mark_outlier_rows: Mark outlier rows.

In CellProfiler/cytominer: Methods for Image-Based Cell Profiling

Mark outlier rows.

Description

mark_outlier_rows drops outlier rows.

Usage

mark_outlier_rows(
  population,
  variables,
  sample,
  method = "svd+iqr",
  outlier_col = "is_outlier",
  ...
)

Arguments

population	tbl with grouping (metadata) and observation variables.
variables	character vector specifying observation variables.
sample	tbl containing sample that is used by outlier removal methods to estimate parameters. sample has same structure as population. Typically, sample corresponds to controls in the experiment.
method	optional character string specifying method for outlier removal. There is currently only one option ("svd_iqr").
outlier_col	optional character string specifying the name for the column that will indicate outliers (in the output). Default "is_outlier".
...	arguments passed to outlier removal method.

Value

population with an extra column is_outlier.

Examples

suppressMessages(suppressWarnings(library(magrittr)))
population <- tibble::tibble(
  Metadata_group = sample(c("a", "b"), 100, replace = TRUE),
  Metadata_type = sample(c("control", "trt"), 100, replace = TRUE),
  AreaShape_Area = c(rnorm(98), 20, 30),
  AreaShape_Eccentricity = rnorm(100)
)
variables <- c("AreaShape_Area", "AreaShape_Eccentricity")
sample <- population %>% dplyr::filter(Metadata_type == "control")
population_marked <-
  cytominer::mark_outlier_rows(
    population,
    variables,
    sample,
    method = "svd+iqr"
  )
population_marked %>%
  dplyr::group_by(is_outlier) %>%
  dplyr::sample_n(3)

CellProfiler/cytominer documentation built on July 2, 2023, 6:19 p.m.