R/runBatchCorrection.R
runSCANORAMA.Rd
SCANORAMA is analogous to computer vision algorithms for panorama stitching that identify images with overlapping content and merge these into a larger panorama.
runSCANORAMA(
inSCE,
useAssay = "logcounts",
batch = "batch",
SIGMA = 15,
ALPHA = 0.1,
KNN = 20L,
assayName = "SCANORAMA"
)
SingleCellExperiment inherited object. Required.
A single character indicating the name of the assay requiring
batch correction. Scanorama requires a transformed normalized expression
assay. Default "logcounts"
.
A single character indicating a field in
colData
that annotates the batches.
Default "batch"
.
A numeric scalar. Algorithmic parameter, correction smoothing
parameter on Gaussian kernel. Default 15
.
A numeric scalar. Algorithmic parameter, alignment score
minimum cutoff. Default 0.1
.
An integer. Algorithmic parameter, number of nearest neighbors to
use for matching. Default 20L
.
A single characeter. The name for the corrected assay. Will
be saved to assay
. Default
"SCANORAMA"
.
The input SingleCellExperiment object with
assay(inSCE, assayName)
updated.
Brian Hie et al, 2019
if (FALSE) {
data('sceBatches', package = 'singleCellTK')
sceBatches <- scaterlogNormCounts(sceBatches)
sceCorr <- runSCANORAMA(sceBatches, "ScaterLogNormCounts")
}