inferSingleCellGradient | R Documentation |
Integration of single cell deconvolution and SPATA2s image annotations.
inferSingleCellGradient(
object,
sc_input,
id,
calculate = "density",
distance = NA_integer_,
n_bins_circle = NA_integer_,
binwidth = getCCD(object),
angle_span = c(0, 360),
n_bins_angle = 1,
remove_circle_bins = "Outside",
normalize = TRUE,
area_unit = NULL,
format = "wide",
as_models = FALSE
)
object |
An object of class |
sc_input |
Data.frame that contains the results from single cell deconvolution. Must have at least three columns:
|
id |
Character value. The ID of the image annotation of interest. |
distance |
Distance value. Specifies the distance from the border of the
image annotation to the horizon in the periphery up to which the screening
is conducted. (See details for more.) - See details of |
n_bins_circle |
Numeric value or vector of length 2. Specifies how many times the area is buffered with the value
denoted in |
binwidth |
Distance value. The width of the circular bins to which
the barcode-spots are assigned. We recommend to set it equal to the center-center
distance: |
angle_span |
Numeric vector of length 2. Confines the area screened by an angle span relative to the center of the image annotation. (See details fore more.) |
n_bins_angle |
Numeric value. Number of bins that are created by angle. (See details for more.) |
normalize |
Logical. If set to TRUE values will be scaled to 0-1. Hint: Variables that are uniformly expressed can not be scaled and are discarded. |
as_models |
Adjusts the output to a list that is a valid input for
|
Data.frame as is returned by getIasDf()
with cell types as variables.
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