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Assay-methods

Assay Methods

Description

Methods for Assay objects for generics defined in other packages

Usage

## S3 method for class 'Assay'
x[i, j, ...]

## S3 method for class 'Assay'
x[[i, ..., drop = FALSE]]

## S3 method for class 'Assay'
dim(x)

## S3 method for class 'Assay'
dimnames(x)

## S3 method for class 'Assay'
head(x, n = 10L, ...)

## S3 method for class 'Assay'
merge(x = NULL, y = NULL, add.cell.ids = NULL, merge.data = TRUE, ...)

## S3 method for class 'Assay'
subset(x, cells = NULL, features = NULL, ...)

## S3 method for class 'Assay'
tail(x, n = 10L, ...)

## S4 replacement method for signature 'Assay'
x[[i, j, ...]] <- value

## S4 method for signature 'Assay'
colMeans(x, na.rm = FALSE, dims = 1, ..., slot = "data")

## S4 method for signature 'Assay'
colSums(x, na.rm = FALSE, dims = 1, ..., slot = "data")

## S4 method for signature 'Assay'
rowMeans(x, na.rm = FALSE, dims = 1, ..., slot = "data")

## S4 method for signature 'Assay'
rowSums(x, na.rm = FALSE, dims = 1, ..., slot = "data")

## S4 method for signature 'Assay'
show(object)

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

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

Functions

  • [.Assay: Get expression data from an Assay

  • [[.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

  • [[<-,Assay-method: Add feature-level metadata

  • colMeans,Assay-method: Calculate colMeans on an Assay

  • colSums,Assay-method: Calculate colSums on an Assay

  • rowMeans,Assay-method: Calculate rowMeans on an Assay

  • rowSums,Assay-method: Calculate rowSums on an Assay

  • show,Assay-method: Overview of an Assay object

SeuratObject

Data Structures for Single Cell Data

v4.0.1
GPL-3
Authors
Rahul Satija [aut] (<https://orcid.org/0000-0001-9448-8833>), Andrew Butler [aut] (<https://orcid.org/0000-0003-3608-0463>), Paul Hoffman [aut, cre] (<https://orcid.org/0000-0002-7693-8957>), Tim Stuart [aut] (<https://orcid.org/0000-0002-3044-0897>), Jeff Farrell [ctb], Shiwei Zheng [ctb] (<https://orcid.org/0000-0001-6682-6743>), Christoph Hafemeister [ctb] (<https://orcid.org/0000-0001-6365-8254>), Patrick Roelli [ctb], Yuhan Hao [ctb] (<https://orcid.org/0000-0002-1810-0822>)
Initial release
2021-05-07

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