normalizeCounts {scater}R Documentation

Compute normalized expression values

Description

Compute (log-)normalized expression values by dividing counts for each cell by the corresponding size factor.

Usage

normalizeCounts(x, ...)

## S4 method for signature 'ANY'
normalizeCounts(x, size_factors = NULL,
  use_size_factors = NULL, log = TRUE, return_log = NULL,
  pseudo_count = 1, log_exprs_offset = NULL,
  center_size_factors = TRUE, subset_row = NULL, downsample = FALSE,
  down_target = NULL, down_prop = 0.01)

## S4 method for signature 'SummarizedExperiment'
normalizeCounts(x, ...,
  exprs_values = "counts")

## S4 method for signature 'SingleCellExperiment'
normalizeCounts(x, size_factors = NULL,
  ...)

Arguments

x

A numeric matrix-like object containing counts for cells in the columns and features in the rows.

Alternatively, a SingleCellExperiment or SummarizedExperiment object containing such a count matrix.

...

For the generic, arguments to pass to specific methods.

For the SummarizedExperiment method, further arguments to pass to the ANY or DelayedMatrix methods.

For the SingleCellExperiment method, further arguments to pass to the SummarizedExperiment method.

size_factors

A numeric vector of cell-specific size factors. Alternatively NULL, in which case the size factors are extracted or computed from x.

use_size_factors

Deprecated, same as size_factors.

log

Logical scalar indicating whether normalized values should be log2-transformed.

return_log

Deprecated, same as log.

pseudo_count

Numeric scalar specifying the pseudo_count to add when log-transforming expression values.

log_exprs_offset

Deprecated, same as pseudo_count.

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 a result.

downsample

Logical scalar indicating whether downsampling should be performed prior to scaling and log-transformation.

down_target

Numeric scalar specifying the downsampling target when downsample=TRUE. If NULL, this is defined by down_prop and a warning is emitted.

down_prop

Numeric scalar between 0 and 1 indicating the quantile to use to define the downsampling target when downsample=TRUE.

exprs_values

A string or integer scalar specifying the assay of x containing the count matrix.

Details

Normalized expression values are computed by dividing the counts for each cell by the size factor for that cell. This aims to remove cell-specific scaling biases, e.g., due to differences in sequencing coverage or capture efficiency. If log=TRUE, log-normalized values are calculated by adding pseudo_count to the normalized count and performing a log2 transformation.

If no size factors are supplied, they are determined automatically from x:

If size_factors are supplied, they will override any size factors present in x.

If center_size_factors=TRUE, size factors are centred at unity prior to calculation of normalized expression values. This means that the computed expression values can be interpreted as being on the same scale as log-counts, and that the value of pseudo_count can be interpreted as being on the same scale as the counts. It also ensures that abundances are roughly comparable between features normalized with different sets of size factors.

Value

A matrix-like object of (log-)normalized expression values.

Downsampling instead of scaling

If downsample=TRUE, counts for each cell are randomly downsampled according to their size factors prior to log-transformation. This is occasionally useful for avoiding artifacts caused by scaling count data with a strong mean-variance relationship. Each cell is downsampled according to the ratio between down_target and that cell's size factor. (Cells with size factors below the target are not downsampled and are directly scaled by this ratio.) If log=TRUE, a log-transformation is also performed after adding pseudo_count to the downsampled counts.

Note that the normalized expression values in this mode cannot be interpreted as being on the same abundance as the original counts, but instead have abundance equivalent to counts after downsampling to the target size factor. This motivates the use of a fixed down_target to ensure that expression values are comparable across different normalizeCounts calls. We automatically set down_target to the 1st percentile of size factors across all cells involved in the analysis, but this is only appropriate if the resulting expression values are only compared within the same call to normalizeCounts. If expression values are to be compared across multiple calls (e.g., in modelGeneVarWithSpikes or multiBatchNorm), down_target should be manually set to a constant target value that can be considered a low size factor in every call.

Author(s)

Aaron Lun

See Also

logNormCounts, which wraps this function for convenient use with SingleCellExperiment instances.

downsampleMatrix, to perform the downsampling.

Examples

example_sce <- mockSCE()
normed <- normalizeCounts(example_sce)
str(normed)

[Package scater version 1.14.0 Index]