Author: Caleb A. Class <caclass@mdanderson.org>, Min Jin Ha <mjha@mdanderson.org>
Description: Fits covariate dependent partial correlation matrices for integrative models to identify differential networks between two groups. The methods are described in Class et. al., (2018) <doi:10.1093/bioinformatics/btx750> and Ha et. al., (2015) <doi:10.1093/bioinformatics/btv406>.

Author: Caleb A. Class <cclass@butler.edu>, Min Jin Ha <mjha@mdanderson.org>
Maintainer: Caleb A. Class <cclass@butler.edu>

Title: Integrated Discovery of Oncogenic Signatures
Description: Integrate molecular profiles to discover candidate oncogenic drivers.

Title: Durability of Vaccine Efficacy Against SARS-CoV-2 Infection
Authors@R: c(person("Yu", "Gu", role = "aut"),
Description: Implements a nonparametric maximum likelihood method for assessing
potentially time-varying vaccine efficacy (VE) against SARS-CoV-2 infection
under staggered enrollment and time-varying community transmission, allowing
crossover of placebo volunteers to the vaccine arm.
Imports: Rcpp (>= 1.0.4.6), methods, stats, graphics, knitr
Collate: 'VEplot.R' 'VEcal.R' 'postProcess.R' 'EMmeth.R'

Imports: Rcpp (>= 1.0.4.6), methods, stats, graphics

Title: R Analysis package for iDynoMiCS Simulation Results
Description: iDynoMiCS is a computer program, developed by an international team of researchers, whose purpose is to model and simulate microbial communities in an individual-based way. It is described in detail in the paper "iDynoMiCS: next-generation individual-based modelling of biofilms" by Lardon et al, published in Environmental Microbiology in 2011. The simulation produces results in XML file format, describing the state of each species in each timestep (agent_State), a summary of the species statistics for a timepoint (agent_Sum), the state of each solute grid in each timestep (env_State) and a summary of the solutes for a timestep (env_Sum). This R package provides a means of reading this XML data into R such that the simulation response can be statistically analysed. iDynoMiCS is available from the website iDynoMiCS.org, where a full tutorial on using both the simulation and this R package is provided.