Perform a grid search over potential design space, and find the predicted power and validity of the designs.
1  FindOptPower(cost, sample.size, MAF, OR, error, costPerExp = 18915, costPerPool = 970, costPerX = 300, lower.P = 20, upper.P = 400, lower.N.p = 2, upper.N.p = 200, lower.Xmean = 4, upper.Xmean = 1280, sig.level = 0.05, Number.Grids = 100)

cost 
cost constraint of the study 
sample.size 
sample size constraint of the study 
MAF 
assumed MAF of the variant of interest 
OR 
assume effect size (odds ratio) of the variant of interest 
error 
assume sequencing error rate 
costPerExp 
cost per experiment 
costPerPool 
cost per pool 
costPerX 
cost per 1X coverage 
lower.P 
lower bound of number of pools in potential consideration 
upper.P 
upper bound of number of pools in potential consideration 
lower.N.p 
lower bound of number of pool size in potential consideration 
upper.N.p 
upper bound of number of pool size in potential consideration 
lower.Xmean 
lower bound of number of coverage per pool in potential consideration 
upper.Xmean 
upper bound of number of coverage per pool in potential consideration 
sig.level 
significance level of the statistic test, usually 0.05 for a single test 
Number.Grids 
number of grids in the search space, preset as 100 
Given the research question and the study constraints, this function calculates the power and validity of all the potential pooled designs.
Returns a list:
cost 

sample.size 

constraint.set 

scenario.set 

designs 
the potential designs, validity and power 
Wei E. Liang
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######## Example 1: A simple example, with very rough grid points (only 20X20 grid points)
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##### Find the optimal design
example.1 < FindOptPower(cost=452915, sample.size=5000, MAF=0.03, OR=2, error=0.01, upper.P=200, Number.Grids=20)
##### assign a directory to store the contour plots
##### with your own choice
proj.Dir < paste(getwd(), "/hiPOD_examples", sep="")
if(!file.exists(proj.Dir)) dir.create(proj.Dir)
##### Inferences on the optimal designs
PlotOptPower(example.1, save.contour=FALSE, plot.3d=FALSE)
# # snapshot3d(filename = paste(proj.Dir, "/example1_3d.bmp", sep=""))
ShowOptDesign(example.1, 5)

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