https://github.com/ctlab/mcmcranking

Tool To Solve The Active Module Problem
https://github.com/ctlab/mcmcranking

Last synced: 8 months ago
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Tool To Solve The Active Module Problem

• Host: GitHub
• URL: https://github.com/ctlab/mcmcranking
• Owner: ctlab
• License: other
• Created: 2017-11-16T13:00:16.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2020-12-21T20:53:06.000Z (over 5 years ago)
• Last Synced: 2024-05-19T00:08:56.041Z (about 2 years ago)
• Language: C++
• Size: 505 KB
• Stars: 5
• Watchers: 5
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE

Awesome Lists containing this project

README

          
---

output: github_document

---

```{r, echo = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "README-"

)

```

# mcmcRanking

[![Travis-CI Build Status](https://travis-ci.org/ctlab/mcmcRanking.svg?branch=master)](https://travis-ci.org/ctlab/mcmcRanking)

[![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/ctlab/mcmcRanking?branch=master&svg=true)](https://ci.appveyor.com/project/ctlab/mcmcRanking)

[![Coverage status](https://codecov.io/gh/ctlab/mcmcRanking/branch/master/graph/badge.svg)](https://codecov.io/github/ctlab/mcmcRanking?branch=master)

## Overview

Tool for estimate probabilities of vertices being in active module using its likelihoods and it proposes methods for ranking vertices in order of importance. Estimating probabilities  based on Markov chain Monte Carlo (MCMC) methods.

## Installation

You can install mcmcRanking from github with:

```{r gh-installation, eval = FALSE}

# install.packages("devtools")

devtools::install_github("ctlab/mcmcRanking")

```

## Illustration

An animation of the MCMC algorithm performing. Vertices are colored depending on its likelihood, burgundy and gray colors corresponds to high and low likelihoods respectively. Yellow subgraph is an active module.