isOutlier {scater} | R Documentation

## Identify if a cell is an outlier based on a metric

### Description

Convenience function to determine which values for a metric are outliers based on median-absolute-deviation (MAD).

### Usage

    isOutlier(metric, nmads = 5, type = c("both", "lower", "higher"),
      log = FALSE, subset = NULL, batch = NULL, min.diff = NA)

### Arguments

`metric` | numeric or integer vector of values for a metric
`nmads` | scalar, number of median-absolute-deviations away from median required for a value to be called an outlier
`type` | character scalar, choice indicate whether outliers should be looked for at both tails (default: "both") or only at the lower end ("lower") or the higher end ("higher")
`log` | logical, should the values of the metric be transformed to the log10 scale before computing median-absolute-deviation for outlier detection?
`subset` | logical or integer vector, which subset of values should be used to calculate the median/MAD? If `NULL`, all values are used. Missing values will trigger a warning and will be automatically ignored.
`batch` | factor of length equal to `metric`, specifying the batch to which each observation belongs. A median/MAD is calculated for each batch, and outliers are then identified within each batch.
`min.diff` | numeric scalar indicating the minimum difference from the median to consider as an outlier. The outlier threshold is defined from the larger of `nmads` MADs and `min.diff`, to avoid calling many outliers when the MAD is very small. If `NA`, it is ignored.

### Value

a logical vector of the same length as the `metric` argument

### 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 <- calculateQCMetrics(example_sce)

    ## with a set of feature controls defined
    example_sce <- calculateQCMetrics(example_sce,
    feature_controls = list(set1 = 1:40))
    isOutlier(example_sce$total_counts, nmads = 3)

[Package scater version 1.6.3 Index]