calculateAverage {scater} | R Documentation

## Calculate average counts, adjusting for size factors or library size

### Description

Calculate average counts per feature, adjusting them to account for normalization due to size factors or library sizes.

### Usage

    calculateAverage(object, exprs_values = "counts",
      use_size_factors = TRUE, subset_row = NULL,
      BPPARAM = SerialParam())

    calcAverage(object, exprs_values = "counts", use_size_factors = TRUE,
      subset_row = NULL, BPPARAM = SerialParam())

### Arguments

`object` | A SingleCellExperiment object or count matrix.
`exprs_values` | A string specifying the assay of `object` containing the count matrix, if `object` is a SingleCellExperiment.
`use_size_factors` | a logical scalar specifying whether the size factors in `object` should be used to construct effective library sizes.
`subset_row` | A vector specifying the subset of rows of `object` for which to return a result.
`BPPARAM` | A BiocParallelParam object specifying whether the calculations should be parallelized.

### Details

The size-adjusted average count is defined by dividing each count by the size factor and taking the average across cells. All sizes factors are scaled so that the mean is 1 across all cells, to ensure that the averages are interpretable on the scale of the raw counts.

Assuming that `object` is a SingleCellExperiment:

- If `use_size_factors=TRUE`, size factors are automatically extracted from the object. Note that different size factors may be used for features marked as spike-in controls. This is due to the presence of control-specific size factors in `object`, see `normalizeSCE` for more details.

- If `use_size_factors=FALSE`, all size factors in `object` are ignored. Size factors are instead computed from the library sizes, using `librarySizeFactors`.

- If `use_size_factors` is a numeric vector, it will override the any size factors for non-spike-in features in `object`. The spike-in size factors will still be used for the spike-in transcripts.

If no size factors are available, they will be computed from the library sizes using `librarySizeFactors`.

If `object` is a matrix or matrix-like object, size factors can be supplied by setting `use_size_factors` to a numeric vector. Otherwise, the sum of counts for each cell is used as the size factor through `librarySizeFactors`.

### Value

Vector of average count values with same length as number of features, or the number of features in `subset_row` if supplied.

### Examples

    data("sc_example_counts")
    data("sc_example_cell_info")
    example_sce <- SingleCellExperiment(
       list(counts = sc_example_counts),
       colData = sc_example_cell_info)

    ## calculate average counts
    ave_counts <- calculateAverage(example_sce)

[Package scater version 1.12.2 Index]