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Per-batch control reference statistics

Source: R/normalize-batch.R
cr_batch_reference.Rd

Summarizes the control cells of every batch: how many there are, and their mean, median and standard deviation for one channel. This table is the reference that cr_standardize_batch() divides by, and it is worth inspecting on its own – a batch with very few control cells, or none at all, is visible here before any standardized value is computed.

Usage

cr_batch_reference(
  experiment,
  channel,
  control_level,
  batch_vars,
  control_var = "treatment",
  sd_floor = 1e-08
)

Arguments

experiment

A cr_experiment.

channel

Channel column to summarize. Must be numeric.

control_level

Value (or values) of control_var that mark the control cells of a batch.

batch_vars

Character vector of columns that jointly define a batch. See cr_batch_key().

control_var

Column holding the treatment assignment. Defaults to "treatment".

sd_floor

Lower bound for the control standard deviation. A batch whose control cells are identical would otherwise divide by zero.

Value

A tibble with one row per batch and the columns

batch_vars

The columns that define the batch.

batch_key

The collapsed batch key.

n_cells

Cells in the batch.

ctrl_n

Control cells with a finite channel value.

ctrl_mean, ctrl_median, ctrl_sd

Control statistics; NA when the batch has no control cells.

has_control

Whether the batch can be standardized.

Details

Both centres are reported deliberately. A right-skewed signal has mean > median, so a downstream gate that compares a well's median against a control mean is silently stricter than the rule it states. Keeping both lets each consumer compare like with like.

See also

cr_standardize_batch(), cr_batch_key()

Other batch standardization functions: cr_batch_key(), cr_correct_batch(), cr_standardize_batch()

Examples

exp <- cr_example_experiment(seed = 1, n_cells_per_well = 20)
exp$design$plate <- rep(c("P1", "P2"), length.out = nrow(exp$design))
cr_batch_reference(exp, channel = "marker_1",
                   control_level = "Untreated", batch_vars = "plate")
#> # A tibble: 2 × 8
#>   plate batch_key n_cells ctrl_n ctrl_mean ctrl_median ctrl_sd has_control
#>   <chr> <chr>       <int>  <int>     <dbl>       <dbl>   <dbl> <lgl>      
#> 1 P1    P1            946    165      806.        450.   1270. TRUE       
#> 2 P2    P2           1015    143      632.        525.    374. TRUE