R/HTSanalyzeR2.R

In CityUHK-CompBio/HTSanalyzeR2: HTSanalyzeR2: An R package for functional annotation, network analysis and time series analysis of high-throughput data

#' HTSanalyzeR2 Package Overview
#'
#' This package provides classes and methods for gene set over-representation,
#' enrichment and network analyses on various high-throughput data generated from RNAi,
#' microarray, RNA-seq and CRISPR. The over-representation analysis is performed based on hypergeometric tests. The
#' enrichment analysis is based on the GSEA algorithm (Subramanian et al. PNAS
#' 2005). The network analysis identifies enriched subnetworks based on
#' algorithms from the BioNet package (Beisser et al., Bioinformatics 2010). A unique point of
#' this package compared to other similar packages lies in that it can deal with "Time series" data
#' with high efficiency. In addition, it can generate a dynamic Shiny report including all the results
#' in, which would be easily for users to download, modify visualizations and even share with others.
#' A pipeline is also specifically designed for CRISPR data pre-processed
#' by MAGeCK to perform integrative analyses including
#' gene set over-representation, enrichment and network analyses. The
#' users can also build their own analysis pipeline for their data based on
#' this package.
#'
#' @section Details:
#' The most important classes in this package are 'GSCA' (Gene Set Collection
#' Analyses), 'NWA' (NetWork Analyses), 'GSCABatch' (Gene Set Collection
#' Analyses for time-series data) and 'NWABatch' (NetWork Analyses for time-series data).
#' As an example, a pipeline (see function
#' 'HTSanalyzeR4MAGeCK') is developed in this package for CRISPR data preprocessed by MAGeCK.
#' Based on these four classes and other functions, users can design
#' their own pipelines specifically for their own data sets.
#'
#' Full help on classes and associated functions is available from within class
#' help pages.
#'
#' Introductory information on the use of classes and pipeline are available in
#' the vignette.
#'
#' A full listing of documented topics is available in HTML view by typing
#' help.start() and selecting the HTSanalyzeR package from the Packages menu
#' or via library(help="HTSanalyzeR2").
#'
#' @references Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert,
#'   B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R.,
#'   Lander, E. S. & Mesirov, J. P. (2005) \emph{ Gene set enrichment analysis:
#'   A knowledge-based approach for interpreting genome-wide expression
#'   profiles.} Proc. Natl. Acad. Sci. USA 102, 15545-15550.
#'
#'   Beisser D, Klau GW, Dandekar T, Muller T, Dittrich MT. BioNet: an R-Package
#'   for the functional analysis of biological networks. Bioinformatics. 2010
#'   Apr 15;26(8):1129-30.
#'
#'   Dittrich MT, Klau GW, Rosenwald A., Dandekar T and Muller T.
#'   \emph{Identifying functional modules in protein-protein interaction
#'   networks: an integrated exact approach.} Bioinformatics 2008
#'   24(13):i223-i231.
#'
#' @docType package
#' @name HTSanalyzeR2
#'
#' @useDynLib HTSanalyzeR2
#' @importFrom Rcpp sourceCpp
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