DriverRWH-package: DriverRWH

In ShandongUniversityZhanglab/DriverRWH: DriverRWH: Discovering Cancer Driver Genes by Random Walk on a Gene Mutation Hypergraph

DriverRWH

Description

DriverRWH prioritizes altered genes by effective integration of somatic mutation data and molecular interaction data. A weighted Hypergraph model is formed by combining the degree of the PPI sub-network composed of each patient's mutated genes. Mutated genes are ranked by the random walk on the weighted Hypergraph model.

Details

Package:	DriverRWH
Type:	Package
Version:	1.0
Date:	2020-10-08
License:	MIT
Authors:	Naiqian Zhang, Chengye Wang, Junhan Shi
Maintainer:	Junhan Shi

Examples

### the example mutation data is a Lung Squamous Cell Carcinoma Dataset from TCGA
### the example network data is HumanNet
### We will show how to get example DriverRWH Results
### to use your own mutation data or network data, please refer to get_DriverRWH_score
library(DriverRWH)

# load the mutation data
data(luscExampleMutation)

# load the network data
data(HumanNet)

# set the current working directory as the output file directory
my_file_dir=getwd()

# get the result of DriverRWH
# the output file would be in the out_data folder in the output file directory
# the default value of theta is 0.2
get_DriverRWH_score(Mutation=luscExampleMutation,string=HumanNet,out_file_dir=my_file_dir)

ShandongUniversityZhanglab/DriverRWH documentation built on May 10, 2022, 2:47 a.m.