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 1.4.0 Index]