.CreateStdAssay | R Documentation |
Create an assay object; runs a standardized filtering scheme that
works regardless of the direction of the data (eg. cells as columns
and features as rows or vice versa) and creates an assay object based
on the initialization scheme defined for StdAssay
-derived
class type
.CreateStdAssay(
counts,
min.cells = 0,
min.features = 0,
cells = NULL,
features = NULL,
transpose = FALSE,
type = "Assay5",
...
)
## Default S3 method:
.CreateStdAssay(
counts,
min.cells = 0,
min.features = 0,
cells = NULL,
features = NULL,
transpose = FALSE,
type = "Assay5",
layer = "counts",
...
)
## S3 method for class 'list'
.CreateStdAssay(
counts,
min.cells = 0,
min.features = 0,
cells = NULL,
features = NULL,
transpose = FALSE,
type = "Assay5",
csum = Matrix::colSums,
fsum = Matrix::rowSums,
...
)
## S3 method for class 'Matrix'
.CreateStdAssay(
counts,
min.cells = 0,
min.features = 0,
cells = NULL,
features = NULL,
transpose = FALSE,
type = "Assay5",
layer = "counts",
...
)
## S3 method for class 'matrix'
.CreateStdAssay(
counts,
min.cells = 0,
min.features = 0,
cells = NULL,
features = NULL,
transpose = FALSE,
type = "Assay5",
layer = "counts",
...
)
counts |
A two-dimensional expression matrix |
min.cells |
Include features detected in at least this many cells; will subset the counts matrix as well. To reintroduce excluded features, create a new object with a lower cutoff |
min.features |
Include cells where at least this many features are detected |
cells |
Vector of cell names |
features |
Vector of feature names |
type |
Type of assay object to create; must be the name of a class
that's derived from |
... |
Extra parameters passed to |
layer |
Name of layer to store |
csum |
Function for calculating cell sums |
fsum |
Function for calculating feature sums |
An object of class type
with a layer named layer
containing the data found in counts
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