Hi,
Thanks for your reply. Accually, I would like to convert the codes in DESeq2/R dirrectoy like core.R, ...

############################################################
#
# DESeq2 organization of R files
#
# core.R ......... most of the statistical code (example call below)
# methods.R ...... the S4 methods (estimateSizeFactors, etc.)
# AllClasses.R ... class definitions and object constructors
# AllGenerics.R .. the generics defined in DESeq2
# results.R ...... results() function and helpers
# plots.R ........ all plotting functions
# helper.R ....... collapseReplicates, fpkm, fpm, DESeqParallel
# expanded.R ..... helpers for dealing with expanded model matrices
# RcppExports.R .. the R wrappers for the C++ functions
# rlogTransformation.R
# varianceStabilizingTransformation.R
#
# general outline of the internal function calls.
# note: not all of these functions are exported.
#
# DESeq
# |- estimateSizeFactors
#    |- estimateSizeFactorsForMatrix
# |- estimateDispersions
#    |- estimateDispersionsGeneEst
#       |- fitNbinomGLMs
#          |- fitBeta (C++)
#       |- fitDisp (C++)
#    |- estimateDispersionsFit
#    |- estimateDispersionsMAP
#       |- estimateDispersionPriorVar
#       |- fitDisp (C++)
# |- nbinomWaldTest
#    |- fitGLMsWithPrior
#       |- fitNbinomGLMs
#          |- fitBeta (C++)
#       |- estimateBetaPriorVar
#       |- fitNbinomGLMs
#          |- fitBeta (C++)
#
############################################################

#' DESeq2 package for differential analysis of count data
#'
#' The main functions for differential analysis are \code{\link{DESeq}} and
#' \code{\link{results}}. See the examples at \code{\link{DESeq}} for basic analysis steps.
#' Two transformations offered for count data are
#' the "regularized logarithm", \code{\link{rlog}},
#' and \code{\link{varianceStabilizingTransformation}}.
#' For more detailed information on usage, see the package vignette, by typing
#' \code{vignette("DESeq2")}, or the workflow linked to on the first page
#' of the vignette. All support questions should be posted to the Bioconductor
#' support site: \url{http://support.bioconductor.org}.
#'
#' @references
#'
#' DESeq2 reference:
#'
#' Michael I Love, Wolfgang Huber, Simon Anders: Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 2014, 15:550. \url{http://dx.doi.org/10.1186/s13059-014-0550-8}
#'
#' DESeq reference:
#'
#' Simon Anders, Wolfgang Huber: Differential expression analysis for sequence count data. Genome Biology 2010, 11:106. \url{http://dx.doi.org/10.1186/gb-2010-11-10-r106}
#'
#' @author Michael Love, Wolfgang Huber, Simon Anders
#'
#' @docType package
#' @name DESeq2-package
#' @aliases DESeq2-package
#' @keywords package
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