github-gs / QPA

Quantitative pathway analysis

QPA

Depends

R Vsersion >= 3.4.2

R Package: omicade4, clusterProfiler, KEGGREST, limma, ade4, parallel

R Depends Package Installation

if (!requireNamespace("BiocManager", quietly = TRUE))

install.packages("BiocManager")

BiocManager::install(c('omicade4', 'clusterProfiler', 'KEGGREST', 'limma', 'ade4'))

install.package('parallel')

Installation

install.packages("devtools")    # if you have not installed "devtools" package
library(devtools)
devtools::install_github("github-gs/QPA", force = TRUE)

or you can down load the source code .zip file (https://github.com/github-gs/QPA/blob/source-code-zip/QPA_1.0.tar.gz), then use the IDE software (Rstudio) --> Tools --> Install Packages --> choose source code zip file to install.

Usage

 help(QPA)
 help(merge_pathway)
 help(pathway_vectorization)
 help(pathway_comparison)

Example

 data(example)  ######## pathway-gene matrix


 pathway_info = merge_pathway(pathway_list)

 group1 = 'Treatment'

 group2 = 'Model'

 group3 = 'Control'


 Treatment_profile = pathway_vectorize(expression_tab,condition,group1,group2,pathway_info)

 Model_profile = pathway_vectorize(nmerge_tab,condition,group2,group3,pathway_info)

 significant_pathway = pathway_comparision(Treatment_profile,Model_profile,pathway_info)
 
 
 data(Case)  ### load the original data in our research