R/runBatchCorrection.R
runFastMNN.Rd
fastMNN is a variant of the classic MNN method, modified for speed and more
robust performance. For introduction of MNN, see runMNNCorrect
.
runFastMNN(
inSCE,
useAssay = "logcounts",
useReducedDim = NULL,
batch = "batch",
reducedDimName = "fastMNN",
k = 20,
propK = NULL,
ndist = 3,
minBatchSkip = 0,
cosNorm = TRUE,
nComponents = 50,
weights = NULL,
BPPARAM = BiocParallel::SerialParam()
)
Input SingleCellExperiment object
A single character indicating the name of the assay requiring
batch correction. Default "logcounts"
.
A single character indicating the dimension reduction
used for batch correction. Will ignore useAssay
when using.
Default NULL
.
A single character indicating a field in colData
that
annotates the batches of each cell; or a vector/factor with the same length
as the number of cells. Default "batch"
.
A single character. The name for the corrected
low-dimensional representation. Default "fastMNN"
.
An integer scalar specifying the number of nearest neighbors to
consider when identifying MNNs. See "See Also". Default 20
.
A numeric scalar in (0, 1) specifying the proportion of cells in
each dataset to use for mutual nearest neighbor searching. See "See Also".
Default NULL
.
A numeric scalar specifying the threshold beyond which
neighbours are to be ignored when computing correction vectors. See "See
Also". Default 3
.
Numeric scalar specifying the minimum relative magnitude
of the batch effect, below which no correction will be performed at a given
merge step. See "See Also". Default 0
.
A logical scalar indicating whether cosine normalization
should be performed on useAssay
prior to PCA. See "See Also". Default
TRUE
.
An integer scalar specifying the number of dimensions to
produce. See "See Also". Default 50
.
The weighting scheme to use. Passed to
multiBatchPCA
. Default NULL
.
A BiocParallelParam object specifying whether the SVD should be parallelized.
The input SingleCellExperiment object with
reducedDim(inSCE, reducedDimName)
updated.
Lun ATL, et al., 2016
fastMNN
for using useAssay
, and
reducedMNN
for using useReducedDim