Decision Tree Analysis for Probabilistic Subgroup Identification with Multiple Treatments

In the situation when multiple alternative treatments or interventions available, different population groups may respond differently to different treatments. This package implements a method that discovers the population subgroups in which a certain treatment has a better effect than the other alternative treatments. This is done by first estimating the treatment effect for a given treatment and its uncertainty by computing random forests, and the resulting model is summarized by a decision tree in which the probabilities that the given treatment is best for a given subgroup is shown in the corresponding terminal node of the tree.

Analysis of Single-Cell Viral Growth Curves

Aims to quantify time intensity data by using sigmoidal and double sigmoidal curves. It fits straight lines, sigmoidal, and double sigmoidal curves on to time vs intensity data. Then all the fits are used to make decision on which model best describes the data. This method was first developed in the context of single-cell viral growth analysis (for details, see Caglar et al. (2018) ), and the package name stands for "SIngle CEll Growth Analysis in R".

Build 'Rust' Powered 'R' Packages

Provides a framework for creating high-performance 'R' packages powered by the 'Rust' programming language using the 'extendr' Rust crate. It offers 'usethis'-like functions to scaffold and develop 'Rust' powered 'R' packages, including utilities for publishing to CRAN, managing dependencies, configuring development environments, and rendering 'Rust' code in 'knitr' documents. Additionally, it provides functions to compile and evaluate 'Rust' code directly from 'R' for interactive development.