AWFisher_pvalue {AWFisher} | R Documentation

## AWFisher

### Description

R package for fast computing for adaptively weighted fisher's method

### Usage

    AWFisher_pvalue(p.values)

### Arguments

`p.values` | Input G by K p-value matrix. Each row represent a gene and each column represent a study. Note that K has to be >=2 and <=100.

### Details

fast computing for adaptively weighted fisher's method

### Value

A list consisting of AWFisher pvalues and AWweight.

`pvalues` | AWFisher pvalues.
`weights` | G by K binary weight matrix W. $W_gk = 1$ represents for gene $g$, study $k$ contributes to the meta-analysis result. $W_gk = 0$ otherwise.

### Author(s)

Zhiguang Huo

### Examples

    K <- 40
    G <- 10000
    p.values = matrix(rbeta(K*G, 1,1), ncol=K)
    res = AWFisher_pvalue(p.values)
    hist(res$pvalues, breaks=40)
    table(rowSums(res$weights))
    pvalues=res$pvalues[order(res$pvalues)]
    plot(-log10((1:NROW(pvalues))/(1+NROW(pvalues))),
     -log10(pvalues),xlab='theoretical quantile', ylab='observed quantile')
    lines(c(0,100), c(0,100), col=2)

[Package AWFisher version 1.6.0 Index]