CalculateSens: Calculate relative inhibition (RI) for dose-response curve

In DrugComb/TidyComb: Preparing drug combination data for DrugComb

Calculate relative inhibition (RI) for dose-response curve

Description

Function CalculateSens calculates cell line sensitivity to a drug or a combination of drugs from dose response curve.

Usage

CalculateSens(df, pred = FALSE)

Arguments

df	A data frame. It contains two variables: dose the concentrations of drugs. response the response of cell lines at crresponding doses. We use inhibition rate of cell line growth to measure the response.
pred	A logical value. If it is TRUE, the function will return one more table in the result. It contains the predicted response value at input doses (according to fitted dose-response model) and corresponding standard deviation. This table could be used in TRUE. Note: The input data frame must be sorted by "dose" with ascending order.

Details

This function measures the sensitivity by calculating the Area Under Curve (AUC) according to the dose response curve. The lower bouder is chosen as lowest non-zero concentration in the dose response data.

Value

If pred is FALSE, only the RI value will be return. If pred is set to be TRUE, one more data frame which contains predicted resposne values and corresponding standard deviations will be return. It could be used to RIConfidenceInterval for confidence interval calculation.

Author(s)

Jing Tang [e-mail] Shuyu Zheng [e-mail]

Examples

# LL.4
df <- data.frame(dose = c(0, 0.1954, 0.7812, 3.125, 12.5, 50),
                 response = c(2.95, 3.76, 18.13, 28.69, 46.66, 58.82))
RI <- CalculateSens(df)

RI_with_pred <- CalculateSens(df, pred = TRUE)

DrugComb/TidyComb documentation built on June 22, 2022, 2:49 a.m.