shinyGPA {GPA}R Documentation

Run ShinyGPA app

Description

Run ShinyGPA app.

Usage

shinyGPA( out=NULL )

Arguments

out

output of fitAll function.

Details

shinyGPA runs the ShinyGPA app. It takes the output of the fitAll function, which fits the GPA model for all possible pairs of GWAS datasets, as input.

Value

Provides visualization to investigate pleiotropic architecture using GWAS results.

Author(s)

Dongjun Chung, Emma Kortemeier

References

Kortemeier E, Ramos PS, Hunt KJ, Kim HJ, Hardiman G, and Chung D (2018), "ShinyGPA: An interactive and dynamic visualization toolkit for genetic studies," PLOS One, 13(1): e0190949.

See Also

fitAll.

Examples


# simulator function

simulator <- function( risk.ind, nsnp=20000, alpha=0.6 ) {
  
  m <- length(risk.ind)
  
  p.sig <- rbeta( m, alpha, 1 )
  pvec <- runif(nsnp)
  pvec[ risk.ind ] <- p.sig
  
  return(pvec)
}

# run simulation

set.seed(12345)
nsnp <- 1000
alpha <- 0.3
pmat <- matrix( NA, nsnp, 5 )

pmat[,1] <- simulator( c(1:200), nsnp=nsnp, alpha=alpha )
pmat[,2] <- simulator( c(51:250), nsnp=nsnp, alpha=alpha )
pmat[,3] <- simulator( c(401:600), nsnp=nsnp, alpha=alpha )
pmat[,4] <- simulator( c(451:750), nsnp=nsnp, alpha=alpha )
pmat[,5] <- simulator( c(801:1000), nsnp=nsnp, alpha=alpha )

# Fit GPA for all possible pairs of GWAS datasets

out <- fitAll( pmat, maxIter = 100 )

# Run the ShinyGPA app using the ouput from fitAll()

# shinyGPA(out)


[Package GPA version 1.5.0 Index]