fit for check!

DESCRIPTION

@@ -2,19 +2,19 @@ Package: HTSanalyzeR2
 Type: Package
 Title: Gene set over-representation, enrichment and network analyses for high-
     throughput data and corresponding time-series data
-Version: 0.99.0 
+Version: 0.99.1
 Author: Lina ZHU, Xiupei MEI, Feng GAO, Xin WANG
-Maintainer: Lina ZHU<zhulina0609@gmail.com>, Xiupei MEI <meixiupei@gmail.com>, Feng GAO <gaofeng21cn@gmail.com>
+Maintainer: Lina ZHU<zhulina0609@gmail.com>
 Description: This package provides classes and methods for gene set over-
     representation, enrichment and network analyses on various high-throughput 
-    data as well as corresponding time-series data.
+    data as well as corresponding time-series data generated by CRISPR, RNAi, 
+    RNA-seq and micro-array.
 License: Artistic-2.0
 LazyData: TRUE
 RoxygenNote: 6.0.1
 Imports: 
     GO.db,
     cellHTS2,
-    doParallel,
     Rcpp,
     foreach,
     stringr,
@@ -67,9 +67,8 @@ Suggests:
     rmarkdown,
     testthat,
     knitr,
-    Homo.sapiens,
     org.Hs.eg.db,
-    org.Dm.eg.db,
+    doParallel,
     Biobase
 VignetteBuilder: knitr
 Depends: R(>= 3.4)

HTSanalyzeR2.Rproj

@@ -18,5 +18,5 @@ StripTrailingWhitespace: Yes
 BuildType: Package
 PackageUseDevtools: Yes
 PackageInstallArgs: --no-multiarch --with-keep.source
-PackageCheckArgs: --no-vignettes  --no-examples
+PackageCheckArgs: --no-vignettes
 PackageRoxygenize: rd,collate,namespace

NAMESPACE

@@ -11,7 +11,6 @@ export(appendGSTermsTS)
 export(cellHTS2OutputStatTests)
 export(duplicateRemover)
 export(interactomeNwaTS)
-export(networkAnalysis)
 export(preprocessGscaTS)
 export(preprocessNwaTS)
 export(reportAll)
@@ -34,7 +33,6 @@ exportMethods(viewSubNet)
 import(DT)
 import(GO.db)
 import(colourpicker)
-import(doParallel)
 import(foreach)
 import(graphics)
 importFrom(AnnotationDbi,GOID)

R/Batch_class.R

@@ -20,7 +20,6 @@
 #' @slot listOfGSCA A list of initialized GSCA object for futher GSCA.
 #' @export
 #' @examples
-#' \dontrun{
 #' data(d7, d13, d25)
 #'
 #' ## generate expInfor to describe the information of time series data
@@ -54,7 +53,6 @@
 #' gscaTS <- new("GSCABatch", expInfor = expInfor, phenotypeTS = phenotypeTS,
 #'                  listOfGeneSetCollections = ListGSC)
 #' gscaTS
-#' }
 
 
 # GSCABatch ----------------------------------------------------------------
@@ -156,7 +154,6 @@ setMethod("show", signature = "GSCABatch", function(object) {
 #' @slot interactome An object of class igraph.
 #' @slot listOfNWA A list of 'NWA' object.
 #' @examples
-#' \dontrun{
 #' data(d7, d13, d25)
 #'
 #' ## generate expInfor to describe the information of time series data
@@ -181,7 +178,6 @@ setMethod("show", signature = "GSCABatch", function(object) {
 #'
 #' ## Example2: create an object of class 'NWABatch' without phenotypes
 #' nwaTS <- new("NWABatch", expInfor = expInfor, pvalueTS = pvalueTS)
-#' }
 #' @export
 #' @aliases NWABatch
 setClass(

R/HTSanalyzeR4MAGeCK.R

@@ -59,6 +59,7 @@
 #' the results in. All the results would be stored as RData named 'results.RData' under
 #' a new automatic generated directory. It can be loaded into R by 'readRDS(results.RData)'.
 #' @examples
+#' \dontrun{
 #' data(d7)
 #'
 #' library(GO.db)
@@ -84,6 +85,7 @@
 #'                    keggGSCs=c("PW_KEGG"),
 #'                    goGSCs = c("GO_MF"),
 #'                    nwAnalysisFdr = 0.0001)
+#' }
 #' @export
 #' @importFrom methods new
 HTSanalyzeR4MAGeCK <- function(MAGeCKdata,

R/data.R

@@ -5,6 +5,14 @@
 #' refer to \href{https://sourceforge.net/p/mageck/wiki/Home/}{MAGeCK}.
 #'
 #' @aliases d13 d25
+#' @references
+#' Tzelepis K, Koike-Yusa H, De Braekeleer E, et al. A CRISPR Dropout Screen Identifies
+#' Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia. Cell Reports.
+#'  2016;17(4):1193-1205. doi:10.1016/j.celrep.2016.09.079.
+#' @examples
+#' data(d7)
+#' data(d13)
+#' data(d25)
 #'
 "d7"
 
@@ -14,6 +22,8 @@
 #' The differential expressed analysis result between CMS4 colon cancer subtype and
 #' non-CMS4 of a gene expression dataset with GEO number-"GSE33113" using R package \emph{limma}.
 #'
+#' @examples
+#' data(GSE33113_limma)
 #'
 "GSE33113_limma"
 
@@ -22,22 +32,25 @@
 #'
 #' An object of class 'GSCA' generated by \emph{HTSanalyzeR2}.
 #'
-#'
+#' @examples
+#' data(d7_gsca)
 "d7_gsca"
 
 
 #' A list of 'GSCA' object
 #'
 #' A list of 'GSCA' object generated by time-series analysis using \emph{HTSanalyzeR2}.
 #'
-#'
+#' @examples
+#' data(gscaTS)
 "gscaTS"
 
 
 #' An object of class 'NWA'
 #'
 #' An object of class 'NWA' generated by \emph{HTSanalyzeR2}.
-#'
+#' @examples
+#' data(d7_nwa)
 #'
 "d7_nwa"
 
@@ -46,15 +59,17 @@
 #'
 #' A list of 'NWA' object generated by time-series analysis using \emph{HTSanalyzeR2}.
 #'
-#'
+#' @examples
+#' data(nwaTS)
 "nwaTS"
 
 
 #' An interactome matrix for \emph{Homo Sapiens}
 #'
 #' An interactome matrix for \emph{Homo Sapiens}.
 #'
-#'
+#' @examples
+#' data(Biogrid_HS_Mat)
 "Biogrid_HS_Mat"
 
 
@@ -63,11 +78,14 @@
 #' An object of class 'igraph' built from the interactome data set for
 #' \emph{Homo Sapiens} downloaded from the \emph{BioGRID} database.
 #'
+#' @examples
+#' data(Biogrid_HS_Interactome)
 "Biogrid_HS_Interactome"
 
 
 #' An object of class 'cellHTS2'
 #'
 #' An object of class 'cellHTS2' which has been normalized, configured and annotated.
-#'
+#' @examples
+#' data(xn)
 "xn"

R/gscaTS.R

@@ -133,7 +133,11 @@ preprocessGscaTS <- function(object, species="Hs", initialIDs="SYMBOL",
 #'                            orderAbsValue=FALSE)
 #'
 #' ## support parallel calculation using doParallel package
+#' if (requireNamespace("doParallel", quietly=TRUE)) {
 #' doParallel::registerDoParallel(cores=2)
+#' } else {
+#'   ## code when "doParallel" is not available
+#' }
 #'
 #' ## do hypergeometric tests and GSEA
 #' gscaTS2 <- analyzeGscaTS(gscaTS1, para=list(pValueCutoff=0.05, pAdjustMethod="BH",
@@ -203,7 +207,11 @@ analyzeGscaTS <- function(gscaList, para=list(pValueCutoff=0.05, pAdjustMethod="
 #'                            orderAbsValue=FALSE)
 #'
 #' ## support parallel calculation using doParallel package
-#' doParallel::registerDoParallel(cores=4)
+#' if (requireNamespace("doParallel", quietly=TRUE)) {
+#' doParallel::registerDoParallel(cores=2)
+#' } else {
+#'   ## code when "doParallel" is not available
+#' }
 #'
 #' ## do hypergeometric tests and GSEA
 #' gscaTS2 <- analyzeGscaTS(gscaTS1, para=list(pValueCutoff=0.05, pAdjustMethod="BH",
@@ -212,8 +220,10 @@ analyzeGscaTS <- function(gscaList, para=list(pValueCutoff=0.05, pAdjustMethod="
 #' head(gscaTS2[[1]]@@result$GSEA.results$GO_BP, 3)
 #'
 #' ## append gene set terms to results
+#' \dontrun{
 #' gscaTS3 <- appendGSTermsTS(gscaTS2, goGSCs=c("GO_BP"))
 #' head(gscaTS3[[1]]@@result$GSEA.results$GO_BP, 3)
+#' }
 appendGSTermsTS <- function(gscaList, keggGSCs=NULL, goGSCs=NULL, msigdbGSCs=NULL){
              paraCheck("gscaTS", "gscaList", gscaList)
              tmpName <- names(gscaList)

R/gsca_analyze.R

@@ -72,7 +72,11 @@ if (!isGeneric("analyze")) {
 #'                     duplicateRemoverMethod="max", orderAbsValue=FALSE)
 #'
 #' ## support parallel calculation using doParallel package
+#' if (requireNamespace("doParallel", quietly=TRUE)) {
 #' doParallel::registerDoParallel(cores=2)
+#' } else {
+#'   ## code when "doParallel" is not available
+#' }
 #'
 #' ## do hypergeometric tests and GSEA
 #' gsca2 <- analyze(gsca1, para=list(pValueCutoff=0.01, pAdjustMethod ="BH",
@@ -457,7 +461,6 @@ calcHGTScore <- function(geneSet, universe, hits) {
 
 #' @import foreach
 #' @importFrom  stats p.adjust
-#' @import doParallel
 calcGSEA <-
   function(listOfGeneSetCollections,
            geneList,

R/gsca_class.R

@@ -33,7 +33,6 @@
 #'
 #' @export
 #' @examples
-#' \dontrun{
 #' library(org.Hs.eg.db)
 #' library(GO.db)
 #' ## load data for enrichment analyses
@@ -57,7 +56,6 @@
 #' gsca <- new("GSCA", listOfGeneSetCollections = ListGSC, geneList = phenotype)
 #' gsca
 #' gsca@@summary
-#' }
 
 setClass(
   Class = "GSCA",

R/gsca_enrichmap.R

@@ -380,14 +380,16 @@ setMethod("extractEnrichMap", signature = "GSCA",
 #' data(d7_gsca)
 #'
 #' ## Example1: view an enrichment map for top 7 significant 'GO_MF' gene sets of GSEA results
+#' \dontrun{
 #' viewEnrichMap(d7_gsca, resultName = "GSEA.results", gscs=c("GO_MF"),
 #'               allSig = FALSE, ntop = 7, gsNameType = "term")
-#'
+#' }
 #' ## Example2: view an enrichment map for top 7 significant 'GO_MF'
 #' ## and 'PW_KEGG' gene sets of GSEA results
+#' \dontrun{
 #' viewEnrichMap(d7_gsca, resultName = "GSEA.results", gscs=c("GO_MF", "PW_KEGG"),
 #'               allSig = FALSE, ntop = 7, gsNameType = "term")
-#'
+#' }
 #' ## Example3: view an enrichment map with specificGenesets in 'GO_MF' gene sets of GSEA results
 #' ## As told previously, specificGeneset needs to be a subset of all analyzed gene sets
 #' ## which can be roughly gotten by:
@@ -397,10 +399,11 @@ setMethod("extractEnrichMap", signature = "GSCA",
 #' GO_MF_geneset <- tmp$GO_MF[c(4,2,6,9,12)]
 #' ## the name of specificGenesets also needs to match with the names of tmp
 #' specificGeneset <- list("GO_MF"=GO_MF_geneset)
+#' \dontrun{
 #' viewEnrichMap(d7_gsca, resultName = "GSEA.results", gscs=c("GO_MF"),
 #'               allSig = FALSE, gsNameType = "term",
 #'               ntop = NULL, specificGeneset = specificGeneset)
-#'
+#' }
 #'
 #' ## Example4: view an enrichment map with specificGenesets in 'GO_MF'
 #' ## and 'PW_KEGG' gene sets of GSEA results
@@ -409,9 +412,11 @@ setMethod("extractEnrichMap", signature = "GSCA",
 #' GO_MF_geneset <- tmp$GO_MF[c(6,3,5,9,12)]
 #' PW_KEGG_geneset <- tmp$PW_KEGG[c(7,2,5,1,9)]
 #' specificGeneset <- list("GO_MF"=GO_MF_geneset, "PW_KEGG"=PW_KEGG_geneset)
+#' \dontrun{
 #' viewEnrichMap(d7_gsca, resultName = "GSEA.results", gscs=c("GO_MF", "PW_KEGG"),
 #'               allSig = FALSE, gsNameType = "term",
 #'               ntop = NULL, specificGeneset = specificGeneset)
+#' }
 #' @export
 #' @references
 #' Merico D, Isserlin R, Stueker O, Emili A, Bader GD (2010) Enrichment Map:

R/gsca_preprocess.R

@@ -304,17 +304,17 @@ duplicateRemover <- function(geneList, method = "max") {
 #' @return The same data vector/matrix but with names/row names converted.
 #'
 #' @examples
-#' library(org.Dm.eg.db)
+#' library(org.Hs.eg.db)
 #' ## Example1: convert a named vector
 #' x <- runif(10)
-#' names(x) <- names(as.list(org.Dm.egSYMBOL2EG))[1:10]
-#' xEntrez <- annotationConvertor(geneList=x, species="Dm", initialIDs="SYMBOL",
+#' names(x) <- names(as.list(org.Hs.egSYMBOL2EG))[1:10]
+#' xEntrez <- annotationConvertor(geneList=x, species="Hs", initialIDs="SYMBOL",
 #'                                finalIDs="ENTREZID")
 #'
 #' ## Example2: convert a data matrix with row names as gene ids
 #' x <- cbind(runif(10),runif(10))
-#' rownames(x) <- names(as.list(org.Dm.egSYMBOL2EG))[1:10]
-#' xEntrez <- annotationConvertor(geneList=x, species="Dm", initialIDs="SYMBOL",
+#' rownames(x) <- names(as.list(org.Hs.egSYMBOL2EG))[1:10]
+#' xEntrez <- annotationConvertor(geneList=x, species="Hs", initialIDs="SYMBOL",
 #'                                finalIDs="ENTREZID")
 #' @export
 #' @importFrom AnnotationDbi mapIds columns

R/gsca_report.R

@@ -30,13 +30,14 @@ if (!isGeneric("report")) {
 #' @return in the end, this function would generate a shiny report.
 #' @examples
 #' # =======================================================
-#' \dontrun{
 #' # GSCA class
 #' ## load a GSCA object(see the examples of analyze GSCA for details)
 #' data(d7_gsca)
 #'
 #' ## Example1: report d7_gsca
+#' \dontrun{
 #' report(d7_gsca)
+#' }
 #'
 #' ## Example2: report d7_gsca containing enrichment map with specificGeneset
 #' tmp <- getTopGeneSets(d7_gsca, resultName = "GSEA.results", gscs=c("GO_MF"),
@@ -45,6 +46,7 @@ if (!isGeneric("report")) {
 #' GO_MF_geneset <- tmp$GO_MF[c(4,2,6,9,12)]
 #' ## the name of specificGenesets also needs to match with the names of tmp
 #' specificGeneset <- list("GO_MF"=GO_MF_geneset)
+#' \dontrun{
 #' report(d7_gsca, specificGeneset=specificGeneset)
 #' }
 #' @rdname report
@@ -74,7 +76,7 @@ setMethod("report", signature = "GSCA",
 #' @export
 #' @return in the end, this function would generate a shiny report.
 #' @examples
-#' \donttest{
+#' \dontrun{
 #' ## load data
 #' data(d7_gsca, d7_nwa, gscaTS, nwaTS)
 #'

R/gsca_view.R

@@ -32,7 +32,9 @@ if(!isGeneric("plotGSEA"))
 #' topGS_GO_MF <- getTopGeneSets(d7_gsca, "GSEA.results", gscs = "GO_MF", allSig=TRUE)
 #'
 #' ## view GSEA results for one gene set
+#' \dontrun{
 #' viewGSEA(d7_gsca, "GO_MF", topGS_GO_MF[["GO_MF"]][1])
+#' }
 #' @include gsca_class.R
 #' @export
 setMethod(
@@ -91,7 +93,9 @@ setMethod(
 #' summarize(d7_gsca)
 #'
 #' ## plot  significant gene sets in GO_MF and PW_KEGG
+#' \dontrun{
 #' plotGSEA(d7_gsca, gscs=c("GO_MF","PW_KEGG"), ntop=3, filepath=".")
+#' }
 #' @export
 ##plot GSEA for GSCA
 setMethod(