R/DESnowball-package.r

In snowball-project/DESnowball: Bagging with Distance-based Regression for Differential Gene Expression Analyses

#' A R package implemented Snowball approach (see references)
#' 
#' Genome-wide differential gene expression analysis with respect to the presence of a recurrent genetic disturbance (a driver mutation)  
#' 
#' The DESnowball package implements a differential gene expression analysis tool that compares the whole genome gene 
#' expression profiles on samples relative to the presence of a recurrent genetic disturbance (driver mutation).
#' 
#' The input data for the snowball analysis are the profiling of the whole genome gene expression 
#' and the mutation status of a recurrent genetic event on a group of samples. The analysis has 
#' been tested on human primary tumor samples and the minimum sample size required per group is three. 
#' Snowball does not require a balanced design between groups (see references).
#'
#' The main function of the package is \code{\link{snowball}}, it requires two input 
#' data, named \code{y} and \code{X}, where \code{y} is a binary vector 
#' indicating the mutation status of the samples, and \code{X} is the gene expression
#' profiles with rows corresponding to genes and columns the samples. \code{y} can be
#' a \code{numerical}, \code{character} or \code{logical} vector. It can also be a
#' factor. The typical format is a character vector with two values indicating the
#' the mutation status of each subject. \code{X} is expected to be a \link{data.frame} with gene names as 
#' its row names, and typically it is after the initial filtering and in log scale. A reasonable
#' choice for the initial filtering could be based on the variation of gene expression  
#' across all the samples in the study, e.g., using the coefficient of variation of each gene
#' to select the ones with greater values than a given cutoff.
#' 
#' The other functions include \code{\link{plotJn}} for visualizing gene selection, 
#' \code{\link{select.features}} for gene ranking and statistical significance assessment, 
#' and \code{\link{toplist}} to report the top genes based on the user provided cutoff.
#' 
#' @name DESnowball-package
#' @docType package
#' @import clue MASS cluster parallel combinat 
#' @references
#' Xu, Y. and Sun, J. (2005) PfCluster: a new cluster analysis procedure for gene expression profiles. Presented at a conference on Nonparametric Inference and Probability With Applications to Science honoring Michael Woodroofe; September 24-25, 2005; Ann Arbor, Mich, 2005. 
#'
#' McArdlei, B.H. and Anderson, M.J. (2001) Fitting multivariate models to community data: A comment on distance-based redundancy analysis. Ecology 82(1): 290-297.
#'
#' Xu, Y., Guo, X., Sun, J. and Zhao. Z. Snowball: resampling combined with distance-based regression to discover transcriptional consequences of driver mutation, manuscript.
#'
#' Guo, X., Xu, Y. and Zhao, Z.. Driver mutation BRAF regulates cell proliferation and apoptosis via MITF in the pathogenesis of melanoma, manuscript.
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