Assay-methods: `Assay` Methods

Description

Methods for Assay objects for generics defined in other packages

Usage

# S3 method for Assay
[(x, i, j, ...)
# S3 method for Assay
[[(x, i, ..., drop = FALSE)
# S3 method for Assay
dim(x)
# S3 method for Assay
dimnames(x)
# S3 method for Assay
head(x, n = 10L, ...)
# S3 method for Assay
merge(x = NULL, y = NULL, add.cell.ids = NULL, merge.data = TRUE, ...)
# S3 method for Assay
subset(x, cells = NULL, features = NULL, ...)
# S3 method for Assay
tail(x, n = 10L, ...)
# S4 method for Assay,ANY,ANY,ANY
[[(x, i, j, ...) <- value
# S4 method for Assay
colMeans(x, na.rm = FALSE, dims = 1, ..., slot = "data")
# S4 method for Assay
colSums(x, na.rm = FALSE, dims = 1, ..., slot = "data")
# S4 method for Assay
rowMeans(x, na.rm = FALSE, dims = 1, ..., slot = "data")
# S4 method for Assay
rowSums(x, na.rm = FALSE, dims = 1, ..., slot = "data")
# S4 method for Assay
show(object)

Value

[: The data slot for features i and cells j

[[: The feature-level metadata for i

dim: The number of features (nrow) and cells (ncol)

dimnames: Feature (row) and cell (column) names

head: The first n rows of feature-level metadata

merge: Merged object

subset: A subsetted Assay

tail: The last n rows of feature-level metadata

[[<-: x with metadata value added as i

colMeans: The column (cell-wise) means of slot

colSums: The column (cell-wise) sums of slot

rowMeans: The row (feature-wise) means of slot

rowSums: The row (feature-wise) sums of slot

show: Prints summary to stdout and invisibly returns NULL

Arguments

x, object: An Assay object
i, features: For [[: metadata names; for all other methods, feature names or indices
j, cells: Cell names or indices
...: Arguments passed to other methods
drop: See drop
n: an integer vector of length up to dim(x) (or 1, for non-dimensioned objects). Values specify the indices to be selected in the corresponding dimension (or along the length) of the object. A positive value of n[i] includes the first/last n[i] indices in that dimension, while a negative value excludes the last/first abs(n[i]), including all remaining indices. NA or non-specified values (when length(n) < length(dim(x))) select all indices in that dimension. Must contain at least one non-missing value.
y: A vector or list of one or more objects to merge
add.cell.ids: A character vector of length(x = c(x, y)); appends the corresponding values to the start of each objects' cell names
merge.data: Merge the data slots instead of just merging the counts (which requires renormalization); this is recommended if the same normalization approach was applied to all objects
value: Additional metadata to add
na.rm: logical. Should missing values (including NaN) be omitted from the calculations?
dims: completely ignored by the Matrix methods.
slot: Name of assay expression matrix to calculate column/row means/sums on

Functions

[: Get expression data from an Assay
[[: Get feature-level metadata
dim(Assay): Number of cells and features for an Assay
dimnames(Assay): Cell- and feature-names for an Assay
head(Assay): Get the first rows of feature-level metadata
merge(Assay): Merge Assay objects
subset(Assay): Subset an Assay
tail(Assay): Get the last rows of feature-level metadata
`[[`(x = Assay, i = ANY, j = ANY) <- value: Add feature-level metadata
colMeans(Assay): Calculate colMeans on an Assay
colSums(Assay): Calculate colSums on an Assay
rowMeans(Assay): Calculate rowMeans on an Assay
rowSums(Assay): Calculate rowSums on an Assay
show(Assay): Overview of an Assay object