R/doc_TMixClust.R

In cbg-ethz/TMixClust: Time Series Clustering of Gene Expression with Gaussian Mixed-Effects Models and Smoothing Splines

#' @title The main usages of TMixClust
#'
#' @description Description of package TMixClust
#'
#' @section Overview:
#' TMixClust is a soft-clustering method which employs mixed-effects models
#' with nonparametric smoothing spline fitting and is able to
#' robustly stratify genes by their complex time series patterns.
#' The package has, besides the main clustering method, a set of
#' functionalities assisting the user to visualise and assess the
#' clustering results, and to choose the most optimal clustering solution.
#'
#' @references Golumbeanu M, Desfarges S, Hernandez C, Quadroni M, Rato S,
#' Mohammadi P, Telenti A, Beerenwinkel N, Ciuffi A. (2017) Dynamics of
#' Proteo-Transcriptomic Response to HIV-1 Infection.
#'
#' @author Monica Golumbeanu, \email{monica.golumbeanu@bsse.ethz.ch}
#'
#' @docType package
#' @name TMixClust-package
#'
#' @aliases TMixClust-package
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