@@ -68,7 +68,6 @@ Imports:

     scran,

     Seurat (>= 3.1.3),

     shiny,

-    shinyDirectoryInput,

     shinyFiles,

     shinyWidgets,

     shinyjs,

@@ -111,9 +110,8 @@ Suggests:

     org.Mm.eg.db,

     stringr,

     harmony,

-    liger

-Remotes: 

-    joshua-d-campbell/shiny-directory-input,

+    liger,

+    shinyDirectoryInput

 VignetteBuilder: knitr

 URL: https://compbiomed.github.io/sctk_docs/

 BugReports: https://github.com/compbiomed/singleCellTK/issues

@@ -20,8 +20,9 @@

 #' Refer \code{anndata.write_h5ad} documentation for details. Default \code{NULL}.

 #' @examples

 #' data(sce_chcl, package = "scds")

+#' \dontrun{

 #' exportSCEtoAnnData(sce=sce_chcl, compression="gzip")

-#'

+#' }

 #' @export

 exportSCEtoAnnData <- function(sce,

                                 useAssay = 'counts',

@@ -13,8 +13,9 @@

 #' @param sample Name of the sample. It will be used as the prefix of file names.

 #' @examples

 #' data(sce_chcl, package = "scds")

+#' \dontrun{

 #' exportSCEtoFlatFile(sce_chcl, "sce_chcl")

-#'

+#' }

 #' @export

 #' @importFrom SummarizedExperiment colData rowData

 exportSCEtoFlatFile <- function(sce,

@@ -41,7 +41,7 @@

 #'  the relative widths for each plot.

 #' @examples

 #' data(scExample, package="singleCellTK")

-#' \donttest{

+#' \dontrun{

 #' sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")

 #' sce <- getUMAP(inSCE=sce, useAssay="counts", reducedDimName="UMAP")

 #' sce <- runPerCellQC(sce)

@@ -85,7 +85,7 @@ reportCellQC <- function(inSCE, output_file = NULL,

 #' @examples

 #' data(scExample, package = "singleCellTK")

 #' sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")

-#' \donttest{

+#' \dontrun{

 #' sce <- runDecontX(sce)

 #' sce <- getUMAP(sce)

 #' reportQCTool(inSCE = sce, algorithm = "DecontX")

@@ -21,7 +21,7 @@

 #' @examples

 #' data(scExample, package = "singleCellTK")

 #' sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")

-#' \donttest{

+#' \dontrun{

 #' sce <- runCellQC(sce)

 #' }

 #' @export

@@ -141,7 +141,7 @@ runCellQC <- function(inSCE,

 #' of \code{inSCE}.

 #' @examples

 #' data(scExample, package = "singleCellTK")

-#' \donttest{

+#' \dontrun{

 #' sce <- runDropletQC(sce)

 #' }

 #' @export

@@ -9,11 +9,10 @@

 #' @examples

 #' data(sce_chcl, package = "scds")

 #' sce_chcl <- scater_logNormCounts(sce_chcl,"logcounts", "counts")

-#' print(sce_chcl)

 scater_logNormCounts <- function(inSCE, logAssayName = "ScaterLogNormCounts", useAssay = "counts"){

   inSCE <- scater::logNormCounts(

     x = inSCE, 

     name = logAssayName,

     exprs_values = useAssay)

   return(inSCE)

-}

\ No newline at end of file

+}

@@ -8,7 +8,6 @@

 #' @examples

 #' data(sce_chcl, package = "scds")

 #' sce_chcl <- scran_modelGeneVar(sce_chcl, "counts")

-#' print(head(rowData(sce_chcl)))

 #' @importFrom SummarizedExperiment assay rowData rowData<-

 scran_modelGeneVar <- function(inSCE, assayName) {

     tempDataFrame <- data.frame(scran::modelGeneVar(assay(inSCE, assayName)))

@@ -9,8 +9,11 @@

 #' @param directory Output directory. Default is './'.

 #' @param format The format of output. It currently supports flat files, rds files

 #' and python h5 files. It can output multiple formats. Default: c("SCE", "AnnData", "FlatFile", "HTAN").

-#' @examples

-#' exportSCE(mouseBrainSubsetSCE, format = "SCE")

+#' @example

+#' data(scExample)

+#' \dontrun{

+#' exportSCE(sce, format = "SCE")

+#' }

 #' @export

 exportSCE <- function(inSCE,

                       samplename = "sample",

Binary files a/data/mouseBrainSubsetSCE.rda and b/data/mouseBrainSubsetSCE.rda differ

Binary files a/data/scExample.rda and b/data/scExample.rda differ

@@ -31,6 +31,3 @@ and python h5 files. It can output multiple formats. Default: c("SCE", "AnnData"

 \description{

 Export data in SingleCellExperiment object

 }

-\examples{

-exportSCE(mouseBrainSubsetSCE, format = "SCE")

-}

@@ -47,6 +47,7 @@ overridden at function call.

 }

 \examples{

 data(sce_chcl, package = "scds")

+\dontrun{

 exportSCEtoAnnData(sce=sce_chcl, compression="gzip")

-

+}

 }

@@ -34,6 +34,7 @@ The items in the 'metadata' slot remain stored in list and are saved in an RDS f

 }

 \examples{

 data(sce_chcl, package = "scds")

+\dontrun{

 exportSCEtoFlatFile(sce_chcl, "sce_chcl")

-

+}

 }

@@ -100,7 +100,7 @@ A wrapper function which visualizes outputs from the

 }

 \examples{

 data(scExample, package="singleCellTK")

-\donttest{

+\dontrun{

 sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")

 sce <- getUMAP(inSCE=sce, useAssay="counts", reducedDimName="UMAP")

 sce <- runPerCellQC(sce)

@@ -33,7 +33,7 @@ A  function to generate .html Rmarkdown report for the specified QC algorithm ou

 \examples{

 data(scExample, package = "singleCellTK")

 sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")

-\donttest{

+\dontrun{

 sce <- runDecontX(sce)

 sce <- getUMAP(sce)

 reportQCTool(inSCE = sce, algorithm = "DecontX")

@@ -55,7 +55,7 @@ A wrapper function to run several QC algorithms on a

 \examples{

 data(scExample, package = "singleCellTK")

 sce <- subsetSCECols(sce, colData = "type != 'EmptyDroplet'")

-\donttest{

+\dontrun{

 sce <- runCellQC(sce)

 }

 }

@@ -38,7 +38,7 @@ empty droplets in single cell RNA-seq data

 }

 \examples{

 data(scExample, package = "singleCellTK")

-\donttest{

+\dontrun{

 sce <- runDropletQC(sce)

 }

 }

@@ -28,7 +28,6 @@ Uses \link[scater]{logNormCounts} to log normalize input data

 \examples{

 data(sce_chcl, package = "scds")

 sce_chcl <- scater_logNormCounts(sce_chcl,"logcounts", "counts")

-print(sce_chcl)

 }

 \author{

 Irzam Sarfraz

@@ -22,7 +22,6 @@ Generates and stores variability data from scran::modelGeneVar in the input sing

 \examples{

 data(sce_chcl, package = "scds")

 sce_chcl <- scran_modelGeneVar(sce_chcl, "counts")

-print(head(rowData(sce_chcl)))

 }

 \author{

 Irzam Sarfraz