Detect low-expression (i.e. potentially failed) channels in high-dimensional cytometry data

Usage

tof_assess_channels(
  tof_tibble,
  channel_cols = where(tof_is_numeric),
  negative_threshold = asinh(10/5),
  negative_proportion_flag = 0.95
)

Arguments

tof_tibble: A `tof_tbl` or `tibble`.
channel_cols: A vector of unquoted column names representing columns that contain single-cell protein measurements. Supports tidyselect helpers. If nothing is specified, the default is to analyze all numeric columns.
negative_threshold: A scalar indicating the threshold below which a measurement should be considered negative. Defaults to the hyperbolic arcsine transformation of 10 counts.
negative_proportion_flag: A scalar between 0 and 1 indicating the proportion of cells in tof_tibble that need to be below `negative_threshold` for a given marker in order for that marker to be flagged. Defaults to 0.95.

Value

A tibble 3 columns and a number of rows equal to the number of columns in `tof_tibble` chosen by `channel_cols`. The three columns are "channel", a character vector of channel names, "negative_proportion", a numeric vector with values between 0 and 1 indicating how many cells in `tof_tibble` below `negative_threshold` for each channel, and `flagged_channel`, a boolean vector indicating whether or not a channel has been flagged as potentially failed (TRUE means that the channel had a large number of cells below `negative_threshold`).

Examples

# simulate some data
sim_data <-
    data.frame(
        cd4 = rnorm(n = 100, mean = 5, sd = 0.5),
        cd8 = rnorm(n = 100, mean = 0, sd = 0.1),
        cd33 = rnorm(n = 100, mean = 10, sd = 0.1)
    )

tof_assess_channels(tof_tibble = sim_data)
#> # A tibble: 3 × 3
#>   channel negative_proportion flagged_channel
#>   <chr>                 <dbl> <lgl>          
#> 1 cd8                       1 TRUE           
#> 2 cd4                       0 FALSE          
#> 3 cd33                      0 FALSE          

tof_assess_channels(tof_tibble = sim_data, channel_cols = c(cd4, cd8))
#> # A tibble: 2 × 3
#>   channel negative_proportion flagged_channel
#>   <chr>                 <dbl> <lgl>          
#> 1 cd8                       1 TRUE           
#> 2 cd4                       0 FALSE          

tof_assess_channels(tof_tibble = sim_data, negative_threshold = 2)
#> # A tibble: 3 × 3
#>   channel negative_proportion flagged_channel
#>   <chr>                 <dbl> <lgl>          
#> 1 cd8                       1 TRUE           
#> 2 cd4                       0 FALSE          
#> 3 cd33                      0 FALSE