DRLevel: Define the drug response level for each animal.

In SCBIT-YYLab/DRAP: Drug Response Analysis Tailored for Drug Testing on Patient-Derived Tumor Models

Description

Define the drug response level of each animal based on tumor volume change.

Usage

DRLevel(data, method = c('NPDXE.Response','PPTP.Response','RC.Response'), 
               criteria, neg.control, rm.neg.control=TRUE)

Arguments

data	a data frame of measured volume data.
method	the method used to quantify the drug response level. Currently available methods include NPDXE.Response (default),PPTP.Response,RC.Response.
criteria	the criteria conrresponding to method.
neg.control	the negative control arm.
rm.neg.control	whether remove the negative control arm.

Details

Defining drug response level is the general pipeline in clinical trial and precinical animal trial. DRLevel offers three published ways to define response level in function DRLevel. Notably, the criteria of each way for defining response level could be adjusted by users based on the actual experimental data.

Value

The response level of each animal.

References

Gao, H., et al. High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response. Nat Med 2015;21(11):1318-1325. Murphy, B., et al. Evaluation of Alternative In Vivo Drug Screening Methodology: A Single Mouse Analysis. Cancer Res 2016;76(19):5798-5809. Bertotti, A., et al. The genomic landscape of response to EGFR blockade in colorectal cancer. Nature 2015;526(7572):263-267.

See Also

NPDXEResponseLevel, PPTPResponseLevel, RCResponseLevel

Examples

### build the criteria

# NPDXE.criteria
npdxe.criteria <- data.frame(BestResponse.lower = c(-1000,-0.95,-0.5,0.35),
                             BestResponse.upper = c(-0.95,-0.5,0.35,1000),
                             BestAvgResponse.lower = c(-1000,-0.4,-0.2,0.3), 
                             BestAvgResponse.upper = c(-0.4,-0.2,0.3,1000), 
                             Level = c( 'CR','PR', 'SD','PD'))
npdxe.criteria
 
# PPTP.criteria 
pptp.criteria <- data.frame(min.RC.lower = c(-1,-1,-0.5,-0.5),
                            min.RC.upper = c(-0.5,-0.5,1000,1000),
                            min.Vol.lower = c(0,100,NA,NA),
                            min.Vol.upper = c(100,10000,NA,NA),
                            end.RC.lower =c(NA,NA,-1,0.25),
                            end.RC.upper = c(NA,NA,0.25,1000),
                            Level = c( 'CR','PR', 'SD','PD'))
pptp.criteria

# RC.criteria
rc.criteria <- data.frame(Response.lower = c(-1000,-0.35,0.35),
                          Response.upper = c(-0.35,0.35,1000),
                          Level = c( 'CR','SD','PD'))
rc.criteria

### drug response level
##
data(oneAN.volume.data)
oneAN.drl <- DRLevel(data = oneAN.volume.data, 
                     method = 'NPDXE.Response', 
                     criteria = npdxe.criteria, 
                     neg.control = 'Control')
oneAN.drl <- oneAN.drl[order(oneAN.drl$Arms),]
head(oneAN.drl)


##
data(TAN.volume.data)
TAN.drl <- DRLevel(data = TAN.volume.data, 
                   method = 'NPDXE.Response', 
                   criteria = npdxe.criteria, 
                   neg.control = 'Control')
head(TAN.drl)

##
data(TAone.volume.data)
head(TAone.volume.data)
TAone.drl <- DRLevel(data = TAone.volume.data, 
                     method = 'NPDXE.Response', 
                     criteria = npdxe.criteria, 
                     neg.control = 'Control')
head(TAone.drl)

SCBIT-YYLab/DRAP documentation built on April 7, 2020, 2:03 a.m.