@@ -493,11 +493,11 @@ setMethod(

         append = TRUE,

         verbose = verbose

       )

-      countsBat <- methods::as(countsBat, "dgCMatrix")

+      countsBat <- methods::as(countsBat, "CsparseMatrix")

     }

     if (!is.null(bgBat)) {

       if (!inherits(bgBat, "dgCMatrix")) {

-        bgBat <- methods::as(bgBat, "dgCMatrix")

+        bgBat <- methods::as(bgBat, "CsparseMatrix")

       }

     }

@@ -144,6 +144,8 @@ setGeneric("decontX", function(x, ...) standardGeneric("decontX"))

 #' @export

 #' @rdname decontX

+#' @importClassesFrom SingleCellExperiment SingleCellExperiment

+#' @importClassesFrom Matrix dgCMatrix

 setMethod("decontX", "SingleCellExperiment", function(x,

                                                       assayName = "counts",

                                                       z = NULL,

@@ -246,6 +246,8 @@ setMethod("decontX", "ANY", function(x,

     # Remove cells with the same ID between x and the background matrix

     background <- .checkBackground(x = x, background = background,

                                    logfile = logfile, verbose = verbose)

+

+    countsBackground <- background

   }

   .decontX(

@@ -27,13 +27,13 @@

 #' @param background A numeric matrix of counts or a

 #' \linkS4class{SingleCellExperiment} with the matrix located in the assay

 #' slot under \code{assayName}. It should have the same data format as \code{x}

-#' except it contains the empty droplets instead of cells. When supplied, 

+#' except it contains the empty droplets instead of cells. When supplied,

 #' empirical distribution of transcripts from these empty droplets

 #' will be used as the contamination distribution. Default NULL.

 #' @param bgAssayName Character. Name of the assay to use if \code{background}

 #' is a \linkS4class{SingleCellExperiment}. Default to same as

 #' \code{assayName}.

-#' @param bgBatch Numeric or character vector. Batch labels for 

+#' @param bgBatch Numeric or character vector. Batch labels for

 #' \code{background}. Its unique values should be the same as those in

 #' \code{batch}, such that each batch of cells have their corresponding batch

 #' of empty droplets as background, pointed by this parameter. Default to NULL.

@@ -174,10 +174,10 @@ setMethod("decontX", "SingleCellExperiment", function(x,

                              bgBatch = bgBatch,

                              logfile = logfile,

                              verbose = verbose)

-    

+

     background <- temp$background

     bgBatch <- temp$bgBatch

-    

+

     if (is.null(bgAssayName)) {

       bgAssayName <- assayName

     }

@@ -265,10 +265,10 @@ setMethod("decontX", "ANY", function(x,

                              bgBatch = bgBatch,

                              logfile = logfile,

                              verbose = verbose)

-    

+

     background <- temp$background

     bgBatch <- temp$bgBatch

-    

+

   }

   .decontX(

@@ -420,9 +420,9 @@ setMethod(

   ## Generate batch labels if none were supplied

   if (is.null(batch)) {

     batch <- rep("all_cells", nC)

-    

+

     # If batch null, bgBatch has to be null

-    if (!is.null(batchBackground)){

+    if (!is.null(batchBackground)) {

       stop(

         "When experiment default to no bacth, background should ",

         "also default to no batch."

@@ -436,7 +436,7 @@ setMethod(

     # If batch not null and countsBackground supplied,

     # user has to supply batchBackground as well

-    if (!is.null(countsBackground) & is.null(batchBackground)){

+    if (!is.null(countsBackground) & is.null(batchBackground)) {

       stop(

         "Cell batch, and background are supplied. Please also ",

         "supply background batch."

@@ -540,7 +540,7 @@ setMethod(

     }

     ## Try to convert class of new matrix to class of original matrix

-    

+

     .logMessages(

       date(),

       ".. Calculating final decontaminated matrix",

@@ -612,7 +612,7 @@ setMethod(

       append = TRUE,

       verbose = verbose

     )

-    

+

     ## Determine class of seed in DelayedArray

     seed.class <- unique(DelayedArray::seedApply(counts, class))[[1]]

     if (seed.class == "HDF5ArraySeed") {

@@ -1422,7 +1422,7 @@ simulateContamination <- function(C = 300,

                              logfile = NULL, verbose = FALSE) {

   # Remove background barcodes that have already appeared in x

   # If bgBatch param is supplied, also remove duplicate bgBatch

-  if(!is.null(colnames(background))) {

+  if (!is.null(colnames(background))) {

     dupBarcode <- colnames(background) %in% colnames(x)

   } else {

     dupBarcode <- FALSE

@@ -1432,7 +1432,7 @@ simulateContamination <- function(C = 300,

             " Please ensure that no true cells are included in the background ",

             "matrix. Otherwise, results will be incorrect.")

   }

-  

+

   if (any(dupBarcode)) {

     .logMessages(

       date(),

@@ -1445,8 +1445,8 @@ simulateContamination <- function(C = 300,

       verbose = verbose

     )

     background <- background[, !(dupBarcode), drop = FALSE]

-    

-    if(!is.null(bgBatch)){

+

+    if (!is.null(bgBatch)) {

       if (length(bgBatch) != length(dupBarcode)) {

         stop(

           "Length of bgBatch must be equal to the number of columns",

@@ -1456,9 +1456,9 @@ simulateContamination <- function(C = 300,

       bgBatch <- bgBatch[!(dupBarcode)]

     }

   }

-  

-  re = list(background = background,

+

+  re <- list(background = background,

             bgBatch = bgBatch)

-  

+

   return(re)

 }

@@ -424,7 +424,7 @@ setMethod(

     # If batch null, bgBatch has to be null

     if (!is.null(batchBackground)){

       stop(

-        "When experiment default to no bacth, background should",

+        "When experiment default to no bacth, background should ",

         "also default to no batch."

       )

     }

@@ -432,6 +432,17 @@ setMethod(

     if (!is.null(countsBackground)) {

       batchBackground <- rep("all_cells", ncol(countsBackground))

     }

+  } else {

+

+    # If batch not null and countsBackground supplied,

+    # user has to supply batchBackground as well

+    if (!is.null(countsBackground) & is.null(batchBackground)){

+      stop(

+        "Cell batch, and background are supplied. Please also ",

+        "supply background batch."

+      )

+    }

+

   }

   runParams$batch <- batch

   runParams$batchBackground <- batchBackground

@@ -421,6 +421,14 @@ setMethod(

   if (is.null(batch)) {

     batch <- rep("all_cells", nC)

+    # If batch null, bgBatch has to be null

+    if (!is.null(batchBackground)){

+      stop(

+        "When experiment default to no bacth, background should",

+        "also default to no batch."

+      )

+    }

+

     if (!is.null(countsBackground)) {

       batchBackground <- rep("all_cells", ncol(countsBackground))

     }

@@ -426,6 +426,7 @@ setMethod(

     }

   }

   runParams$batch <- batch

+  runParams$batchBackground <- batchBackground

   batchIndex <- unique(batch)

   ## Set result lists upfront for all cells from different batches

@@ -458,7 +459,7 @@ setMethod(

     zBat <- NULL

     countsBat <- counts[, batch == bat]

-    bgBat <- countsBackground[, batchBackgound == bat]

+    bgBat <- countsBackground[, batchBackground == bat]

     ## Convert to sparse matrix

     if (!inherits(countsBat, "dgCMatrix")) {

@@ -458,7 +458,7 @@ setMethod(

     zBat <- NULL

     countsBat <- counts[, batch == bat]

-    bgBat <- countsBackground[, bactchBackgound == bat]

+    bgBat <- countsBackground[, batchBackgound == bat]

     ## Convert to sparse matrix

     if (!inherits(countsBat, "dgCMatrix")) {

@@ -168,6 +168,7 @@ setMethod("decontX", "SingleCellExperiment", function(x,

   countsBackground <- NULL

   if (!is.null(background)) {

     # Remove cells with the same ID between x and the background matrix

+    # Also update bgBatch when background is updated and bgBatch is not null

     temp <- .checkBackground(x = x,

                              background = background,

                              bgBatch = bgBatch,

@@ -258,6 +259,7 @@ setMethod("decontX", "ANY", function(x,

   countsBackground <- NULL

   if (!is.null(background)) {

     # Remove cells with the same ID between x and the background matrix

+    # Also update bgBatch when background is updated and bgBatch is not null

     temp <- .checkBackground(x = x,

                              background = background,

                              bgBatch = bgBatch,

@@ -168,10 +168,14 @@ setMethod("decontX", "SingleCellExperiment", function(x,

   countsBackground <- NULL

   if (!is.null(background)) {

     # Remove cells with the same ID between x and the background matrix

-    background <- .checkBackground(x = x, background = background,

-                                   logfile = logfile, verbose = verbose)

+    temp <- .checkBackground(x = x,

+                             background = background,

+                             bgBatch = bgBatch,

+                             logfile = logfile,

+                             verbose = verbose)

-    # TODO: Does bgBatch needs to be checked?

+    background <- temp$background

+    bgBatch <- temp$bgBatch

     if (is.null(bgAssayName)) {

       bgAssayName <- assayName

@@ -254,10 +258,14 @@ setMethod("decontX", "ANY", function(x,

   countsBackground <- NULL

   if (!is.null(background)) {

     # Remove cells with the same ID between x and the background matrix

-    background <- .checkBackground(x = x, background = background,

-                                   logfile = logfile, verbose = verbose)

+    temp <- .checkBackground(x = x,

+                             background = background,

+                             bgBatch = bgBatch,

+                             logfile = logfile,

+                             verbose = verbose)

-    # TODO: Does bgBatch needs to be checked?

+    background <- temp$background

+    bgBatch <- temp$bgBatch

   }

@@ -1388,8 +1396,10 @@ simulateContamination <- function(C = 300,

 }

-.checkBackground <- function(x, background, logfile = NULL, verbose = FALSE) {

+.checkBackground <- function(x, background, bgBatch,

+                             logfile = NULL, verbose = FALSE) {

   # Remove background barcodes that have already appeared in x

+  # If bgBatch param is supplied, also remove duplicate bgBatch

   if(!is.null(colnames(background))) {

     dupBarcode <- colnames(background) %in% colnames(x)

   } else {

@@ -1413,6 +1423,20 @@ simulateContamination <- function(C = 300,

       verbose = verbose

     )

     background <- background[, !(dupBarcode), drop = FALSE]

+    

+    if(!is.null(bgBatch)){

+      if (length(bgBatch) != length(dupBarcode)) {

+        stop(

+          "Length of bgBatch must be equal to the number of columns",

+          "of background matrix."

+          )

+      }

+      bgBatch <- bgBatch[!(dupBarcode)]

+    }

   }

-  return(background)

+  

+  re = list(background = background,

+            bgBatch = bgBatch)

+  

+  return(re)

 }

@@ -170,7 +170,8 @@ setMethod("decontX", "SingleCellExperiment", function(x,

     # Remove cells with the same ID between x and the background matrix

     background <- .checkBackground(x = x, background = background,

                                    logfile = logfile, verbose = verbose)

-    # Does bgBatch needs to be checked?

+    

+    # TODO: Does bgBatch needs to be checked?

     if (is.null(bgAssayName)) {

       bgAssayName <- assayName

@@ -255,6 +256,9 @@ setMethod("decontX", "ANY", function(x,

     # Remove cells with the same ID between x and the background matrix

     background <- .checkBackground(x = x, background = background,

                                    logfile = logfile, verbose = verbose)

+    

+    # TODO: Does bgBatch needs to be checked?

+    

   }

   .decontX(

@@ -407,9 +411,9 @@ setMethod(

   if (is.null(batch)) {

     batch <- rep("all_cells", nC)

-    # When no batch, batchBackground can have max 1 batch, depending on if

-    # countsBackground supplied

-    batchBackground <- rep("all_cells", ncol(countsBackground))

+    if (!is.null(countsBackground)) {

+      batchBackground <- rep("all_cells", ncol(countsBackground))

+    }

   }

   runParams$batch <- batch

   batchIndex <- unique(batch)

@@ -26,17 +26,17 @@

 #' should be considered different batches. Default NULL.

 #' @param background A numeric matrix of counts or a

 #' \linkS4class{SingleCellExperiment} with the matrix located in the assay

-#' slot under \code{assayName}. It should have the same structure as \code{x}

-#' except it contains the matrix of empty droplets instead of cells. When

-#' supplied, empirical distribution of transcripts from these empty droplets

+#' slot under \code{assayName}. It should have the same data format as \code{x}

+#' except it contains the empty droplets instead of cells. When supplied, 

+#' empirical distribution of transcripts from these empty droplets

 #' will be used as the contamination distribution. Default NULL.

 #' @param bgAssayName Character. Name of the assay to use if \code{background}

 #' is a \linkS4class{SingleCellExperiment}. Default to same as

 #' \code{assayName}.

-#' @param bgBatch Numeric or chracter vector. Batch labels for 

-#' \code{background}. Its unique values should be the same as in \code{batch},

-#' such that each batch of cells have their corresponding background batch.

-#' Default to NULL.

+#' @param bgBatch Numeric or character vector. Batch labels for 

+#' \code{background}. Its unique values should be the same as those in

+#' \code{batch}, such that each batch of cells have their corresponding batch

+#' of empty droplets as background, pointed by this parameter. Default to NULL.

 #' @param maxIter Integer. Maximum iterations of the EM algorithm. Default 500.

 #' @param convergence Numeric. The EM algorithm will be stopped if the maximum

 #' difference in the contamination estimates between the previous and

@@ -170,6 +170,8 @@ setMethod("decontX", "SingleCellExperiment", function(x,

     # Remove cells with the same ID between x and the background matrix

     background <- .checkBackground(x = x, background = background,

                                    logfile = logfile, verbose = verbose)

+    # Does bgBatch needs to be checked?

+    

     if (is.null(bgAssayName)) {

       bgAssayName <- assayName

     }

@@ -392,7 +394,7 @@ setMethod(

   nC <- ncol(counts)

   allCellNames <- colnames(counts)

-  ## Set up final deconaminated matrix

+  ## Set up final decontaminated matrix

   estRmat <- Matrix::Matrix(

     data = 0,

     ncol = totalCells,

@@ -404,6 +406,9 @@ setMethod(

   ## Generate batch labels if none were supplied

   if (is.null(batch)) {

     batch <- rep("all_cells", nC)

+    

+    # When no batch, batchBackground can have max 1 batch, depending on if

+    # countsBackground supplied

     batchBackground <- rep("all_cells", ncol(countsBackground))

   }

   runParams$batch <- batch

@@ -439,6 +444,7 @@ setMethod(

     zBat <- NULL

     countsBat <- counts[, batch == bat]

+    bgBat <- countsBackground[, bactchBackgound == bat]

     ## Convert to sparse matrix

     if (!inherits(countsBat, "dgCMatrix")) {

@@ -451,9 +457,9 @@ setMethod(

       )

       countsBat <- methods::as(countsBat, "dgCMatrix")

     }

-    if (!is.null(countsBackground)) {

-      if (!inherits(countsBackground, "dgCMatrix")) {

-        countsBackground <- methods::as(countsBackground, "dgCMatrix")

+    if (!is.null(bgBat)) {

+      if (!inherits(bgBat, "dgCMatrix")) {

+        bgBat <- methods::as(bgBat, "dgCMatrix")

       }

     }

@@ -465,7 +471,7 @@ setMethod(

         counts = countsBat,

         z = zBat,

         batch = bat,

-        countsBackground = countsBackground,

+        countsBackground = bgBat,

         maxIter = maxIter,

         delta = delta,

         estimateDelta = estimateDelta,

@@ -484,7 +490,7 @@ setMethod(

           counts = countsBat,

           z = zBat,

           batch = bat,

-          countsBackground = countsBackground,

+          countsBackground = bgBat,

           maxIter = maxIter,

           delta = delta,

           estimateDelta = estimateDelta,

@@ -154,6 +154,7 @@ setMethod("decontX", "SingleCellExperiment", function(x,

                                                       batch = NULL,

                                                       background = NULL,

                                                       bgAssayName = NULL,

+                                                      bgBatch = NULL,

                                                       maxIter = 500,

                                                       delta = c(10, 10),

                                                       estimateDelta = TRUE,

@@ -182,6 +183,7 @@ setMethod("decontX", "SingleCellExperiment", function(x,

     z = z,

     batch = batch,

     countsBackground = countsBackground,

+    batchBackground = bgBatch,

     maxIter = maxIter,

     convergence = convergence,

     iterLogLik = iterLogLik,

@@ -234,6 +236,7 @@ setMethod("decontX", "ANY", function(x,

                                      z = NULL,

                                      batch = NULL,

                                      background = NULL,

+                                     bgBatch = NULL,

                                      maxIter = 500,

                                      delta = c(10, 10),

                                      estimateDelta = TRUE,

@@ -257,6 +260,7 @@ setMethod("decontX", "ANY", function(x,

     z = z,

     batch = batch,

     countsBackground = countsBackground,

+    batchBackground = bgBatch,

     maxIter = maxIter,

     convergence = convergence,

     iterLogLik = iterLogLik,

@@ -339,6 +343,7 @@ setMethod(

                      z = NULL,

                      batch = NULL,

                      countsBackground = NULL,

+                     batchBackground = NULL,

                      maxIter = 200,

                      convergence = 0.001,

                      iterLogLik = 10,

@@ -369,6 +374,7 @@ setMethod(

   runParams <- list(

     z = z,

     batch = batch,

+    batchBackground = batchBackground,

     maxIter = maxIter,

     delta = delta,

     estimateDelta = estimateDelta,

@@ -398,6 +404,7 @@ setMethod(

   ## Generate batch labels if none were supplied

   if (is.null(batch)) {

     batch <- rep("all_cells", nC)

+    batchBackground <- rep("all_cells", ncol(countsBackground))

   }

   runParams$batch <- batch

   batchIndex <- unique(batch)

@@ -33,6 +33,10 @@

 #' @param bgAssayName Character. Name of the assay to use if \code{background}

 #' is a \linkS4class{SingleCellExperiment}. Default to same as

 #' \code{assayName}.

+#' @param bgBatch Numeric or chracter vector. Batch labels for 

+#' \code{background}. Its unique values should be the same as in \code{batch},

+#' such that each batch of cells have their corresponding background batch.

+#' Default to NULL.

 #' @param maxIter Integer. Maximum iterations of the EM algorithm. Default 500.

 #' @param convergence Numeric. The EM algorithm will be stopped if the maximum

 #' difference in the contamination estimates between the previous and

@@ -546,7 +546,7 @@ setMethod(

     .logMessages(

       date(),

-      ".. Converting decontaminated matrix to ", class(counts),

+      ".. Converting decontaminated matrix to", class(counts),

       logfile = logfile,

       append = TRUE,

       verbose = verbose

@@ -1372,14 +1372,16 @@ simulateContamination <- function(C = 300,

   if (any(dupBarcode)) {

     .logMessages(

+      date(),

+      ".. ",

       sum(dupBarcode),

-      " columns in the background matrix were removed as they were found in",

+      " cells in the background matrix were removed as they were found in",

       " the filtered matrix.",

       logfile = logfile,

       append = TRUE,

       verbose = verbose

     )

-    background <- background[, !(dupBarcode)]

+    background <- background[, !(dupBarcode), drop = FALSE]

   }

   return(background)

 }

@@ -495,22 +495,21 @@ setMethod(

       z = as.integer(res$z),

       pseudocount = 1e-20

     )

-    

+

     # Speed up sparse matrix value assignment by cbind -> order recovery

-    

-    allCol <- paste0("col_", 1:ncol(estRmat))

+    allCol <- paste0("col_", seq_len(ncol(estRmat)))

     colnames(estRmat) <- allCol

-    

+

     subCol <- paste0("col_", which(batch == bat))

     colnames(estRmat.temp) <- subCol

-    

+

     estRmat <- estRmat[, !(allCol %in% subCol)]

     estRmat <- cbind(estRmat, estRmat.temp)

-    

+

     # Recover order

     estRmat <- estRmat[, allCol]

-    

-    #(Old method) estRmat[seq(nrow(counts)), which(batch == bat)] <- estRmat.temp

+

+    ##estRmat[seq(nrow(counts)), which(batch == bat)] <- estRmat.temp

     dimnames(estRmat) <- list(geneNames, allCellNames)

     resBatch[[bat]] <- list(

@@ -495,7 +495,22 @@ setMethod(

       z = as.integer(res$z),

       pseudocount = 1e-20

     )

-    estRmat[seq(nrow(counts)), which(batch == bat)] <- estRmat.temp

+    

+    # Speed up sparse matrix value assignment by cbind -> order recovery

+    

+    allCol <- paste0("col_", 1:ncol(estRmat))

+    colnames(estRmat) <- allCol

+    

+    subCol <- paste0("col_", which(batch == bat))

+    colnames(estRmat.temp) <- subCol

+    

+    estRmat <- estRmat[, !(allCol %in% subCol)]

+    estRmat <- cbind(estRmat, estRmat.temp)

+    

+    # Recover order

+    estRmat <- estRmat[, allCol]

+    

+    #(Old method) estRmat[seq(nrow(counts)), which(batch == bat)] <- estRmat.temp

     dimnames(estRmat) <- list(geneNames, allCellNames)

     resBatch[[bat]] <- list(

@@ -487,6 +487,17 @@ setMethod(

         )

       )

     }

+

+    ## Try to convert class of new matrix to class of original matrix

+    

+    .logMessages(

+      date(),

+      ".. Calculating final decontaminated matrix",

+      logfile = logfile,

+      append = TRUE,

+      verbose = verbose

+    )

+

     estRmat.temp <- calculateNativeMatrix(

       counts = countsBat,

       theta = res$theta,

@@ -495,6 +506,8 @@ setMethod(

       z = as.integer(res$z),

       pseudocount = 1e-20

     )

+

+    # This part needs to be optimized

     estRmat[seq(nrow(counts)), which(batch == bat)] <- estRmat.temp

     dimnames(estRmat) <- list(geneNames, allCellNames)

@@ -528,19 +541,17 @@ setMethod(

     "z" = returnZ

   )

-  ## Try to convert class of new matrix to class of original matrix

-  if (inherits(counts, "dgCMatrix")) {

+

+  if (inherits(counts, c("DelayedMatrix", "DelayedArray"))) {

+

     .logMessages(

       date(),

-      ".. Finalizing decontaminated matrix",

+      ".. Converting decontaminated matrix to ", class(counts),

       logfile = logfile,

       append = TRUE,

       verbose = verbose

     )

-  }

-

-  if (inherits(counts, c("DelayedMatrix", "DelayedArray"))) {

-

+    

     ## Determine class of seed in DelayedArray

     seed.class <- unique(DelayedArray::seedApply(counts, class))[[1]]

     if (seed.class == "HDF5ArraySeed") {

@@ -162,22 +162,9 @@ setMethod("decontX", "SingleCellExperiment", function(x,

                                                       verbose = TRUE) {

   countsBackground <- NULL

   if (!is.null(background)) {

-    # Remove background barcodes that have already appeared in x

-    dupBarcode <- background$Barcode %in% x$Barcode

-

-    if (any(dupBarcode)) {

-      .logMessages(

-        sum(dupBarcode),

-        " columns in background removed as they are found in filtered matrix",

-        logfile = logfile,

-        append = TRUE,

-        verbose = verbose

-      )

-    }

-

-    background <- background[, !(dupBarcode)]

-

-

+    # Remove cells with the same ID between x and the background matrix

+    background <- .checkBackground(x = x, background = background,

+                                   logfile = logfile, verbose = verbose)

     if (is.null(bgAssayName)) {

       bgAssayName <- assayName

     }

@@ -256,20 +243,9 @@ setMethod("decontX", "ANY", function(x,

   countsBackground <- NULL

   if (!is.null(background)) {

-    # Remove background barcodes that have already appeared in x

-    dupBarcode <- colnames(background) %in% colnames(x)

-

-    if (any(dupBarcode)) {

-      .logMessages(

-        sum(dupBarcode),

-        " columns in background removed as they are found in filtered matrix",

-        logfile = logfile,

-        append = TRUE,

-        verbose = verbose

-      )

-    }

-

-    countsBackground <- background[, !(dupBarcode)]

+    # Remove cells with the same ID between x and the background matrix

+    background <- .checkBackground(x = x, background = background,

+                                   logfile = logfile, verbose = verbose)

   }

   .decontX(

@@ -1368,3 +1344,31 @@ simulateContamination <- function(C = 300,

     )

   )

 }

+

+

+.checkBackground <- function(x, background, logfile = NULL, verbose = FALSE) {

+  # Remove background barcodes that have already appeared in x

+  if(!is.null(colnames(background))) {

+    dupBarcode <- colnames(background) %in% colnames(x)

+  } else {

+    dupBarcode <- FALSE

+    warning("No column names were found for the 'background' matrix. ",

+            "No checking was performed between the ids in the 'backgroud' ",

+            "matrix and 'x'.",

+            " Please ensure that no true cells are included in the background ",

+            "matrix. Otherwise, results will be incorrect.")

+  }

+  

+  if (any(dupBarcode)) {

+    .logMessages(

+      sum(dupBarcode),

+      " columns in the background matrix were removed as they were found in",

+      " the filtered matrix.",

+      logfile = logfile,

+      append = TRUE,

+      verbose = verbose

+    )

+    background <- background[, !(dupBarcode)]

+  }

+  return(background)

+}

@@ -1014,23 +1014,17 @@ addLogLikelihood <- function(llA, llB) {

   }

   sce <- scater::logNormCounts(sce, log = TRUE)

-  if (nrow(sce) <= varGenes) {

-    topVariableGenes <- seq_len(nrow(sce))

-  } else if (nrow(sce) > varGenes) {

-    sce.var <- scran::modelGeneVar(sce)

-    topVariableGenes <- order(sce.var$bio,

-      decreasing = TRUE

-    )[seq(varGenes)]

-  }

-  sce <- sce[topVariableGenes, ]

-

   if (!is.null(seed)) {

     with_seed(

       seed,

-      resUmap <- scater::calculateUMAP(sce, n_threads = 1)

+      resUmap <- scater::calculateUMAP(sce, ntop = varGenes,

+                                       n_threads = 1,

+                                       exprs_values = "logcounts")

     )

   } else {

-    resUmap <- scater::calculateUMAP(sce, n_threads = 1)

+    resUmap <- scater::calculateUMAP(sce, ntop = varGenes,

+                                     n_threads = 1,

+                                     exprs_values = "logcounts")

   }

   z <- NULL

@@ -205,7 +205,7 @@ setMethod("decontX", "SingleCellExperiment", function(x,

   ## Add results into column annotation

   SummarizedExperiment::colData(x)$decontX_contamination <- result$contamination

-  SummarizedExperiment::colData(x)$decontX_clusters <- result$z

+  SummarizedExperiment::colData(x)$decontX_clusters <- as.factor(result$z)

   ## Put estimated UMAPs into SCE

   batchIndex <- unique(result$runParams$batch)

@@ -338,11 +338,13 @@ setGeneric("decontXcounts<-", function(object, ..., value) {

 })

 #' @export

+#' @rdname decontXcounts

 setMethod("decontXcounts", "SingleCellExperiment", GET_FUN("decontXcounts"))

 #' @export

-setReplaceMethod(

-  "decontXcounts", c("SingleCellExperiment", "ANY"),

+#' @rdname decontXcounts

+setMethod(

+  "decontXcounts<-", c("SingleCellExperiment", "ANY"),

   SET_FUN("decontXcounts")

 )

@@ -204,8 +204,8 @@ setMethod("decontX", "SingleCellExperiment", function(x,

   )

   ## Add results into column annotation

-  colData(x)$decontX_contamination <- result$contamination

-  colData(x)$decontX_clusters <- result$z

+  SummarizedExperiment::colData(x)$decontX_contamination <- result$contamination

+  SummarizedExperiment::colData(x)$decontX_clusters <- result$z

   ## Put estimated UMAPs into SCE

   batchIndex <- unique(result$runParams$batch)

@@ -296,14 +296,14 @@ setMethod("decontX", "ANY", function(x,

 GET_FUN <- function(exprs_values, ...) {

   (exprs_values) # To ensure evaluation

   function(object, ...) {

-    assay(object, i = exprs_values, ...)

+    SummarizedExperiment::assay(object, i = exprs_values, ...)

   }

 }

 SET_FUN <- function(exprs_values, ...) {

   (exprs_values) # To ensure evaluation

   function(object, ..., value) {

-    assay(object, i = exprs_values, ...) <- value

+    SummarizedExperiment::assay(object, i = exprs_values, ...) <- value

     object

   }

 }

@@ -168,7 +168,7 @@ setMethod("decontX", "SingleCellExperiment", function(x,

     if (any(dupBarcode)) {

       .logMessages(

         sum(dupBarcode),

-        " columns in background removed because they are found in filtered matrix",

+        " columns in background removed as they are found in filtered matrix",

         logfile = logfile,

         append = TRUE,

         verbose = verbose

@@ -262,7 +262,7 @@ setMethod("decontX", "ANY", function(x,

     if (any(dupBarcode)) {

       .logMessages(

         sum(dupBarcode),

-        " columns in background removed because they are found in filtered matrix",

+        " columns in background removed as they are found in filtered matrix",

         logfile = logfile,

         append = TRUE,

         verbose = verbose

@@ -271,7 +271,7 @@ setMethod("decontX", "ANY", function(x,

     countsBackground <- background[, !(dupBarcode)]

   }

-  

+

   .decontX(

     counts = x,

     z = z,

@@ -30,6 +30,9 @@

 #' except it contains the matrix of empty droplets instead of cells. When

 #' supplied, empirical distribution of transcripts from these empty droplets

 #' will be used as the contamination distribution. Default NULL.

+#' @param bgAssayName Character. Name of the assay to use if \code{background}

+#' is a \linkS4class{SingleCellExperiment}. Default to same as

+#' \code{assayName}.

 #' @param maxIter Integer. Maximum iterations of the EM algorithm. Default 500.

 #' @param convergence Numeric. The EM algorithm will be stopped if the maximum

 #' difference in the contamination estimates between the previous and

@@ -146,6 +149,7 @@ setMethod("decontX", "SingleCellExperiment", function(x,

                                                       z = NULL,