getVarianceExplained {scater} | R Documentation

## Estimate the percentage of variance explained for each gene.

### Description

Estimate the percentage of variance explained for each gene.

### Usage

    getVarianceExplained(object, exprs_values = "logcounts",
      variables = NULL, chunk = 1000)

### Arguments

`object` | A SingleCellExperiment object containing expression values and per-cell experimental information.
`exprs_values` | String specifying the expression values for which to compute the variance.
`variables` | Character vector specifying the explanatory factors in `colData(object)` to use. Default is `NULL`, in which case all variables in `colData(object)` are considered.
`chunk` | Integer scalar specifying the chunk size for chunk-wise processing. Only affects the speed/memory usage trade-off.

### Details

This function computes the percentage of variance in gene expression that is explained by variables in the sample-level metadata. It allows problematic factors to be quickly identified, as well as the genes that are most affected.

### Value

A matrix containing the percentage of variance explained by each factor (column) and for each gene (row).

### Author(s)

Aaron Lun

### See Also

`plotExplanatoryVariables`

### Examples

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

    r2mat <- getVarianceExplained(example_sce)

[Package scater version 1.12.2 Index]