shinyGPA {GPA} | R Documentation |
Run ShinyGPA app.
shinyGPA( out=NULL )
out |
output of |
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.
Provides visualization to investigate pleiotropic architecture using GWAS results.
Dongjun Chung, Emma Kortemeier
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.
# 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)