In Merguerrero/GSAFisherComb: Package to perform a GSAfisher test for a gene-set analysis

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Install package

This package could be downloaded and istalled:

install.packages("GSAFisherComb_1.0.tar.gz")
library(GSAFisherComb)

Or, as it is in Git Hub:

library(devtools)
install_git("https://github.com/Merguerrero")

Load GSA data

To perform the test an object of class GSAfisher or GSAfisher.mult. In this package there is test data that you can load and try this functions. As we are working with pvalues, this functions accept as input a vector, a list of vectors or a matrix.

data("pvales.totest")
pvales.totest[1:20]
GSA_vector<-loadGSAfisher(pvales.totest)
GSA_vector

Load list of vectors:

data("pvales.mult")
GSA_list<-loadGSAfisher(pvales.mult)

Load matrix:

data("pvales.matrix")
GSA_matrix<-loadGSAfisher(pvales.matrix)

GSAfisher test

Once the data is loaded, with the function GSAfisher the test is done. The output of the test differ with the class of the data.

res.Gsa<-GSAfisher(GSA_vector)
res.Gsa

For lists:

res.Gsa.list<-GSAfisher(GSA_list)
res.Gsa.list

For matrix:

res.Gsa.matrix<-GSAfisher(GSA_matrix)
res.Gsa.matrix

Summary of the test

To see the result of the test in a ordered way the function summary prints some information:

summary(res.Gsa)

Plot of the result

To see if the result of the GSAfisher of the class GSAfisher.mult follows a chisquare distribution.

plot(res.Gsa.list)

Hist of the result

If we are interested in the distribution of the result, an histogram with the density can also be plotted.

hist(res.Gsa.matrix)

Merguerrero/GSAFisherComb documentation built on May 7, 2019, 3:12 p.m.