GSAfisher.plot: GSAfisher.plot

In carlosgarciaprieto/GSAfishercombined: Gene Set Analysis with Fisher Combined Method

Description

Plot method of GSAfisher function that plots the p-values for a joint test of association between a phenotype and multiple gene-sets of genetic variants (SNPs) by combining multiple marginal p-values data vectors using the Fisher method.

Usage

## S3 method for class 'plot'
GSAfisher(...)

Arguments

...	Set of multiple marginal p-values data vectors or matrix.

Value

plot.p.multiple

Plot of a set of multiple Fisher method combined p-values for each data vector.

Author(s)

Carlos Garcia Prieto

Examples

#Generate 3 vectors with 1000 random values from an Uniform distribution U(0, 0.25). 
data.vector1<-runif(1000, 0, 0.25)
data.vector2<-runif(1000, 0, 0.25)
data.vector3<-runif(1000, 0, 0.25)
#Set data class to "plot".
class(data.vector1)<-"plot"
#Apply the GSAfisher.plot function to these data vectors.
GSAfisher(data.vector1, data.vector2, data.vector3)

#You can also try:
#Generate 5000 vectors with 1000 random values from an Uniform distribution U(0,0.25).
data.vectors<-sapply(1:5000, function (x) runif(1000, 0, 0.25))
#Set data class to "plot".
class(data.vectors)<-"plot"
#Apply the GSAfisher.plot function to these data vectors.
GSAfisher(data.vectors)

carlosgarciaprieto/GSAfishercombined documentation built on May 14, 2019, 5:13 a.m.