GSAfisher.plot {GSAfisherCombined} | R Documentation |
GSAfisher.plot
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)
[Package GSAfisherCombined version 1.0 Index]