Husk data. — husk • cytominer

husk detects unwanted variation in the sample and removes it from the population.

husk(
  population,
  variables,
  sample,
  remove_outliers = TRUE,
  epsilon = 1e-06,
  remove_signal = TRUE,
  flatten_noise = TRUE
)

Arguments

population	tbl with grouping (metadata) and observation variables.
variables	character vector specifying observation variables.
sample	tbl containing sample that is used by the method to estimate husking parameters. `sample` has same structure as `population`. Typically, `sample` corresponds to controls in the experiment.
remove_outliers	optional boolean specifying whether to remove outliers. Default is `TRUE`.
epsilon	optional parameter used in husking to offset eigenvalues to avoid division by zero. Default is `1`.
remove_signal	optional boolean specifying whether to husk the signal instead of only scaling it down. Default is `TRUE`.
flatten_noise	optional boolean specifying whether to flatten the noise instead of scaling it up. Default is `TRUE`. The parameter is ignored if `remove_signal` is `FALSE`.

Value

transformed data of the same class as population.

Examples

population <- tibble::tibble(
  Metadata_pert_name = c(NA, NA, NA, NA),
  Metadata_Well = c("A01", "A02", "B01", "B02"),
  Intensity_DNA = c(10, 20, 12, 32),
  Granularity_DNA = c(22, 20, NA, 32),
  Texture_DNA = c(5, 2, 43, 13)
)
variables <- c("Intensity_DNA", "Texture_DNA")
husk(population, variables, population, epsilon = 1, remove_signal = TRUE)
#> # A tibble: 4 x 5
#>   Metadata_pert_name Metadata_Well Granularity_DNA      V1     V2
#>   <lgl>              <chr>                   <dbl>   <dbl>  <dbl>
#> 1 NA                 A01                        22 -0.0797 -0.411
#> 2 NA                 A02                        20  0.576   0.160
#> 3 NA                 B01                        NA -0.497   0.251
#> 4 NA                 B02                        32  1.16    1.05 
husk(population, variables, population, epsilon = 1e-5, remove_signal = TRUE)
#> # A tibble: 4 x 5
#>   Metadata_pert_name Metadata_Well Granularity_DNA     V1     V2
#>   <lgl>              <chr>                   <dbl>  <dbl>  <dbl>
#> 1 NA                 A01                        22 -0.147 -0.760
#> 2 NA                 A02                        20  1.07   0.295
#> 3 NA                 B01                        NA -0.918  0.465
#> 4 NA                 B02                        32  2.14   1.94 
husk(population, variables, population, epsilon = 1, remove_signal = FALSE)
#> # A tibble: 4 x 5
#>   Metadata_pert_name Metadata_Well Granularity_DNA      V1     V2
#>   <lgl>              <chr>                   <dbl>   <dbl>  <dbl>
#> 1 NA                 A01                        22 -0.0797 -0.503
#> 2 NA                 A02                        20  0.576   0.195
#> 3 NA                 B01                        NA -0.497   0.307
#> 4 NA                 B02                        32  1.16    1.29 
husk(population, variables, population, epsilon = 1e-5, remove_signal = FALSE)
#> # A tibble: 4 x 5
#>   Metadata_pert_name Metadata_Well Granularity_DNA     V1     V2
#>   <lgl>              <chr>                   <dbl>  <dbl>  <dbl>
#> 1 NA                 A01                        22 -0.147 -1.15 
#> 2 NA                 A02                        20  1.07   0.445
#> 3 NA                 B01                        NA -0.918  0.700
#> 4 NA                 B02                        32  2.14   2.93