filterCells | R Documentation |
Filter cells
filterCells(object, ...)
## S4 method for signature 'SingleCellExperiment'
filterCells(
object,
assay = 1L,
minCounts = 1L,
maxCounts = Inf,
minFeatures = 1L,
maxFeatures = Inf,
minNovelty = 0L,
maxMitoRatio = 1L,
minCellsPerFeature = 1L,
nCells = Inf,
countsCol = "nCount",
featuresCol = "nFeature",
noveltyCol = "log10FeaturesPerCount",
mitoRatioCol = "mitoRatio"
)
object |
Object. |
assay |
|
minCounts , maxCounts |
|
minFeatures , maxFeatures |
|
minNovelty |
|
maxMitoRatio |
|
minCellsPerFeature |
|
nCells |
|
countsCol , featuresCol , noveltyCol , mitoRatioCol |
|
... |
Additional arguments. |
Apply feature (i.e. gene/transcript) detection, novelty score, and
mitochondrial abundance cutoffs to cellular barcodes. By default we recommend
applying the same filtering cutoff to all samples. The filtering parameters
now support per-sample cutoffs, defined using a named numeric
vector. When
matching per sample, be sure to use the sampleNames()
return values (i.e.
the sampleName
column in sampleData()
.
Filtering information gets slotted into metadata()
as filterCells
metadata.
SingleCellExperiment
.
Updated 2022-10-24.
data(SingleCellExperiment_splatter, package = "AcidTest")
## SingleCellExperiment ====
object <- SingleCellExperiment_splatter
x <- filterCells(object)
print(x)
## Per sample cutoffs.
x <- filterCells(
object = object,
minCounts = c("sample1" = 100L)
)
print(x)
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