systematic framework for understanding cell-cell 
    communication, uncovering regulatory interactions and signaling mechanisms. 
    Offers tools for LR pair-level, sample-level, and differential interaction analyses, 
    with comprehensive visualization support to aid biological interpretation. 
    The methodology is described in a manuscript currently under review and will be 
    referenced here once published or publicly available.

Tools for modelling populations and demography using matrix projection models,
 with deterministic and stochastic model implementations. Includes population projection,
 indices of short- and long-term population size and growth, perturbation analysis,
 convergence to stability or stationarity, and diagnostic and manipulation tools.

The primary goal of phase I clinical trials is to find the maximum tolerated dose (MTD). To reach this objective, we introduce a new design for phase I clinical trials, the posterior predictive (PoP) design. The PoP design is an innovative model-assisted design that is as simply as the conventional algorithmic designs as its decision rules can be pre-tabulated prior to the onset of trial, but is of more flexibility of selecting diverse target toxicity rates and cohort sizes. The PoP design has desirable properties, such as coherence and consistency. Moreover, the PoP design provides better empirical performance than the BOIN and Keyboard design with respect to high average probabilities of choosing the MTD and slightly lower risk of treating patients at subtherapeutic or overly toxic doses.