@@ -1,10 +1,10 @@

 .constructSCE <- function(

-  matrices,

-  features,

-  barcodes,

-  metadata,

-  reducedDims) {

-

+    matrices,

+    features,

+    barcodes,

+    metadata,

+    reducedDims) {

+  

   sce <- SingleCellExperiment::SingleCellExperiment(assays = matrices)

   SummarizedExperiment::rowData(sce) <- S4Vectors::DataFrame(features)

   SummarizedExperiment::colData(sce) <- S4Vectors::DataFrame(barcodes)

@@ -34,7 +34,7 @@

   } else {

     fill <- NA

   }

-

+  

   ### combine row

   if (isTRUE(combineRow) & (!is.null(row))) {

     missRow <- row[!row %in% rownames(x)]

@@ -43,14 +43,14 @@

     if (!isTRUE(sparse)) {

       missMat <- as.matrix(missMat)

     }

-

+    

     mat <- rbind(matOrigin, missMat)

     if (anyDuplicated(rownames(mat))) {

       mat <- mat[!duplicated(rownames(mat)), ]

     }

     matOrigin <- mat[row, ]

   }

-

+  

   ### combine cols

   if (isTRUE(combineCol) & (!is.null(col))) {

     missCol <- col[!col %in% colnames(x)]

@@ -59,7 +59,7 @@

     if (!isTRUE(sparse)) {

       missMat <- as.matrix(missMat)

     }

-

+    

     mat <- cbind(matOrigin, missMat)

     if (anyDuplicated(colnames(mat))) {

       mat <- mat[, !duplicated(colnames(mat))]

@@ -76,12 +76,12 @@

     rw[['rownames']] <- rownames(rw)

     return(rw)

   })

-

+  

   ## Get merged rowData

   by.r <- unique(c('rownames', by.r))

   unionFe <- Reduce(function(r1, r2) merge(r1, r2, by=by.r, all=TRUE), feList)

   allGenes <- unique(unlist(lapply(feList, rownames)))

-

+  

   ## rowData

   newFe <- unionFe

   if (nrow(newFe) != length(allGenes)) {

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

     cD[['rownames']] <- rownames(cD)

     return(cD)

   })

-

+  

   by.c <- unique(c("rownames", by.c))

   unionCb <- Reduce(function(c1, c2) merge(c1, c2, by=by.c, all=TRUE), cbList)

   rownames(unionCb) <- unionCb[['rownames']]

@@ -118,19 +118,19 @@

   reduceList <- lapply(sceList, SingleCellExperiment::reducedDims)

   ## get every reducedDim exists in at least one SCEs

   UnionReducedDims <- unique(unlist(lapply(sceList, SingleCellExperiment::reducedDimNames)))

-

+  

   ## for each reducedDim, get union row/cols

   reducedDims <- list()

   for (reduceDim in UnionReducedDims) {

     x <- lapply(sceList, function(x) {if (reduceDim %in% SingleCellExperiment::reducedDimNames(x)) {SingleCellExperiment::reducedDim(x, reduceDim)}})

     reducedDims[[reduceDim]] <- .getDimUnion(x)

   }

-

+  

   ## Merge reducedDim for each SCE

   redList <- list()

   for (idx in seq_along(sceList)){

     redMat <- reduceList[[idx]]

-

+    

     for (DimName in UnionReducedDims) {

       if (DimName %in% names(redMat)) {

         redMat[[DimName]] <- .getMatUnion(reducedDims[[DimName]], redMat[[DimName]],

@@ -142,10 +142,10 @@

                                           dimnames = list(colnames(sceList[[idx]]), reducedDims[[DimName]][[2]]))

       }

     }

-

+    

     redList[[idx]] <- redMat

   }

-

+  

   return(redList)

 }

@@ -157,7 +157,7 @@

     unique(unlist(lapply(sceList, rownames))),

     unique(unlist(lapply(sceList, colnames)))

   )

-

+  

   asList <- list()

   for (idx in seq_along(assayList)){

     assay <- assayList[[idx]]

@@ -174,7 +174,7 @@

     }

     asList[[idx]] <- assay

   }

-

+  

   return(asList)

 }

@@ -197,27 +197,48 @@

 # }

 .mergeMetaSCE <- function(SCE_list) {

+  # Merge highest level metadata entries (except "sctk") by sample names in

+  # SCE_list. For analysis results in "sctk", merge by SCE_list sample name if 

+  # given "all_cells" in one object, else, use existing sample names. 

+  samples <- names(SCE_list)

   sampleMeta <- lapply(SCE_list, S4Vectors::metadata)

   metaNames <- unique(unlist(lapply(sampleMeta, names)))

+  sampleSctkMeta <- lapply(SCE_list, function(x) {S4Vectors::metadata(x)$sctk})

+  sctkMetaNames <- unique(unlist(lapply(sampleMeta, 

+                                        function(x) names(x$sctk))))

+  sampleMeta$sctk <- NULL

+  metaNames <- metaNames[!metaNames %in% c("sctk")]

   NewMeta <- list()

-

+  for (meta in sctkMetaNames) {

+    for (i in seq_along(sampleSctkMeta)) {

+      # `i` is for identifying each SCE object, usually matching a sample in 

+      # the pipeline. `sampleAvail` for samples stored in metadata entry, in

+      # case users are merging merged objects. 

+      sampleAvail <- names(sampleSctkMeta[[i]][[meta]])

+      if (length(sampleAvail) == 1) {

+        NewMeta$sctk[[meta]][[samples[i]]] <- sampleSctkMeta[[i]][[meta]][[1]]

+      } else if (length(sampleAvail) > 1) {

+        names(sampleSctkMeta[[i]][[meta]]) <- 

+          paste(names(sampleSctkMeta)[i], 

+                names(sampleSctkMeta[[i]][[meta]]), sep = "_")

+        NewMeta$sctk[[meta]] <- c(NewMeta$sctk[[meta]], 

+                                  sampleSctkMeta[[i]][[meta]])

+      }

+    }

+  }

   for (meta in metaNames) {

     for (i in seq_along(sampleMeta)) {

-      NewMeta[[meta]][[i]] <- sampleMeta[[i]][[meta]]

+      NewMeta[[meta]][[samples[i]]] <- sampleMeta[[i]][[meta]]

     }

   }

-

-  if ("runBarcodeRanksMetaOutput" %in% metaNames) {

-    NewMeta[["runBarcodeRanksMetaOutput"]] <- unlist(NewMeta[["runBarcodeRanksMetaOutput"]])

-  }

-

+  

   if ("assayType" %in% metaNames) {

     assayType <- lapply(SCE_list, function(x){S4Vectors::metadata(x)$assayType})

     assayType <- BiocGenerics::Reduce(dplyr::union, assayType)

     NewMeta[["assayType"]] <- assayType

   }

-

+  

   return(NewMeta)

 }

@@ -241,7 +262,7 @@

 #' @export

 combineSCE <- function(sceList, by.r = NULL, by.c = NULL, combined = TRUE){

-  if(length(sceList) == 1){

+  if (length(sceList) == 1) {

     return(sceList[[1]])

   }

   ##  rowData

@@ -252,16 +273,21 @@ combineSCE <- function(sceList, by.r = NULL, by.c = NULL, combined = TRUE){

   redMatList <- .mergeRedimSCE(sceList)

   ## assay

   assayList <- .mergeAssaySCE(sceList)

-

+  samples <- names(sceList)

+  if (is.null(samples)) {

+    samples <- paste0("sample", seq_along(sceList))

+  }

   New_SCE <- list()

   for (i in seq(length(sceList))) {

     ## create new sce

-    New_SCE[[i]] <- .constructSCE(matrices = assayList[[i]], features = newFeList,

-                                  barcodes = newCbList[[i]],

-                                  metadata = S4Vectors::metadata(sceList[[i]]),

-                                  reducedDims = redMatList[[i]])

+    sampleName <- samples[i]

+    New_SCE[[sampleName]] <- .constructSCE(matrices = assayList[[i]], 

+                                           features = newFeList,

+                                           barcodes = newCbList[[i]],

+                                           metadata = S4Vectors::metadata(sceList[[i]]),

+                                           reducedDims = redMatList[[i]])

   }

-

+  

   if (isTRUE(combined)) {

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

     meta <- .mergeMetaSCE(New_SCE)

@@ -236,6 +236,7 @@

 #' @return A \link[SingleCellExperiment]{SingleCellExperiment} object which combines all

 #' objects in sceList. The colData is merged.

 #' @examples

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

 #' combinedsce <- combineSCE(list(sce,sce), by.r = NULL, by.c = NULL, combined = TRUE)

 #' @export

@@ -213,7 +213,7 @@

   if ("assayType" %in% metaNames) {

     assayType <- lapply(SCE_list, function(x){S4Vectors::metadata(x)$assayType})

-    assayType <- Reduce(intersect, assayType)

+    assayType <- BiocGenerics::Reduce(dplyr::union, assayType)

     NewMeta[["assayType"]] <- assayType

   }

@@ -212,7 +212,7 @@

   }

   if ("assayType" %in% metaNames) {

-    assayType <- lapply(SCE_list, function(x){metadata(x)$assayType})

+    assayType <- lapply(SCE_list, function(x){S4Vectors::metadata(x)$assayType})

     assayType <- Reduce(intersect, assayType)

     NewMeta[["assayType"]] <- assayType

@@ -212,18 +212,9 @@

   }

   if ("assayType" %in% metaNames) {

-    tags <- unique(unlist(lapply(SCE_list,

-                                 function(x) {

-                                   names(S4Vectors::metadata(x)[["assayType"]])

-                                 })))

-    assayType <- list()

-    for (sample in SCE_list) {

-      assayType.each <- S4Vectors::metadata(sample)[["assayType"]]

-      for (t in tags) {

-        assayType[[t]] <- c(assayType[[t]], assayType.each[[t]])

-      }

-    }

-    assayType <- lapply(assayType, unique)

+    assayType <- lapply(SCE_list, function(x){metadata(x)$assayType})

+    assayType <- Reduce(intersect, assayType)

+    

     NewMeta[["assayType"]] <- assayType

   }

@@ -277,4 +268,4 @@ combineSCE <- function(sceList, by.r = NULL, by.c = NULL, combined = TRUE){

     return(sce)

   }

   return(New_SCE)

-}

\ No newline at end of file

+}

@@ -234,16 +234,21 @@

 #' @param sceList A list contains \link[SingleCellExperiment]{SingleCellExperiment} objects.

 #' Currently, combineSCE function only support combining SCE objects with assay in dgCMatrix format.

 #' It does not support combining SCE with assay in delayedArray format.

-#' @param by.r Specifications of the columns used for merging rowData. See 'Details'.

-#' @param by.c Specifications of the columns used for merging colData. See 'Details'.

-#' @param combined logical; if TRUE, it will combine the list of SingleCellExperiment objects. See 'Details'.

+#' @param by.r Specifications of the columns used for merging rowData. If set as NULL, 

+#' the rownames of rowData tables will be used to merging rowData. Default is NULL. 

+#' @param by.c Specifications of the columns used for merging colData. If set as NULL, 

+#' the rownames of colData tables will be used to merging colData. Default is NULL.

+#' @param combined logical; if TRUE, it will combine the list of SingleCellExperiment objects 

+#' and return a SingleCellExperiment. If FALSE, it will return a list of SingleCellExperiment whose

+#' rowData, colData, assay and reducedDim data slot are compatible within SCE objects in the list. 

+#' Default is TRUE.

 #' @return A \link[SingleCellExperiment]{SingleCellExperiment} object which combines all

 #' objects in sceList. The colData is merged.

 #' @examples

 #' combinedsce <- combineSCE(list(sce,sce), by.r = NULL, by.c = NULL, combined = TRUE)

 #' @export

-combineSCE <- function(sceList, by.r, by.c, combined){

+combineSCE <- function(sceList, by.r = NULL, by.c = NULL, combined = TRUE){

   if(length(sceList) == 1){

     return(sceList[[1]])

   }

@@ -211,6 +211,22 @@

     NewMeta[["runBarcodeRanksMetaOutput"]] <- unlist(NewMeta[["runBarcodeRanksMetaOutput"]])

   }

+  if ("assayType" %in% metaNames) {

+    tags <- unique(unlist(lapply(SCE_list,

+                                 function(x) {

+                                   names(S4Vectors::metadata(x)[["assayType"]])

+                                 })))

+    assayType <- list()

+    for (sample in SCE_list) {

+      assayType.each <- S4Vectors::metadata(sample)[["assayType"]]

+      for (t in tags) {

+        assayType[[t]] <- c(assayType[[t]], assayType.each[[t]])

+      }

+    }

+    assayType <- lapply(assayType, unique)

+    NewMeta[["assayType"]] <- assayType

+  }

+

   return(NewMeta)

 }

@@ -215,9 +215,9 @@

 }

 #' Combine a list of SingleCellExperiment objects as one SingleCellExperiment object

-#' @param sceList A list contains \link[SingleCellExperiment]{SingleCellExperiment} objects. 

-#' Currently, combineSCE function only support combining SCE objects with assay in dgCMatrix format. 

-#' It does not support combining SCE with assay in delayedArray format. 

+#' @param sceList A list contains \link[SingleCellExperiment]{SingleCellExperiment} objects.

+#' Currently, combineSCE function only support combining SCE objects with assay in dgCMatrix format.

+#' It does not support combining SCE with assay in delayedArray format.

 #' @param by.r Specifications of the columns used for merging rowData. See 'Details'.

 #' @param by.c Specifications of the columns used for merging colData. See 'Details'.

 #' @param combined logical; if TRUE, it will combine the list of SingleCellExperiment objects. See 'Details'.

@@ -228,6 +228,9 @@

 #' @export

 combineSCE <- function(sceList, by.r, by.c, combined){

+  if(length(sceList) == 1){

+    return(sceList[[1]])

+  }

   ##  rowData

   newFeList <- .mergeRowDataSCE(sceList, by.r)

   ## colData

@@ -108,7 +108,7 @@

   rownames(unionCb) <- unionCb[['rownames']]

   newCbList <- list()

   for (i in seq_along(sceList)) {

-    newCbList[[i]] <- unionCb[colnames(sceList[[i]]),]

+    newCbList[[i]] <- unionCb[colnames(sceList[[i]]), , drop=FALSE]

   }

   return(newCbList)

 }

@@ -215,7 +215,9 @@

 }

 #' Combine a list of SingleCellExperiment objects as one SingleCellExperiment object

-#' @param sceList A list contains \link[SingleCellExperiment]{SingleCellExperiment} objects

+#' @param sceList A list contains \link[SingleCellExperiment]{SingleCellExperiment} objects. 

+#' Currently, combineSCE function only support combining SCE objects with assay in dgCMatrix format. 

+#' It does not support combining SCE with assay in delayedArray format. 

 #' @param by.r Specifications of the columns used for merging rowData. See 'Details'.

 #' @param by.c Specifications of the columns used for merging colData. See 'Details'.

 #' @param combined logical; if TRUE, it will combine the list of SingleCellExperiment objects. See 'Details'.

@@ -14,9 +14,9 @@

 }

 .getDimUnion <- function(dataList){

-  Row <- vapply(dataList, function(x) {rownames(x)})

+  Row <- lapply(dataList, function(x) {rownames(x)})

   RowUnion <- base::Reduce(union, Row)

-  Col <- vapply(dataList, function(x) {colnames(x)})

+  Col <- lapply(dataList, function(x) {colnames(x)})

   ColUnion <- base::Reduce(union, Col)

   return(list(RowUnion, ColUnion))

 }

@@ -4,7 +4,7 @@

   barcodes,

   metadata,

   reducedDims) {

-  

+

   sce <- SingleCellExperiment::SingleCellExperiment(assays = matrices)

   SummarizedExperiment::rowData(sce) <- S4Vectors::DataFrame(features)

   SummarizedExperiment::colData(sce) <- S4Vectors::DataFrame(barcodes)

@@ -21,9 +21,9 @@

   return(list(RowUnion, ColUnion))

 }

-.getMatUnion <- function(dimsList, x, 

-                         combineRow, combineCol, 

-                         sparse = FALSE, 

+.getMatUnion <- function(dimsList, x,

+                         combineRow, combineCol,

+                         sparse = FALSE,

                          fill = c("NA", "0")){

   row <- dimsList[[1]]

   col <- dimsList[[2]]

@@ -34,8 +34,8 @@

   } else {

     fill <- NA

   }

-  

-  ### combine row 

+

+  ### combine row

   if (isTRUE(combineRow) & (!is.null(row))) {

     missRow <- row[!row %in% rownames(x)]

     missMat <- Matrix::Matrix(fill, nrow = length(missRow), ncol = ncol(matOrigin),

@@ -43,15 +43,15 @@

     if (!isTRUE(sparse)) {

       missMat <- as.matrix(missMat)

     }

-    

+

     mat <- rbind(matOrigin, missMat)

     if (anyDuplicated(rownames(mat))) {

       mat <- mat[!duplicated(rownames(mat)), ]

     }

     matOrigin <- mat[row, ]

   }

-  

-  ### combine cols 

+

+  ### combine cols

   if (isTRUE(combineCol) & (!is.null(col))) {

     missCol <- col[!col %in% colnames(x)]

     missMat <- Matrix::Matrix(fill, nrow = nrow(matOrigin), ncol = length(missCol),

@@ -59,7 +59,7 @@

     if (!isTRUE(sparse)) {

       missMat <- as.matrix(missMat)

     }

-    

+

     mat <- cbind(matOrigin, missMat)

     if (anyDuplicated(colnames(mat))) {

       mat <- mat[, !duplicated(colnames(mat))]

@@ -76,17 +76,17 @@

     rw[['rownames']] <- rownames(rw)

     return(rw)

   })

-  

+

   ## Get merged rowData

   by.r <- unique(c('rownames', by.r))

   unionFe <- Reduce(function(r1, r2) merge(r1, r2, by=by.r, all=TRUE), feList)

   allGenes <- unique(unlist(lapply(feList, rownames)))

-  

+

   ## rowData

   newFe <- unionFe

   if (nrow(newFe) != length(allGenes)) {

     warning("Conflicts were found when merging two rowData. ",

-            "Resolved the conflicts by choosing the first entries.", 

+            "Resolved the conflicts by choosing the first entries.",

             "To avoid conflicts, please provide the 'by.r' arguments to ",

             "specify columns in rowData that does not have conflict between two singleCellExperiment object. ")

     newFe <- newFe[!duplicated(newFe$rownames), ]

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

     cD[['rownames']] <- rownames(cD)

     return(cD)

   })

-  

+

   by.c <- unique(c("rownames", by.c))

   unionCb <- Reduce(function(c1, c2) merge(c1, c2, by=by.c, all=TRUE), cbList)

   rownames(unionCb) <- unionCb[['rownames']]

@@ -118,34 +118,34 @@

   reduceList <- lapply(sceList, SingleCellExperiment::reducedDims)

   ## get every reducedDim exists in at least one SCEs

   UnionReducedDims <- unique(unlist(lapply(sceList, SingleCellExperiment::reducedDimNames)))

-  

+

   ## for each reducedDim, get union row/cols

   reducedDims <- list()

   for (reduceDim in UnionReducedDims) {

     x <- lapply(sceList, function(x) {if (reduceDim %in% SingleCellExperiment::reducedDimNames(x)) {SingleCellExperiment::reducedDim(x, reduceDim)}})

     reducedDims[[reduceDim]] <- .getDimUnion(x)

   }

-  

+

   ## Merge reducedDim for each SCE

   redList <- list()

   for (idx in seq_along(sceList)){

     redMat <- reduceList[[idx]]

-    

+

     for (DimName in UnionReducedDims) {

       if (DimName %in% names(redMat)) {

         redMat[[DimName]] <- .getMatUnion(reducedDims[[DimName]], redMat[[DimName]],

                                           combineRow = FALSE, combineCol = TRUE,

                                           sparse = FALSE, fill = "NA")

       } else {

-        redMat[[DimName]] <- base::matrix(NA, nrow = ncol(sceList[[idx]]), 

+        redMat[[DimName]] <- base::matrix(NA, nrow = ncol(sceList[[idx]]),

                                           ncol = length(reducedDims[[DimName]][[2]]),

                                           dimnames = list(colnames(sceList[[idx]]), reducedDims[[DimName]][[2]]))

       }

     }

-    

+

     redList[[idx]] <- redMat

   }

-  

+

   return(redList)

 }

@@ -154,21 +154,21 @@

                         lapply(sceList, SummarizedExperiment::assayNames))

   assayList <- lapply(sceList, assays)

   assayDims <- list(

-    unique(unlist(lapply(sceList, rownames))), 

+    unique(unlist(lapply(sceList, rownames))),

     unique(unlist(lapply(sceList, colnames)))

   )

-  

+

   asList <- list()

   for (idx in seq_along(assayList)){

     assay <- assayList[[idx]]

     for (assayName in UnionAssays) {

       if (assayName %in% names(assay)) {

         assay[[assayName]] <- .getMatUnion(assayDims, assay[[assayName]],

-                                           combineRow = TRUE, combineCol = FALSE, 

+                                           combineRow = TRUE, combineCol = FALSE,

                                            sparse = TRUE, fill = "0")

       } else{

-        assay[[assayName]] <- Matrix::Matrix(0, nrow = length(assayDims[[1]]), 

-                                             ncol = ncol(sceList[[idx]]), 

+        assay[[assayName]] <- Matrix::Matrix(0, nrow = length(assayDims[[1]]),

+                                             ncol = ncol(sceList[[idx]]),

                                              dimnames = list(assayDims[[1]], colnames(sceList[[idx]]))) #assayDims[[assayName]])

       }

     }

@@ -181,46 +181,48 @@

 # .mergeMetaSCE <- function(sceList) {

 #   metaList <- lapply(sceList, S4Vectors::metadata)

 #   metaNames <- unlist(lapply(metaList, names))

-  

+

 #   if ("runBarcodeRanksMetaOutput" %in% metaNames) {

 #     barcodeMetas <- lapply(metaList, function(x) {x[["runBarcodeRanksMetaOutput"]]})

 #     barcodeMetas <- do.call(rbind, barcodeMetas)

-    

+

 #     for (i in seq_along(metaList)) {

-#       metaList[[i]][["runBarcodeRanksMetaOutput"]] <- NULL  

+#       metaList[[i]][["runBarcodeRanksMetaOutput"]] <- NULL

 #     }

-    

+

 #     metaList[["runBarcodeRanksMetaOutput"]] <- barcodeMetas

 #   }

-  

+

 #   return(metaList)

 # }

 .mergeMetaSCE <- function(SCE_list) {

-  sampleMeta <- lapply(SCE_list, S4Vectors::metadata) 

+  sampleMeta <- lapply(SCE_list, S4Vectors::metadata)

   metaNames <- unique(unlist(lapply(sampleMeta, names)))

   NewMeta <- list()

-  

+

   for (meta in metaNames) {

     for (i in seq_along(sampleMeta)) {

       NewMeta[[meta]][[i]] <- sampleMeta[[i]][[meta]]

     }

   }

-  

+

   if ("runBarcodeRanksMetaOutput" %in% metaNames) {

     NewMeta[["runBarcodeRanksMetaOutput"]] <- unlist(NewMeta[["runBarcodeRanksMetaOutput"]])

   }

-  

+

   return(NewMeta)

 }

 #' Combine a list of SingleCellExperiment objects as one SingleCellExperiment object

-#' @param sceList A list contains \link[SingleCellExperiment]{SingleCellExperiment} objects 

+#' @param sceList A list contains \link[SingleCellExperiment]{SingleCellExperiment} objects

 #' @param by.r Specifications of the columns used for merging rowData. See 'Details'.

 #' @param by.c Specifications of the columns used for merging colData. See 'Details'.

-#' @param combined logical; if TRUE, it will combine the list of SingleCellExperiment objects. See 'Details'.  

-#' @return A \link[SingleCellExperiment]{SingleCellExperiment} object which combines all 

-#' objects in sceList. The colData is merged.  

+#' @param combined logical; if TRUE, it will combine the list of SingleCellExperiment objects. See 'Details'.

+#' @return A \link[SingleCellExperiment]{SingleCellExperiment} object which combines all

+#' objects in sceList. The colData is merged.

+#' @examples

+#' combinedsce <- combineSCE(list(sce,sce), by.r = NULL, by.c = NULL, combined = TRUE)

 #' @export

 combineSCE <- function(sceList, by.r, by.c, combined){

@@ -229,19 +231,19 @@ combineSCE <- function(sceList, by.r, by.c, combined){

   ## colData

   newCbList <- .mergeColDataSCE(sceList, by.c)

   ## reducedDim

-  redMatList <- .mergeRedimSCE(sceList) 

+  redMatList <- .mergeRedimSCE(sceList)

   ## assay

-  assayList <- .mergeAssaySCE(sceList) 

-  

+  assayList <- .mergeAssaySCE(sceList)

+

   New_SCE <- list()

   for (i in seq(length(sceList))) {

     ## create new sce

     New_SCE[[i]] <- .constructSCE(matrices = assayList[[i]], features = newFeList,

-                                  barcodes = newCbList[[i]], 

+                                  barcodes = newCbList[[i]],

                                   metadata = S4Vectors::metadata(sceList[[i]]),

                                   reducedDims = redMatList[[i]])

   }

-  

+

   if (isTRUE(combined)) {

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

     meta <- .mergeMetaSCE(New_SCE)

@@ -79,7 +79,7 @@

   ## Get merged rowData

   by.r <- unique(c('rownames', by.r))

-  unionFe <- Reduce(function(r1, r2) merge(r1, r2, by=by.r, all=T), feList)

+  unionFe <- Reduce(function(r1, r2) merge(r1, r2, by=by.r, all=TRUE), feList)

   allGenes <- unique(unlist(lapply(feList, rownames)))

   ## rowData

@@ -104,7 +104,7 @@

   })

   by.c <- unique(c("rownames", by.c))

-  unionCb <- Reduce(function(c1, c2) merge(c1, c2, by=by.c, all=T), cbList)

+  unionCb <- Reduce(function(c1, c2) merge(c1, c2, by=by.c, all=TRUE), cbList)

   rownames(unionCb) <- unionCb[['rownames']]

   newCbList <- list()

   for (i in seq_along(sceList)) {

@@ -234,7 +234,7 @@ combineSCE <- function(sceList, by.r, by.c, combined){

   assayList <- .mergeAssaySCE(sceList) 

   New_SCE <- list()

-  for (i in 1:length(sceList)) {

+  for (i in seq(length(sceList))) {

     ## create new sce

     New_SCE[[i]] <- .constructSCE(matrices = assayList[[i]], features = newFeList,

                                   barcodes = newCbList[[i]], 

@@ -249,4 +249,4 @@ combineSCE <- function(sceList, by.r, by.c, combined){

     return(sce)

   }

   return(New_SCE)

-}

\ No newline at end of file

+}

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

   reducedDims) {

   sce <- SingleCellExperiment::SingleCellExperiment(assays = matrices)

-  SummarizedExperiment::rowData(sce) <- features

-  SummarizedExperiment::colData(sce) <- barcodes

+  SummarizedExperiment::rowData(sce) <- S4Vectors::DataFrame(features)

+  SummarizedExperiment::colData(sce) <- S4Vectors::DataFrame(barcodes)

   S4Vectors::metadata(sce) <- metadata

   SingleCellExperiment::reducedDims(sce) <- reducedDims

   return(sce)

new file mode 100644

@@ -0,0 +1,252 @@

+.constructSCE <- function(

+  matrices,

+  features,

+  barcodes,

+  metadata,

+  reducedDims) {

+  

+  sce <- SingleCellExperiment::SingleCellExperiment(assays = matrices)

+  SummarizedExperiment::rowData(sce) <- features

+  SummarizedExperiment::colData(sce) <- barcodes

+  S4Vectors::metadata(sce) <- metadata

+  SingleCellExperiment::reducedDims(sce) <- reducedDims

+  return(sce)

+}

+

+.getDimUnion <- function(dataList){

+  Row <- sapply(dataList, function(x) {rownames(x)})

+  RowUnion <- base::Reduce(union, Row)

+  Col <- sapply(dataList, function(x) {colnames(x)})

+  ColUnion <- base::Reduce(union, Col)

+  return(list(RowUnion, ColUnion))

+}

+

+.getMatUnion <- function(dimsList, x, 

+                         combineRow, combineCol, 

+                         sparse = FALSE, 

+                         fill = c("NA", "0")){

+  row <- dimsList[[1]]

+  col <- dimsList[[2]]

+  matOrigin <- x

+  fill <- match.arg(fill)

+  if (fill == "0") {

+    fill <- 0

+  } else {

+    fill <- NA

+  }

+  

+  ### combine row 

+  if (isTRUE(combineRow) & (!is.null(row))) {

+    missRow <- row[!row %in% rownames(x)]

+    missMat <- Matrix::Matrix(fill, nrow = length(missRow), ncol = ncol(matOrigin),

+                            dimnames = list(missRow, colnames(matOrigin)))

+    if (!isTRUE(sparse)) {

+      missMat <- as.matrix(missMat)

+    }

+    

+    mat <- rbind(matOrigin, missMat)

+    if (anyDuplicated(rownames(mat))) {

+      mat <- mat[!duplicated(rownames(mat)), ]

+    }

+    matOrigin <- mat[row, ]

+  }

+  

+  ### combine cols 

+  if (isTRUE(combineCol) & (!is.null(col))) {

+    missCol <- col[!col %in% colnames(x)]

+    missMat <- Matrix::Matrix(fill, nrow = nrow(matOrigin), ncol = length(missCol),

+                            dimnames = list(rownames(matOrigin), missCol))

+    if (!isTRUE(sparse)) {

+      missMat <- as.matrix(missMat)

+    }

+    

+    mat <- cbind(matOrigin, missMat)

+    if (anyDuplicated(colnames(mat))) {

+      mat <- mat[, !duplicated(colnames(mat))]

+    }

+    matOrigin <- mat[, col]

+  }

+  return(matOrigin)

+}

+

+

+.mergeRowDataSCE <- function(sceList, by.r) {

+  feList <- lapply(sceList, function(x){

+    rw <- SummarizedExperiment::rowData(x)

+    rw[['rownames']] <- rownames(rw)

+    return(rw)

+  })

+  

+  ## Get merged rowData

+  by.r <- unique(c('rownames', by.r))

+  unionFe <- Reduce(function(r1, r2) merge(r1, r2, by=by.r, all=T), feList)

+  allGenes <- unique(unlist(lapply(feList, rownames)))

+  

+  ## rowData

+  newFe <- unionFe

+  if (nrow(newFe) != length(allGenes)) {

+    warning("Conflicts were found when merging two rowData. ",

+            "Resolved the conflicts by choosing the first entries.", 

+            "To avoid conflicts, please provide the 'by.r' arguments to ",

+            "specify columns in rowData that does not have conflict between two singleCellExperiment object. ")

+    newFe <- newFe[!duplicated(newFe$rownames), ]

+  }

+  rownames(newFe) <- newFe[['rownames']]

+  newFe <- newFe[allGenes,]

+  return(newFe)

+}

+

+.mergeColDataSCE <- function(sceList, by.c) {

+  cbList <- lapply(sceList, function(x) {

+    cD <- SummarizedExperiment::colData(x)

+    cD[['rownames']] <- rownames(cD)

+    return(cD)

+  })

+  

+  by.c <- unique(c("rownames", by.c))

+  unionCb <- Reduce(function(c1, c2) merge(c1, c2, by=by.c, all=T), cbList)

+  rownames(unionCb) <- unionCb[['rownames']]

+  newCbList <- list()

+  for (i in seq_along(sceList)) {

+    newCbList[[i]] <- unionCb[colnames(sceList[[i]]),]

+  }

+  return(newCbList)

+}

+

+.mergeRedimSCE <- function(sceList, reduceList) {

+  ## get reducedDims for each SCE SummarizedExperiment::

+  reduceList <- lapply(sceList, SingleCellExperiment::reducedDims)

+  ## get every reducedDim exists in at least one SCEs

+  UnionReducedDims <- unique(unlist(lapply(sceList, SingleCellExperiment::reducedDimNames)))

+  

+  ## for each reducedDim, get union row/cols

+  reducedDims <- list()

+  for (reduceDim in UnionReducedDims) {

+    x <- lapply(sceList, function(x) {if (reduceDim %in% SingleCellExperiment::reducedDimNames(x)) {SingleCellExperiment::reducedDim(x, reduceDim)}})

+    reducedDims[[reduceDim]] <- .getDimUnion(x)

+  }

+  

+  ## Merge reducedDim for each SCE

+  redList <- list()

+  for (idx in seq_along(sceList)){

+    redMat <- reduceList[[idx]]

+    

+    for (DimName in UnionReducedDims) {

+      if (DimName %in% names(redMat)) {

+        redMat[[DimName]] <- .getMatUnion(reducedDims[[DimName]], redMat[[DimName]],

+                                          combineRow = FALSE, combineCol = TRUE,

+                                          sparse = FALSE, fill = "NA")

+      } else {

+        redMat[[DimName]] <- base::matrix(NA, nrow = ncol(sceList[[idx]]), 

+                                          ncol = length(reducedDims[[DimName]][[2]]),

+                                          dimnames = list(colnames(sceList[[idx]]), reducedDims[[DimName]][[2]]))

+      }

+    }

+    

+    redList[[idx]] <- redMat

+  }

+  

+  return(redList)

+}

+

+.mergeAssaySCE <- function(sceList) {

+  UnionAssays <- Reduce(function(d1, d2) base::union(d1, d2),

+                        lapply(sceList, SummarizedExperiment::assayNames))

+  assayList <- lapply(sceList, assays)

+  assayDims <- list(

+    unique(unlist(lapply(sceList, rownames))), 

+    unique(unlist(lapply(sceList, colnames)))

+  )

+  

+  asList <- list()

+  for (idx in seq_along(assayList)){

+    assay <- assayList[[idx]]

+    for (assayName in UnionAssays) {

+      if (assayName %in% names(assay)) {

+        assay[[assayName]] <- .getMatUnion(assayDims, assay[[assayName]],

+                                           combineRow = TRUE, combineCol = FALSE, 

+                                           sparse = TRUE, fill = "0")

+      } else{

+        assay[[assayName]] <- Matrix::Matrix(0, nrow = length(assayDims[[1]]), 

+                                             ncol = ncol(sceList[[idx]]), 

+                                             dimnames = list(assayDims[[1]], colnames(sceList[[idx]]))) #assayDims[[assayName]])

+      }

+    }

+    asList[[idx]] <- assay

+  }

+

+  return(asList)

+}

+

+# .mergeMetaSCE <- function(sceList) {