R: Compute log-normalized expression values

logNormCounts {scuttle}

R Documentation

Compute log-normalized expression values

Description

Compute log-transformed normalized expression values from a count matrix in a SingleCellExperiment object.

Usage

logNormCounts(x, ...)

## S4 method for signature 'SummarizedExperiment'
logNormCounts(
  x,
  size.factors = NULL,
  log = NULL,
  transform = c("log", "none", "asinh"),
  pseudo.count = 1,
  center.size.factors = TRUE,
  ...,
  subset.row = NULL,
  normalize.all = FALSE,
  assay.type = "counts",
  name = NULL,
  BPPARAM = SerialParam(),
  size_factors = NULL,
  pseudo_count = NULL,
  center_size_factors = NULL,
  exprs_values = NULL
)

## S4 method for signature 'SingleCellExperiment'
logNormCounts(
  x,
  size.factors = sizeFactors(x),
  log = NULL,
  transform = c("log", "none", "asinh"),
  pseudo.count = 1,
  center.size.factors = TRUE,
  ...,
  subset.row = NULL,
  normalize.all = FALSE,
  assay.type = "counts",
  use.altexps = FALSE,
  name = NULL,
  BPPARAM = SerialParam(),
  size_factors = NULL,
  pseudo_count = NULL,
  center_size_factors = NULL,
  exprs_values = NULL,
  use_altexps = NULL
)

Arguments

`x`	A SingleCellExperiment or SummarizedExperiment object containing a count matrix.
`...`	For the generic, additional arguments passed to specific methods. For the methods, additional arguments passed to `normalizeCounts`.
`size.factors`	A numeric vector of cell-specific size factors. Alternatively `NULL`, in which case the size factors are computed from `x`.
`log`	Logical scalar indicating whether normalized values should be log2-transformed. This is retained for back-compatibility and will override any setting of `transform`. Users should generally use `transform` instead to specify the transformation.
`transform`	String specifying the transformation (if any) to apply to the normalized expression values.
`pseudo.count`	Numeric scalar specifying the pseudo-count to add when `transform="log"`.
`center.size.factors`	Logical scalar indicating whether size factors should be centered at unity before being used.
`subset.row`	A vector specifying the subset of rows of `x` for which to return normalized values. If `size.factors=NULL`, the size factors are also computed from this subset.
`normalize.all`	Logical scalar indicating whether to return normalized values for all genes. If `TRUE`, any non-`NULL` value for `subset.row` is only used to compute the size factors. Ignored if `subset.row=NULL` or `size.factors` is supplied.
`assay.type`	A string or integer scalar specifying the assay of `x` containing the count matrix.
`name`	String containing an assay name for storing the output normalized values. Defaults to `"logcounts"` when `transform="log"`, `"ashcounts"` when `transform="asinh"`, and `"normcounts"` otherwise.
`BPPARAM`	A BiocParallelParam object specifying how library size factor calculations should be parallelized. Only used if `size.factors` is not specified.
`size_factors`	Soft-deprecated equivalents to the arguments described previously.
`pseudo_count`	Soft-deprecated equivalents to the arguments described previously.
`center_size_factors`	Soft-deprecated equivalents to the arguments described previously.
`exprs_values`	Soft-deprecated equivalents to the arguments described previously.
`use.altexps, use_altexps`	Deprecated, use `applySCE` instead (see Examples).

Details

This function is a convenience wrapper around normalizeCounts. It returns a SingleCellExperiment or SummarizedExperiment containing the normalized values in a separate assay. This makes it easier to perform normalization by avoiding book-keeping errors during a long analysis workflow.

If NULL, size factors are determined as described in normalizeCounts. subset.row and normalize.all have the same interpretation as for normalizeCounts.

Value

x is returned containing the (log-)normalized expression values in an additional assay named as name.

If x is a SingleCellExperiment, the size factors used for normalization are stored in sizeFactors. These are centered if center.size.factors=TRUE.

Author(s)

Aaron Lun, based on code by Davis McCarthy

Examples

example_sce <- mockSCE()

# Standard library size normalization:
example_sce2 <- logNormCounts(example_sce)
assayNames(example_sce2)
logcounts(example_sce2)[1:5,1:5]

# Without logging, the assay is 'normcounts':
example_sce2 <- logNormCounts(example_sce, log=FALSE)
assayNames(example_sce2)
normcounts(example_sce2)[1:5,1:5]

# Pre-loading with size factors:
example_sce2 <- computeMedianFactors(example_sce)
example_sce2 <- logNormCounts(example_sce2)
logcounts(example_sce2)[1:5,1:5]

# Also normalizing the alternative experiments:
example_sce2 <- applySCE(example_sce, logNormCounts)
logcounts(altExp(example_sce2))[1:5,1:5]

[Package scuttle version 1.2.1 Index]