@@ -102,7 +102,8 @@

 #'  object. Can be one of "Matrix" (as returned by

 #'  \link{readMM} function), or "matrix" (as returned by

 #'  \link[base]{matrix} function). Default \code{"Matrix"}.

-

+#' @param rowNamesDedup Boolean. Whether to deduplicate rownames. Default 

+#'  \code{TRUE}.

 #' @details

 #' \code{importDropEst} expects either raw counts matrix stored as "cm_raw" or filtered

 #' counts matrix stored as "cm" in the DropEst rds output.

@@ -125,7 +126,8 @@ importDropEst <- function(sampleDirs = NULL,

                           rdsFileName = 'cell.counts',

                           sampleNames = NULL,

                           delayedArray = FALSE,

-                          class = c("Matrix", "matrix")) {

+                          class = c("Matrix", "matrix"),

+                          rowNamesDedup = TRUE) {

   dataType <- match.arg(dataType)

   class <- match.arg(class)

@@ -145,6 +147,15 @@ importDropEst <- function(sampleDirs = NULL,

     res[[i]] <- scei

   }

   sce <- do.call(SingleCellExperiment::cbind, res)

+  

+  if (isTRUE(rowNamesDedup)) {

+    if (any(duplicated(rownames(sce)))) {

+      message("Duplicated gene names found, adding '-1', '-2', ",

+              "... suffix to them.")

+    }

+    sce <- dedupRowNames(sce)

+  }

+  

   return(sce)

 }

@@ -42,7 +42,8 @@

                                  dataType,

                                  rdsFileName,

                                  sampleName = 'sample',

-                                 delayedArray = FALSE){

+                                 delayedArray = FALSE,

+                                 class){

   ## Read DropEst RDS

   dropEst_rds <- .readDropEstFile(sampleDir,dataType,rdsFileName)

   if (dataType == 'filtered' && 'cm' %in% names(dropEst_rds)) {

@@ -53,9 +54,15 @@

     stop("No counts matrix found in the .rds provided! Exiting.")

   }

+  if (class == "Matrix") {

+    counts_matrix <- .convertToMatrix(counts_matrix)

+  } else if (class == "matrix") {

+    counts_matrix <- base::as.matrix(counts_matrix)

+  }

+

   if (isTRUE(delayedArray)) {

     counts_matrix <- DelayedArray::DelayedArray(counts_matrix)

-    }

+  }

   ## Create SingleCellExperiment object

   ## Add SCE ColData. If using filtered counts matrix, colData is subset to include filtered cells.

   ## append sample name to cells in SCE

@@ -91,6 +98,11 @@

 #' @param rdsFileName File name prefix of the DropEst RDS output. default is "cell.counts"

 #' @param delayedArray Boolean. Whether to read the expression matrix as

 #'  \link{DelayedArray} object or not. Default \code{FALSE}.

+#' @param class Character. The class of the expression matrix stored in the SCE

+#'  object. Can be one of "Matrix" (as returned by

+#'  \link{readMM} function), or "matrix" (as returned by

+#'  \link[base]{matrix} function). Default \code{"Matrix"}.

+

 #' @details

 #' \code{importDropEst} expects either raw counts matrix stored as "cm_raw" or filtered

 #' counts matrix stored as "cm" in the DropEst rds output.

@@ -112,8 +124,10 @@ importDropEst <- function(sampleDirs = NULL,

                           dataType = c('filtered','raw'),

                           rdsFileName = 'cell.counts',

                           sampleNames = NULL,

-                          delayedArray = FALSE) {

+                          delayedArray = FALSE,

+                          class = c("Matrix", "matrix")) {

   dataType <- match.arg(dataType)

+  class <- match.arg(class)

   if (length(sampleDirs)!=length(sampleNames)){

     stop("Please provide sample names for all input directories")

@@ -126,7 +140,8 @@ importDropEst <- function(sampleDirs = NULL,

                          sampleName = sampleNames[[i]],

                          dataType = dataType,

                          rdsFileName = rdsFileName,

-                         delayedArray = delayedArray)

+                         delayedArray = delayedArray,

+                         class = class)

     res[[i]] <- scei

   }

   sce <- do.call(SingleCellExperiment::cbind, res)

@@ -91,7 +91,7 @@

 #' @param dataType can be "filtered" or "raw". Default \code{"filtered"}.

 #' @param rdsFileName File name prefix of the DropEst RDS output. default is "cell.counts"

 #' @param delayedArray Boolean. Whether to read the expression matrix as

-#'  \link{DelayedArray} object or not. Default \code{TRUE}.

+#'  \link{DelayedArray} object or not. Default \code{FALSE}.

 #' @details

 #' \code{importDropEst} expects either raw counts matrix stored as "cm_raw" or filtered

 #' counts matrix stored as "cm" in the DropEst rds output.

@@ -114,7 +114,7 @@ importDropEst <- function(sampleDirs = NULL,

                           dataType = c('filtered','raw'),

                           rdsFileName = 'cell.counts',

                           sampleNames = NULL,

-                          delayedArray = TRUE) {

+                          delayedArray = FALSE) {

   dataType <- match.arg(dataType)

   if (length(sampleDirs)!=length(sampleNames)){

@@ -91,7 +91,7 @@

 #' @param dataType can be "filtered" or "raw". Default \code{"filtered"}.

 #' @param rdsFileName File name prefix of the DropEst RDS output. default is "cell.counts"

 #' @param delayedArray Boolean. Whether to read the expression matrix as

-#'  \link[DelayedArray]{DelayedArray} object or not. Default \code{TRUE}.

+#'  \link{DelayedArray} object or not. Default \code{TRUE}.

 #' @details

 #' \code{importDropEst} expects either raw counts matrix stored as "cm_raw" or filtered

 #' counts matrix stored as "cm" in the DropEst rds output.

@@ -1,141 +1,141 @@

-

-.readDropEstFile <- function(sampleDir, dataType,rdsFileName){

-  dropEst_cell_counts <- file.path(sampleDir, paste(rdsFileName, '.rds', sep=''))

-  if (!file.exists(dropEst_cell_counts)){

-    stop("DropEst output not found at location specified. Please check path provided and/or filename.")

-  }

-  dropEst_rds <- readRDS(dropEst_cell_counts)

-

-  return(dropEst_rds)

-}

-

-.constructColdata <- function(dropEst_rds,counts_matrix, dataType){

-  coldata_fields <- c("mean_reads_per_umi","aligned_reads_per_cell","aligned_umis_per_cell","requested_umis_per_cb","requested_reads_per_cb")

-  coldata_df <-  list()

-  for (field in coldata_fields){

-    if (field %in% names(dropEst_rds)){

-      coldata_field_df <- data.frame(as.matrix(dropEst_rds[[field]]))

-      names(coldata_field_df)[1] <- field

-      coldata_field_df$cell <- row.names(coldata_field_df)

-

-      coldata_df[[field]] <- coldata_field_df

-    }}

-  coldata_df_merged <- Reduce(function(x, y) merge(x, y, all=TRUE,by="cell"), coldata_df)

-  row.names(coldata_df_merged) <- coldata_df_merged$cell

-  coldata_df_merged <- S4Vectors::DataFrame(as.matrix(coldata_df_merged))

-  if (dataType == 'filtered'){

-    coldata_df_merged <- coldata_df_merged[coldata_df_merged$cell %in% colnames(counts_matrix),]

-  }

-  return(coldata_df_merged)

-}

-

-.extractMetadata <- function(dropEst_rds){

-  metadata_fields <- c("saturation_info","merge_targets","reads_per_umi_per_cell")

-  metadata <- c()

-  for (md in metadata_fields){

-    if (md %in% names(dropEst_rds)){

-      metadata[[md]] <- dropEst_rds[[md]]

-    }}

-  return(metadata)

-}

-

-.importDropEstSample <- function(sampleDir = './',

-                                 dataType,

-                                 rdsFileName,

-                                 sampleName = 'sample',

-                                 delayedArray = FALSE){

-  ## Read DropEst RDS

-  dropEst_rds <- .readDropEstFile(sampleDir,dataType,rdsFileName)

-  if (dataType == 'filtered' && 'cm' %in% names(dropEst_rds)) {

-    counts_matrix <- dropEst_rds$cm

-  } else if (dataType == 'raw' && 'cm_raw' %in% names(dropEst_rds)) {

-    counts_matrix <- dropEst_rds$cm_raw

-  } else {

-    stop("No counts matrix found in the .rds provided! Exiting.")

-  }

-

-  if (isTRUE(delayedArray)) {

-    counts_matrix <- DelayedArray::DelayedArray(counts_matrix)

-    }

-  ## Create SingleCellExperiment object

-  ## Add SCE ColData. If using filtered counts matrix, colData is subset to include filtered cells.

-  ## append sample name to cells in SCE

-  sce <- SingleCellExperiment::SingleCellExperiment(assays = list(counts = counts_matrix))

-  colnames(sce) <- paste0(sampleName,"_",colnames(sce))

-  sce_coldata <- .constructColdata(dropEst_rds, counts_matrix, dataType)

-  row.names(sce_coldata) <- paste0(sampleName,"_",row.names(sce_coldata))

-

-  if (dim(counts_matrix)[2] == dim(sce_coldata)[1]){

-    SummarizedExperiment::colData(sce) <- sce_coldata

-  } else {

-    warning("Unable to add ColData to SCE. nCol of Counts Matrix not equal to nRow of ColData matrix.")

-  }

-

-  ## Add SCE metadata

-  sce_metadata <- .extractMetadata(dropEst_rds)

-  sce@metadata$dropEst <- sce_metadata

-  

-  return(sce)

-}

-

-#' @name importDropEst

-#' @rdname importDropEst

-#' @title Create a SingleCellExperiment Object from DropEst output

-#' @description imports the RDS file created by DropEst (https://github.com/hms-dbmi/dropEst) and

-#' create a SingleCellExperiment object from either the raw or filtered counts matrix.

-#' Additionally parse through the RDS to obtain appropriate feature annotations as

-#' SCE coldata, in addition to any metadata.

-#' @param sampleDirs  A path to the directory containing the data files. Default "./".

-#' @param sampleNames A User-defined sample name. This will be prepended to all cell barcode IDs.

-#'  Default "sample".

-#' @param dataType can be "filtered" or "raw". Default \code{"filtered"}.

-#' @param rdsFileName File name prefix of the DropEst RDS output. default is "cell.counts"

-#' @param delayedArray Boolean. Whether to read the expression matrix as

-#'  \link[DelayedArray]{DelayedArray} object or not. Default \code{TRUE}.

-#' @details

-#' \code{importDropEst} expects either raw counts matrix stored as "cm_raw" or filtered

-#' counts matrix stored as "cm" in the DropEst rds output.

-#' ColData is obtained from the DropEst corresponding to "mean_reads_per_umi","aligned_reads_per_cell",

-#' "aligned_umis_per_cell","requested_umis_per_cb","requested_reads_per_cb"

-#' If using filtered counts matrix, the colData dataframe is

-#' subset to contain features from the filtered counts matrix alone.

-#' If any annotations of ("saturation_info","merge_targets","reads_per_umi_per_cell") are

-#' found in the DropEst rds, they will be added to the SCE metadata field

-#' @return A \code{SingleCellExperiment} object containing the count matrix,

-#'  the feature annotations from DropEst as ColData, and any metadata from DropEst

-#' @examples

-#' # Example results were generated as per instructions from the developers of dropEst described in

-#' # https://github.com/hms-dbmi/dropEst/blob/master/examples/EXAMPLES.md

-#' sce <- importDropEst(sampleDirs = system.file("extdata/dropEst_scg71", package = "singleCellTK"),

-#'                      sampleNames = 'scg71')

-

-#' @export

-importDropEst <- function(sampleDirs = NULL,

-                          dataType = c('filtered','raw'),

-                          rdsFileName = 'cell.counts',

-                          sampleNames = NULL,

-                          delayedArray = TRUE) {

-  dataType <- match.arg(dataType)

-

-  if (length(sampleDirs)!=length(sampleNames)){

-    stop("Please provide sample names for all input directories")

-  }

-

-  res <- vector("list", length = length(sampleDirs))

-

-  for (i in seq_along(sampleDirs)){

-    scei <- .importDropEstSample(sampleDir = sampleDirs[[i]],

-                         sampleName = sampleNames[[i]],

-                         dataType = dataType,

-                         rdsFileName = rdsFileName,

-                         delayedArray = delayedArray)

-    res[[i]] <- scei

-  }

-  sce <- do.call(SingleCellExperiment::cbind, res)

-  return(sce)

-}

-

-

-

-

-

+

+.readDropEstFile <- function(sampleDir, dataType,rdsFileName){

+  dropEst_cell_counts <- file.path(sampleDir, paste(rdsFileName, '.rds', sep=''))

+  if (!file.exists(dropEst_cell_counts)){

+    stop("DropEst output not found at location specified. Please check path provided and/or filename.")

+  }

+  dropEst_rds <- readRDS(dropEst_cell_counts)

+

+  return(dropEst_rds)

+}

+

+.constructColdata <- function(dropEst_rds,counts_matrix, dataType){

+  coldata_fields <- c("mean_reads_per_umi","aligned_reads_per_cell","aligned_umis_per_cell","requested_umis_per_cb","requested_reads_per_cb")

+  coldata_df <-  list()

+  for (field in coldata_fields){

+    if (field %in% names(dropEst_rds)){

+      coldata_field_df <- data.frame(as.matrix(dropEst_rds[[field]]))

+      names(coldata_field_df)[1] <- field

+      coldata_field_df$cell <- row.names(coldata_field_df)

+

+      coldata_df[[field]] <- coldata_field_df

+    }}

+  coldata_df_merged <- Reduce(function(x, y) merge(x, y, all=TRUE,by="cell"), coldata_df)

+  row.names(coldata_df_merged) <- coldata_df_merged$cell

+  coldata_df_merged <- S4Vectors::DataFrame(as.matrix(coldata_df_merged))

+  if (dataType == 'filtered'){

+    coldata_df_merged <- coldata_df_merged[coldata_df_merged$cell %in% colnames(counts_matrix),]

+  }

+  return(coldata_df_merged)

+}

+

+.extractMetadata <- function(dropEst_rds){

+  metadata_fields <- c("saturation_info","merge_targets","reads_per_umi_per_cell")

+  metadata <- c()

+  for (md in metadata_fields){

+    if (md %in% names(dropEst_rds)){

+      metadata[[md]] <- dropEst_rds[[md]]

+    }}

+  return(metadata)

+}

+

+.importDropEstSample <- function(sampleDir = './',

+                                 dataType,

+                                 rdsFileName,

+                                 sampleName = 'sample',

+                                 delayedArray = FALSE){

+  ## Read DropEst RDS

+  dropEst_rds <- .readDropEstFile(sampleDir,dataType,rdsFileName)

+  if (dataType == 'filtered' && 'cm' %in% names(dropEst_rds)) {

+    counts_matrix <- dropEst_rds$cm

+  } else if (dataType == 'raw' && 'cm_raw' %in% names(dropEst_rds)) {

+    counts_matrix <- dropEst_rds$cm_raw

+  } else {

+    stop("No counts matrix found in the .rds provided! Exiting.")

+  }

+

+  if (isTRUE(delayedArray)) {

+    counts_matrix <- DelayedArray::DelayedArray(counts_matrix)

+    }

+  ## Create SingleCellExperiment object

+  ## Add SCE ColData. If using filtered counts matrix, colData is subset to include filtered cells.

+  ## append sample name to cells in SCE

+  sce <- SingleCellExperiment::SingleCellExperiment(assays = list(counts = counts_matrix))

+  colnames(sce) <- paste0(sampleName,"_",colnames(sce))

+  sce_coldata <- .constructColdata(dropEst_rds, counts_matrix, dataType)

+  row.names(sce_coldata) <- paste0(sampleName,"_",row.names(sce_coldata))

+

+  if (dim(counts_matrix)[2] == dim(sce_coldata)[1]){

+    SummarizedExperiment::colData(sce) <- sce_coldata

+  } else {

+    warning("Unable to add ColData to SCE. nCol of Counts Matrix not equal to nRow of ColData matrix.")

+  }

+

+  ## Add SCE metadata

+  sce_metadata <- .extractMetadata(dropEst_rds)

+  sce@metadata$dropEst <- sce_metadata

+  

+  return(sce)

+}

+

+#' @name importDropEst

+#' @rdname importDropEst

+#' @title Create a SingleCellExperiment Object from DropEst output

+#' @description imports the RDS file created by DropEst (https://github.com/hms-dbmi/dropEst) and

+#' create a SingleCellExperiment object from either the raw or filtered counts matrix.

+#' Additionally parse through the RDS to obtain appropriate feature annotations as

+#' SCE coldata, in addition to any metadata.

+#' @param sampleDirs  A path to the directory containing the data files. Default "./".

+#' @param sampleNames A User-defined sample name. This will be prepended to all cell barcode IDs.

+#'  Default "sample".

+#' @param dataType can be "filtered" or "raw". Default \code{"filtered"}.

+#' @param rdsFileName File name prefix of the DropEst RDS output. default is "cell.counts"

+#' @param delayedArray Boolean. Whether to read the expression matrix as

+#'  \link[DelayedArray]{DelayedArray} object or not. Default \code{TRUE}.

+#' @details

+#' \code{importDropEst} expects either raw counts matrix stored as "cm_raw" or filtered

+#' counts matrix stored as "cm" in the DropEst rds output.

+#' ColData is obtained from the DropEst corresponding to "mean_reads_per_umi","aligned_reads_per_cell",

+#' "aligned_umis_per_cell","requested_umis_per_cb","requested_reads_per_cb"

+#' If using filtered counts matrix, the colData dataframe is

+#' subset to contain features from the filtered counts matrix alone.

+#' If any annotations of ("saturation_info","merge_targets","reads_per_umi_per_cell") are

+#' found in the DropEst rds, they will be added to the SCE metadata field

+#' @return A \code{SingleCellExperiment} object containing the count matrix,

+#'  the feature annotations from DropEst as ColData, and any metadata from DropEst

+#' @examples

+#' # Example results were generated as per instructions from the developers of dropEst described in

+#' # https://github.com/hms-dbmi/dropEst/blob/master/examples/EXAMPLES.md

+#' sce <- importDropEst(sampleDirs = system.file("extdata/dropEst_scg71", package = "singleCellTK"),

+#'                      sampleNames = 'scg71')

+

+#' @export

+importDropEst <- function(sampleDirs = NULL,

+                          dataType = c('filtered','raw'),

+                          rdsFileName = 'cell.counts',

+                          sampleNames = NULL,

+                          delayedArray = TRUE) {

+  dataType <- match.arg(dataType)

+

+  if (length(sampleDirs)!=length(sampleNames)){

+    stop("Please provide sample names for all input directories")

+  }

+

+  res <- vector("list", length = length(sampleDirs))

+

+  for (i in seq_along(sampleDirs)){

+    scei <- .importDropEstSample(sampleDir = sampleDirs[[i]],

+                         sampleName = sampleNames[[i]],

+                         dataType = dataType,

+                         rdsFileName = rdsFileName,

+                         delayedArray = delayedArray)

+    res[[i]] <- scei

+  }

+  sce <- do.call(SingleCellExperiment::cbind, res)

+  return(sce)

+}

+

+

+

+

+

@@ -83,9 +83,10 @@

 #' @title Create a SCE Object from DropEst output

 #' @description imports the RDS file created by DropEst and

 #' creates a \link[SingleCellExperiment]{SingleCellExperiment} object from either the raw or filtered counts matrix.

-#' @param sampleDirs  A path to the directory containing the data files. Default "./".

-#' @param sampleNames A User-defined sample name. This will be prepended to all cell barcode IDs.

-#'  Default "sample".

+#' @param sampleDirs  a vector of paths to the sample directories containing the cell.counts.rds file. 

+#' Default is current working directory. 

+#' @param sampleNames a vector of  sample names corresponding to the sample directories.

+#' Default "sample". The sample name will be prepended to cell barcode IDs. 

 #' @param dataType can be "filtered" or "raw". Default \code{"filtered"}.

 #' @param rdsFileName File name prefix of the DropEst RDS output. default is "cell.counts"

 #' @param delayedArray Boolean. Whether to read the expression matrix as

@@ -80,11 +80,9 @@

 #' @name importDropEst

 #' @rdname importDropEst

-#' @title Create a SingleCellExperiment Object from DropEst output

-#' @description imports the RDS file created by DropEst (https://github.com/hms-dbmi/dropEst) and

-#' create a SingleCellExperiment object from either the raw or filtered counts matrix.

-#' Additionally parse through the RDS to obtain appropriate feature annotations as

-#' SCE coldata, in addition to any metadata.

+#' @title Create a SCE Object from DropEst output

+#' @description imports the RDS file created by DropEst and

+#' creates a \link[SingleCellExperiment]{SingleCellExperiment} object from either the raw or filtered counts matrix.

 #' @param sampleDirs  A path to the directory containing the data files. Default "./".

 #' @param sampleNames A User-defined sample name. This will be prepended to all cell barcode IDs.

 #'  Default "sample".

@@ -73,7 +73,7 @@

   ## Add SCE metadata

   sce_metadata <- .extractMetadata(dropEst_rds)

-  metadata(sce) <- sce_metadata

+  sce@metadata$dropEst <- sce_metadata

   return(sce)

 }

@@ -103,6 +103,12 @@

 #' found in the DropEst rds, they will be added to the SCE metadata field

 #' @return A \code{SingleCellExperiment} object containing the count matrix,

 #'  the feature annotations from DropEst as ColData, and any metadata from DropEst

+#' @examples

+#' # Example results were generated as per instructions from the developers of dropEst described in

+#' # https://github.com/hms-dbmi/dropEst/blob/master/examples/EXAMPLES.md

+#' sce <- importDropEst(sampleDirs = system.file("extdata/dropEst_scg71", package = "singleCellTK"),

+#'                      sampleNames = 'scg71')

+

 #' @export

 importDropEst <- function(sampleDirs = NULL, 

                           dataType = c('filtered','raw'),

@@ -43,7 +43,7 @@

                                  dataType, 

                                  rdsFileName, 

                                  sampleName = 'sample',

-                                 delayedArray = delayedArrary){

+                                 delayedArray = FALSE){

   ## Read DropEst RDS

   dropEst_rds <- .readDropEstFile(sampleDir,dataType,rdsFileName)

   if (dataType == 'filtered' && 'cm' %in% names(dropEst_rds)) {

@@ -85,10 +85,10 @@

 #' create a SingleCellExperiment object from either the raw or filtered counts matrix.

 #' Additionally parse through the RDS to obtain appropriate feature annotations as 

 #' SCE coldata, in addition to any metadata.

-#' @param sampleDir  A path to the directory containing the data files. Default "./".

-#' @param sampleName A User-defined sample name. This will be prepended to all cell barcode IDs.

+#' @param sampleDirs  A path to the directory containing the data files. Default "./".

+#' @param sampleNames A User-defined sample name. This will be prepended to all cell barcode IDs.

 #'  Default "sample".

-#'  @param dataType can be "filtered" or "raw". Default is "filtered"

+#' @param dataType can be "filtered" or "raw". Default \code{"filtered"}.

 #' @param rdsFileName File name prefix of the DropEst RDS output. default is "cell.counts"

 #' @param delayedArray Boolean. Whether to read the expression matrix as

 #'  \link[DelayedArray]{DelayedArray} object or not. Default \code{TRUE}.

@@ -103,14 +103,6 @@

 #' found in the DropEst rds, they will be added to the SCE metadata field

 #' @return A \code{SingleCellExperiment} object containing the count matrix,

 #'  the feature annotations from DropEst as ColData, and any metadata from DropEst

-#' @examples

-#' # Example #1

-#' Example DropEst outputs were downloaded from the DropEst Github 

-#' (http://pklab.med.harvard.edu/viktor/dropest_paper/dropest_0.8.5.zip). 

-#' To run the dropest import function with the example dataset, 

-#' set the sampleDirs variable to the example dropEst provided in SCTK as follows-

-#' sce <- importDropEst(sampleDirs = c('path/to/dropest/folder/'), 

-#'                      dataType='filtered', sampleNames=c('sample'))

 #' @export

 importDropEst <- function(sampleDirs = NULL, 

                           dataType = c('filtered','raw'),

@@ -4,8 +4,8 @@

   if (!file.exists(dropEst_cell_counts)){

     stop("DropEst output not found at location specified. Please check path provided and/or filename.")

   }

-  dropEst_rds <- readRDS(dropEst_cell_counts) 

-  

+  dropEst_rds <- readRDS(dropEst_cell_counts)

+

   return(dropEst_rds)

 }

@@ -17,7 +17,7 @@

       coldata_field_df <- data.frame(as.matrix(dropEst_rds[[field]]))

       names(coldata_field_df)[1] <- field

       coldata_field_df$cell <- row.names(coldata_field_df)

-      

+

       coldata_df[[field]] <- coldata_field_df

     }}

   coldata_df_merged <- Reduce(function(x, y) merge(x, y, all=TRUE,by="cell"), coldata_df)

@@ -39,9 +39,9 @@

   return(metadata)

 }

-.importDropEstSample <- function(sampleDir = './', 

-                                 dataType, 

-                                 rdsFileName, 

+.importDropEstSample <- function(sampleDir = './',

+                                 dataType,

+                                 rdsFileName,

                                  sampleName = 'sample',

                                  delayedArray = delayedArrary){

   ## Read DropEst RDS

@@ -53,37 +53,37 @@

   } else {

     stop("No counts matrix found in the .rds provided! Exiting.")

   }

-  

+

   if (isTRUE(delayedArray)) {

     counts_matrix <- DelayedArray::DelayedArray(counts_matrix)

     }

   ## Create SingleCellExperiment object

   ## Add SCE ColData. If using filtered counts matrix, colData is subset to include filtered cells.

-  ## append sample name to cells in SCE 

+  ## append sample name to cells in SCE

   sce <- SingleCellExperiment::SingleCellExperiment(assays = list(counts = counts_matrix))

-  colnames(sce) <- paste0(sampleName,"_",colnames(sce)) 

+  colnames(sce) <- paste0(sampleName,"_",colnames(sce))

   sce_coldata <- .constructColdata(dropEst_rds, counts_matrix, dataType)

   row.names(sce_coldata) <- paste0(sampleName,"_",row.names(sce_coldata))

-  

+

   if (dim(counts_matrix)[2] == dim(sce_coldata)[1]){

     SummarizedExperiment::colData(sce) <- sce_coldata

   } else {

     warning("Unable to add ColData to SCE. nCol of Counts Matrix not equal to nRow of ColData matrix.")

   }

-  

+

   ## Add SCE metadata

   sce_metadata <- .extractMetadata(dropEst_rds)

   metadata(sce) <- sce_metadata

-  

+

   return(sce)

 }

 #' @name importDropEst

 #' @rdname importDropEst

-#' @title Create a SingleCellExperiment Object from DropEst output 

+#' @title Create a SingleCellExperiment Object from DropEst output

 #' @description imports the RDS file created by DropEst (https://github.com/hms-dbmi/dropEst) and

 #' create a SingleCellExperiment object from either the raw or filtered counts matrix.

-#' Additionally parse through the RDS to obtain appropriate feature annotations as 

+#' Additionally parse through the RDS to obtain appropriate feature annotations as

 #' SCE coldata, in addition to any metadata.

 #' @param sampleDir  A path to the directory containing the data files. Default "./".

 #' @param sampleName A User-defined sample name. This will be prepended to all cell barcode IDs.

@@ -94,37 +94,38 @@

 #'  \link[DelayedArray]{DelayedArray} object or not. Default \code{TRUE}.

 #' @details

 #' \code{importDropEst} expects either raw counts matrix stored as "cm_raw" or filtered

-#' counts matrix stored as "cm" in the DropEst rds output. 

+#' counts matrix stored as "cm" in the DropEst rds output.

 #' ColData is obtained from the DropEst corresponding to "mean_reads_per_umi","aligned_reads_per_cell",

 #' "aligned_umis_per_cell","requested_umis_per_cb","requested_reads_per_cb"

-#' If using filtered counts matrix, the colData dataframe is 

+#' If using filtered counts matrix, the colData dataframe is

 #' subset to contain features from the filtered counts matrix alone.

-#' If any annotations of ("saturation_info","merge_targets","reads_per_umi_per_cell") are 

+#' If any annotations of ("saturation_info","merge_targets","reads_per_umi_per_cell") are

 #' found in the DropEst rds, they will be added to the SCE metadata field

 #' @return A \code{SingleCellExperiment} object containing the count matrix,

 #'  the feature annotations from DropEst as ColData, and any metadata from DropEst

 #' @examples

-#' # Example #1

-#' Example DropEst outputs were downloaded from the DropEst Github 

-#' (http://pklab.med.harvard.edu/viktor/dropest_paper/dropest_0.8.5.zip). 

-#' To run the dropest import function with the example dataset, 

+#' \dontrun{

+#' example outputs were downloaded from the DropEst Github

+#' (http://pklab.med.harvard.edu/viktor/dropest_paper/dropest_0.8.5.zip).

+#' To run the dropest import function with the example dataset,

 #' set the sampleDirs variable to the example dropEst provided in SCTK as follows-

-#' sce <- importDropEst(sampleDirs = c('path/to/dropest/folder/'), 

+#' sce <- importDropEst(sampleDirs = c('path/to/dropest/folder/'),

 #'                      dataType='filtered', sampleNames=c('sample'))

+#' }

 #' @export

-importDropEst <- function(sampleDirs = NULL, 

+importDropEst <- function(sampleDirs = NULL,

                           dataType = c('filtered','raw'),

                           rdsFileName = 'cell.counts',

                           sampleNames = NULL,

                           delayedArray = TRUE) {

   dataType <- match.arg(dataType)

-  

+

   if (length(sampleDirs)!=length(sampleNames)){

     stop("Please provide sample names for all input directories")

   }

-  

+

   res <- vector("list", length = length(sampleDirs))

-  

+

   for (i in seq_along(sampleDirs)){

     scei <- .importDropEstSample(sampleDir = sampleDirs[[i]],

                          sampleName = sampleNames[[i]],

@@ -136,8 +137,8 @@ importDropEst <- function(sampleDirs = NULL,

   sce <- do.call(SingleCellExperiment::cbind, res)

   return(sce)

 }

-  

-  

+

+

new file mode 100644

@@ -0,0 +1,143 @@

+

+.readDropEstFile <- function(sampleDir, dataType,rdsFileName){

+  dropEst_cell_counts <- file.path(sampleDir, paste(rdsFileName, '.rds', sep=''))

+  if (!file.exists(dropEst_cell_counts)){

+    stop("DropEst output not found at location specified. Please check path provided and/or filename.")

+  }

+  dropEst_rds <- readRDS(dropEst_cell_counts) 

+  

+  return(dropEst_rds)

+}

+

+.constructColdata <- function(dropEst_rds,counts_matrix, dataType){

+  coldata_fields <- c("mean_reads_per_umi","aligned_reads_per_cell","aligned_umis_per_cell","requested_umis_per_cb","requested_reads_per_cb")

+  coldata_df <-  list()

+  for (field in coldata_fields){

+    if (field %in% names(dropEst_rds)){

+      coldata_field_df <- data.frame(as.matrix(dropEst_rds[[field]]))

+      names(coldata_field_df)[1] <- field

+      coldata_field_df$cell <- row.names(coldata_field_df)

+      

+      coldata_df[[field]] <- coldata_field_df

+    }}

+  coldata_df_merged <- Reduce(function(x, y) merge(x, y, all=TRUE,by="cell"), coldata_df)

+  row.names(coldata_df_merged) <- coldata_df_merged$cell

+  coldata_df_merged <- S4Vectors::DataFrame(as.matrix(coldata_df_merged))

+  if (dataType == 'filtered'){

+    coldata_df_merged <- coldata_df_merged[coldata_df_merged$cell %in% colnames(counts_matrix),]

+  }

+  return(coldata_df_merged)

+}

+

+.extractMetadata <- function(dropEst_rds){

+  metadata_fields <- c("saturation_info","merge_targets","reads_per_umi_per_cell")

+  metadata <- c()

+  for (md in metadata_fields){

+    if (md %in% names(dropEst_rds)){

+      metadata[[md]] <- dropEst_rds[[md]]

+    }}

+  return(metadata)

+}

+

+.importDropEstSample <- function(sampleDir = './', 

+                                 dataType, 

+                                 rdsFileName, 

+                                 sampleName = 'sample',

+                                 delayedArray = delayedArrary){

+  ## Read DropEst RDS

+  dropEst_rds <- .readDropEstFile(sampleDir,dataType,rdsFileName)

+  if (dataType == 'filtered' && 'cm' %in% names(dropEst_rds)) {

+    counts_matrix <- dropEst_rds$cm

+  } else if (dataType == 'raw' && 'cm_raw' %in% names(dropEst_rds)) {

+    counts_matrix <- dropEst_rds$cm_raw

+  } else {

+    stop("No counts matrix found in the .rds provided! Exiting.")

+  }

+  

+  if (isTRUE(delayedArray)) {

+    counts_matrix <- DelayedArray::DelayedArray(counts_matrix)

+    }

+  ## Create SingleCellExperiment object

+  ## Add SCE ColData. If using filtered counts matrix, colData is subset to include filtered cells.

+  ## append sample name to cells in SCE 

+  sce <- SingleCellExperiment::SingleCellExperiment(assays = list(counts = counts_matrix))

+  colnames(sce) <- paste0(sampleName,"_",colnames(sce)) 

+  sce_coldata <- .constructColdata(dropEst_rds, counts_matrix, dataType)

+  row.names(sce_coldata) <- paste0(sampleName,"_",row.names(sce_coldata))

+  

+  if (dim(counts_matrix)[2] == dim(sce_coldata)[1]){

+    SummarizedExperiment::colData(sce) <- sce_coldata

+  } else {

+    warning("Unable to add ColData to SCE. nCol of Counts Matrix not equal to nRow of ColData matrix.")

+  }

+  

+  ## Add SCE metadata

+  sce_metadata <- .extractMetadata(dropEst_rds)

+  metadata(sce) <- sce_metadata

+  

+  return(sce)

+}

+

+#' @name importDropEst

+#' @rdname importDropEst

+#' @title Create a SingleCellExperiment Object from DropEst output 

+#' @description imports the RDS file created by DropEst (https://github.com/hms-dbmi/dropEst) and

+#' create a SingleCellExperiment object from either the raw or filtered counts matrix.

+#' Additionally parse through the RDS to obtain appropriate feature annotations as 

+#' SCE coldata, in addition to any metadata.

+#' @param sampleDir  A path to the directory containing the data files. Default "./".

+#' @param sampleName A User-defined sample name. This will be prepended to all cell barcode IDs.

+#'  Default "sample".

+#'  @param dataType can be "filtered" or "raw". Default is "filtered"

+#' @param rdsFileName File name prefix of the DropEst RDS output. default is "cell.counts"

+#' @param delayedArray Boolean. Whether to read the expression matrix as

+#'  \link[DelayedArray]{DelayedArray} object or not. Default \code{TRUE}.

+#' @details

+#' \code{importDropEst} expects either raw counts matrix stored as "cm_raw" or filtered

+#' counts matrix stored as "cm" in the DropEst rds output. 

+#' ColData is obtained from the DropEst corresponding to "mean_reads_per_umi","aligned_reads_per_cell",

+#' "aligned_umis_per_cell","requested_umis_per_cb","requested_reads_per_cb"

+#' If using filtered counts matrix, the colData dataframe is 

+#' subset to contain features from the filtered counts matrix alone.

+#' If any annotations of ("saturation_info","merge_targets","reads_per_umi_per_cell") are 

+#' found in the DropEst rds, they will be added to the SCE metadata field

+#' @return A \code{SingleCellExperiment} object containing the count matrix,

+#'  the feature annotations from DropEst as ColData, and any metadata from DropEst

+#' @examples

+#' # Example #1

+#' Example DropEst outputs were downloaded from the DropEst Github 

+#' (http://pklab.med.harvard.edu/viktor/dropest_paper/dropest_0.8.5.zip). 

+#' To run the dropest import function with the example dataset, 

+#' set the sampleDirs variable to the example dropEst provided in SCTK as follows-

+#' sce <- importDropEst(sampleDirs = c('path/to/dropest/folder/'), 

+#'                      dataType='filtered', sampleNames=c('sample'))

+#' @export

+importDropEst <- function(sampleDirs = NULL, 

+                          dataType = c('filtered','raw'),

+                          rdsFileName = 'cell.counts',

+                          sampleNames = NULL,

+                          delayedArray = TRUE) {

+  dataType <- match.arg(dataType)

+  

+  if (length(sampleDirs)!=length(sampleNames)){

+    stop("Please provide sample names for all input directories")

+  }

+  

+  res <- vector("list", length = length(sampleDirs))

+  

+  for (i in seq_along(sampleDirs)){

+    scei <- .importDropEstSample(sampleDir = sampleDirs[[i]],

+                         sampleName = sampleNames[[i]],

+                         dataType = dataType,

+                         rdsFileName = rdsFileName,

+                         delayedArray = delayedArray)

+    res[[i]] <- scei

+  }

+  sce <- do.call(SingleCellExperiment::cbind, res)

+  return(sce)

+}

+  

+  

+

+

+