Attach indicator columns to intens_dat based on gates provided in cutoffs

Adds an indicator column (0/1) to intens_dat for each marker in cutoffs as indicated by the columns in cutoffs

Usage

getGatedDat(intens_dat = intensity_dat, cutoffs, subset_col)

Arguments

intens_dat: dataframe of pre-gated (compensated, biexp. transf, openCyto steps) intensity values where rows=each cell and cols are the intensity values for each marker
cutoffs: tibble of gates/cutoffs for all markers to gate
Expects cutoffs to match format of output from getDensityGates() with column corresponding to a marker, and rows to the subsets defined in the subset_col
subset_col: string for the column name to indicate the subsets to apply density gating on will perform operation on subsets corresponding to each unique value in column

Value

intens_dat with additional columns attached for each marker in cutoffs

Details

The naming convention for the tagged on indicator columns will be tolower(<marker_name>_pos) where 0 indicates negativity or intensity < gate provided 1 indicates positivity or intensity > gate provided

Examples

# Create a fake dataset
set.seed(100)
intens_dat <- tibble::tibble(
               CD3_pos=rep(c(0, 1), each=50),
               CD4=rnorm(100, 100, 10),
               CD8=rnorm(100, 100, 10)
)

# Run getDensityGates to obtain the gates
gates <- getDensityGates(intens_dat, marker="CD4", subset_col="CD3_pos", bin_n=40)

# Tag on the 0/1 on intens_dat
intens_dat_2 <- getGatedDat(intens_dat, cutoffs=gates, subset_col="CD3_pos")

# intens_dat_2 now has the cd4_pos tagged on
head(intens_dat_2)
#> # A tibble: 6 × 4
#>   CD3_pos   CD4   CD8 cd4_pos
#>     <dbl> <dbl> <dbl>   <dbl>
#> 1       0  95.0  96.7       1
#> 2       0 101.  114.        1
#> 3       0  99.2  95.3       1
#> 4       0 109.  108.        1
#> 5       0 101.   85.4       1
#> 6       0 103.   96.0       1