geneDrugSensitivityPBCorr: Calculate The Gene Drug Sensitivity

View source: R/geneDrugSensitivityPBCorr.R

geneDrugSensitivityPBCorrR Documentation

Calculate The Gene Drug Sensitivity

Description

This version of the function uses a partial correlation instead of standardized linear models, for discrete predictive features Requires at least 3 observations per group.

Usage

geneDrugSensitivityPBCorr(
  x,
  type,
  batch,
  drugpheno,
  test = c("resampling", "analytic"),
  req_alpha = 0.05,
  nBoot = 1000,
  conf.level = 0.95,
  max_perm = getOption("PharmacoGx_Max_Perm", ceiling(1/req_alpha * 100)),
  verbose = FALSE
)

Arguments

x

A numeric vector of gene expression values

type

A vector of factors specifying the cell lines or type types

batch

A vector of factors specifying the batch

drugpheno

A numeric vector of drug sensitivity values (e.g., IC50 or AUC)

test

A character string indicating whether resampling or analytic based tests should be used

req_alpha

numeric, number of permutations for p value calculation

nBoot

numeric, number of bootstrap resamplings for confidence interval estimation

conf.level

numeric, between 0 and 1. Size of the confidence interval required

max_perm

numeric the maximum number of permutations that QUICKSTOP can do before giving up and returning NA. Can be set globally by setting the option "PharmacoGx_Max_Perm", or left at the default of ceiling(1/req_alpha*100).

verbose

boolean Should the function display messages?

Value

A vector reporting the effect size (estimateof the coefficient of drug concentration), standard error (se), sample size (n), t statistic, and F statistics and its corresponding p-value.

Examples

print("TODO::")


bhklab/PharmacoGx documentation built on April 18, 2024, 3:13 a.m.