Remove endpoints with specific data quality flags from data

Through the ToxCast program quality assurance procedures, information is examined and at times, it is necessary to assign a data quality flag to a specific chemical/assay result. A toxEval user may want to include or exclude assay results with certain flags depending on the objectives of a given study. Assay results with specific data quality flags assigned to them can be removed based on their designated flag with the remove_flags function. The flags included in ToxCast, and the associated flagsShort value (used in the remove_flags function) are as follows:

flag_id	Full Name
5*	Model directionality questionable
6*	Only highest conc above baseline, active
7	Only one conc above baseline, active
8	Multiple points above baseline, inactive
9	Bmd > ac50, indication of high baseline variability
10	Noisy data
11*	Borderline
15*	Gain AC50 < lowest conc & loss AC50 < mean conc
17	Less than 50% efficacy
18*	AC50 less than lowest concentration tested
13	Average number of replicates per conc is less than 2
14	Number of concentrations tested is less than 4
19	Cell viability assay fit with gnls winning model

Asterisks indicate flags removed in the function as default.

Usage

remove_flags(ACC, flag_id = c(5, 6, 11, 15, 18))

Arguments

ACC: data frame with columns: casn, chnm, endPoint, and ACC_value
flag_id: vector of flags to to trigger REMOVAL

Examples

CAS <- c("121-00-6", "136-85-6", "80-05-7", "84-65-1", "5436-43-1", "126-73-8")
ACC <- get_ACC(CAS)
nrow(ACC)
#> [1] 408

# See available flags and associated ids:

flags
#>    flag_id                                            flag_full
#> 1        5                    Model directionality questionable
#> 2        6             Only highest conc above baseline, active
#> 3        7                 Only one conc above baseline, active
#> 4        8             Multiple points above baseline, inactive
#> 5        9  Bmd > ac50, indication of high baseline variability
#> 6       10                                           Noisy data
#> 7       11                                           Borderline
#> 8       15      Gain AC50 < lowest conc & loss AC50 < mean conc
#> 9       17                               Less than 50% efficacy
#> 10      18           AC50 less than lowest concentration tested
#> 11      13 Average number of replicates per conc is less than 2
#> 12      14       Number of concentrations tested is less than 4
#> 13      19     Cell viability assay fit with gnls winning model

ACC <- remove_flags(ACC)
nrow(ACC)
#> [1] 319