Optimization of a multi-stage proteomic study

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Documentation for package ‘proteomicdesign’ version 2.0

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proteomicdesign-package Optimization of a multi stage proteomic study
calculate.cost Function to calculate the total cost of the multi-stage design
calculate.n3 A function to calculate the stage III sample size based on the current design parameters
do.one.experiment Simulation function for calculate the expected number of detectable proteins from the three stage proteomic study using group information
do.one.experiment.t Simulation function for calculating the expected number of detectable proteins from the three stage proteomic study
Ftest.Ttest A function to perform the paired t test for each protein, and the Hotelling T test for the group that the protein is assigned.
genseq.appr A sub function to generate the sub solution space
genseq.group A sub function to generate the sub solution space
genseq.single A sub function to generate the sub solution space
optim.two.stage.appr Optimize numbers of discoveries by using an approximated analytical objective function in a multi-stage clinical proteomic study that utilizes biological group information
optim.two.stage.group Optimization of the design parameters in the discovery , verification and validation stage from a multi-stage clinical proteomic study using biological grouping information
optim.two.stage.single Optimization of the number of discoveries from a multistage clinical proteomic study
ots.env assign the current working environment
power The power function used in the optim.two.stage.single function
power.appr The power function used in the optim.two.stage.appr function
power.group.cost Derive the averaged estimated costs of stage II and III and the stage III sample size from the 1000 Monte Carlo simulated functions of a three-stage proteomis study, given a solution of the design parameters
power.single.cost Derive the averaged estimated costs of stage II and III and the stage III sample size from the 1000 Monte Carlo simulated functions of a three-stage proteomic study, given a solution of the design parameters
power.t The power function used in the optim.two.stage.single function
proteomicdesign Optimization of a multi stage proteomic study
Ttest The function to calculate the p values for each protein in the optim.two.stage.single function