| ... | ... |
@@ -100,20 +100,16 @@ |
| 100 | 100 |
#' @importFrom BiocGenerics sizeFactors sizeFactors<- cbind |
| 101 | 101 |
#' @importFrom scuttle logNormCounts librarySizeFactors .unpackLists |
| 102 | 102 |
#' @importFrom SingleCellExperiment altExp altExp<- |
| 103 |
-multiBatchNorm <- function(..., batch=NULL, assay.type="counts", norm.args=list(), as.altexp=NULL, |
|
| 104 |
- min.mean=1, subset.row=NULL, normalize.all=FALSE, preserve.single=TRUE, BPPARAM=SerialParam()) |
|
| 103 |
+multiBatchNorm <- function(..., batch=NULL, norm.args=list(), |
|
| 104 |
+ min.mean=1, subset.row=NULL, normalize.all=FALSE, preserve.single=TRUE, |
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| 105 |
+ assay.type="counts", as.altexp=NULL, BPPARAM=SerialParam()) |
|
| 105 | 106 |
{
|
| 106 | 107 |
batches <- .unpackLists(...) |
| 107 |
- checkBatchConsistency(batches) |
|
| 108 |
- if (length(batches)==0L) {
|
|
| 109 |
- stop("at least one SingleCellExperiment must be supplied")
|
|
| 110 |
- } |
|
| 111 |
- |
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| 112 |
- # Setting up the parallelization environment. |
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| 113 |
- if (.bpNotSharedOrUp(BPPARAM)) {
|
|
| 114 |
- bpstart(BPPARAM) |
|
| 115 |
- on.exit(bpstop(BPPARAM), add=TRUE) |
|
| 108 |
+ if (!is.null(as.altexp)) {
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|
| 109 |
+ originals <- batches |
|
| 110 |
+ batches <- lapply(batches, altExp, e=as.altexp) |
|
| 116 | 111 |
} |
| 112 |
+ checkBatchConsistency(batches) |
|
| 117 | 113 |
|
| 118 | 114 |
# Handling the batch= and preserve.single= options. |
| 119 | 115 |
if (length(batches)==1L) {
|
| ... | ... |
@@ -122,20 +118,30 @@ multiBatchNorm <- function(..., batch=NULL, assay.type="counts", norm.args=list( |
| 122 | 118 |
} |
| 123 | 119 |
|
| 124 | 120 |
if (!preserve.single) {
|
| 125 |
- sce <- batches[[1]] |
|
| 126 | 121 |
by.batch <- split(seq_along(batch), batch) |
| 127 |
- batches <- by.batch |
|
| 128 |
- for (i in seq_along(by.batch)) {
|
|
| 129 |
- batches[[i]] <- sce[,by.batch[[i]],drop=FALSE] |
|
| 122 |
+ FRAGMENT <- function(target) {
|
|
| 123 |
+ batches <- by.batch |
|
| 124 |
+ for (i in seq_along(by.batch)) {
|
|
| 125 |
+ batches[[i]] <- target[,by.batch[[i]],drop=FALSE] |
|
| 126 |
+ } |
|
| 127 |
+ batches |
|
| 128 |
+ } |
|
| 129 |
+ |
|
| 130 |
+ batches <- FRAGMENT(batches[[1]]) |
|
| 131 |
+ if (!is.null(as.altexp)) {
|
|
| 132 |
+ originals <- FRAGMENT(originals[[1]]) |
|
| 130 | 133 |
} |
| 131 | 134 |
} |
| 135 |
+ } else if (length(batches)==0L) {
|
|
| 136 |
+ stop("at least one SingleCellExperiment must be supplied")
|
|
| 132 | 137 |
} else {
|
| 133 | 138 |
preserve.single <- FALSE |
| 134 | 139 |
} |
| 135 | 140 |
|
| 136 |
- if (!is.null(as.altexp)) {
|
|
| 137 |
- originals <- batches |
|
| 138 |
- batches <- lapply(batches, altExp, e=as.altexp) |
|
| 141 |
+ # Setting up the parallelization environment. |
|
| 142 |
+ if (.bpNotSharedOrUp(BPPARAM)) {
|
|
| 143 |
+ bpstart(BPPARAM) |
|
| 144 |
+ on.exit(bpstop(BPPARAM), add=TRUE) |
|
| 139 | 145 |
} |
| 140 | 146 |
|
| 141 | 147 |
# Computing the averages and the size factors. |
| ... | ... |
@@ -7,13 +7,13 @@ |
| 7 | 7 |
multiBatchNorm( |
| 8 | 8 |
..., |
| 9 | 9 |
batch = NULL, |
| 10 |
- assay.type = "counts", |
|
| 11 | 10 |
norm.args = list(), |
| 12 |
- as.altexp = NULL, |
|
| 13 | 11 |
min.mean = 1, |
| 14 | 12 |
subset.row = NULL, |
| 15 | 13 |
normalize.all = FALSE, |
| 16 | 14 |
preserve.single = TRUE, |
| 15 |
+ assay.type = "counts", |
|
| 16 |
+ as.altexp = NULL, |
|
| 17 | 17 |
BPPARAM = SerialParam() |
| 18 | 18 |
) |
| 19 | 19 |
} |
| ... | ... |
@@ -30,13 +30,8 @@ this is flattened as if the objects inside were passed directly to \code{...}.}
|
| 30 | 30 |
\item{batch}{A factor specifying the batch of origin for all cells when only a single object is supplied in \code{...}.
|
| 31 | 31 |
This is ignored if multiple objects are present.} |
| 32 | 32 |
|
| 33 |
-\item{assay.type}{A string specifying which assay values contains the counts.}
|
|
| 34 |
- |
|
| 35 | 33 |
\item{norm.args}{A named list of further arguments to pass to \code{\link[scuttle]{logNormCounts}}.}
|
| 36 | 34 |
|
| 37 |
-\item{as.altexp}{String or integer scalar indicating the alternative Experiment to use in the function (see below for details).
|
|
| 38 |
-All entries of \code{...} must contain the specified entry in their \code{\link{altExps}}.}
|
|
| 39 |
- |
|
| 40 | 35 |
\item{min.mean}{A numeric scalar specifying the minimum (library size-adjusted) average count of genes to be used for normalization.}
|
| 41 | 36 |
|
| 42 | 37 |
\item{subset.row}{A vector specifying which features to use for normalization.}
|
| ... | ... |
@@ -45,6 +40,11 @@ All entries of \code{...} must contain the specified entry in their \code{\link{
|
| 45 | 40 |
|
| 46 | 41 |
\item{preserve.single}{A logical scalar indicating whether to combine the results into a single matrix if only one object was supplied in \code{...}.}
|
| 47 | 42 |
|
| 43 |
+\item{assay.type}{A string specifying which assay values contains the counts.}
|
|
| 44 |
+ |
|
| 45 |
+\item{as.altexp}{String or integer scalar indicating the alternative Experiment to use in the function (see below for details).
|
|
| 46 |
+All entries of \code{...} must contain the specified entry in their \code{\link{altExps}}.}
|
|
| 47 |
+ |
|
| 48 | 48 |
\item{BPPARAM}{A \linkS4class{BiocParallelParam} object specifying whether calculations should be parallelized.}
|
| 49 | 49 |
} |
| 50 | 50 |
\value{
|
