Identify type of data
Arguments
- dt
data.table of raw drug response data containing both treated and untreated values
- codilution_conc
integer of maximum number of concentration ratio of co-treatment to classify as codilution data type; defaults to
2- matrix_conc
integer of minimum number of concentration pairs of co-treatment to classify as co-treatment or matrix data type; defaults to
1
Value
data.table of raw drug response data with additional column type
with the info of data type for a given row of data.table
Author
Bartosz Czech bartosz.czech@contractors.roche.com
Examples
conc <- rep(seq(0, 0.3, 0.1), 2)
ctrl_dt <- S4Vectors::DataFrame(
ReadoutValue = c(2, 2, 1, 1, 2, 1),
Concentration = rep(0, 6),
masked = FALSE,
DrugName = rep(c("DRUG_10", "vehicle", "DRUG_8"), 2),
CellLineName = "CELL1"
)
trt_dt <- S4Vectors::DataFrame(
ReadoutValue = rep(seq(1, 4, 1), 2),
Concentration = conc,
masked = rep(FALSE, 8),
DrugName = c("DRUG_10", "DRUG_8"),
CellLineName = "CELL1"
)
input_dt <- data.table::as.data.table(rbind(ctrl_dt, trt_dt))
input_dt$Duration <- 72
input_dt$CorrectedReadout2 <- input_dt$ReadoutValue
identify_data_type(input_dt)
#> ReadoutValue Concentration masked DrugName CellLineName Duration
#> <num> <num> <lgcl> <char> <char> <num>
#> 1: 2 0.0 FALSE DRUG_10 CELL1 72
#> 2: 2 0.0 FALSE vehicle CELL1 72
#> 3: 1 0.0 FALSE DRUG_8 CELL1 72
#> 4: 1 0.0 FALSE DRUG_10 CELL1 72
#> 5: 2 0.0 FALSE vehicle CELL1 72
#> 6: 1 0.0 FALSE DRUG_8 CELL1 72
#> 7: 1 0.0 FALSE DRUG_10 CELL1 72
#> 8: 2 0.1 FALSE DRUG_8 CELL1 72
#> 9: 3 0.2 FALSE DRUG_10 CELL1 72
#> 10: 4 0.3 FALSE DRUG_8 CELL1 72
#> 11: 1 0.0 FALSE DRUG_10 CELL1 72
#> 12: 2 0.1 FALSE DRUG_8 CELL1 72
#> 13: 3 0.2 FALSE DRUG_10 CELL1 72
#> 14: 4 0.3 FALSE DRUG_8 CELL1 72
#> CorrectedReadout2 record_id type
#> <num> <int> <char>
#> 1: 2 1 control
#> 2: 2 2 control
#> 3: 1 3 control
#> 4: 1 4 control
#> 5: 2 5 control
#> 6: 1 6 control
#> 7: 1 7 control
#> 8: 2 8 single-agent
#> 9: 3 9 single-agent
#> 10: 4 10 single-agent
#> 11: 1 11 control
#> 12: 2 12 single-agent
#> 13: 3 13 single-agent
#> 14: 4 14 single-agent