An introduction to network analysis

This page gathers information and material for “An introduction to network analysis: inference and mining”, a tutorial given during the CIMI automn school, organized for the thematic semester on “Mathematics, Computer Science and Biology”. The tutorial is proposed by the Biostatistics platform, Genotoul.

The tutorial will be held on September 19th, 15h45-17h45, at Université Paul Sabatier, room U1 204.

• How to install R and required packages?
• Material for the tutorial

How to install R and required packages?

You will be asked to have your own R installation with a list of required packages already installed. We also advise that you install RStudio. The installation steps are described below. In case of difficulty, please, contact me (emails preferred).

   

Install R

I will use R 3.4.1 (2017-06-30) -- "Single Candle".
R can be downloaded for free on the official repository website. Choose the version depending of your OS (Windows, Linux or Mac). Mac users should also probably install tcltk which is available in the section called tools. Some linux users might also found R in their distribution repositories (this is the case for Ubuntu and Debian users; further details are provided at the beginning of this page).

   

Install RStudio

I will use RStudio version Version 1.0.143.
RStudio (Desktop version) can be downloaded for free at this link. Choose the version ("Installers" prefer) depending of your OS (Windows, Linux or Mac). Ubuntu users can install the .deb file with

sudo dpkg -i rstudio-1.0.143-amd64.deb
sudo apt-get install -f
      

install.packages(c("huge", "igraph", "mixOmics"))
      

Material for the tutorial

Please make sure you have downloaded all material before the tutorial. For text files (data), do not open them with MS Word or MS Excel but save them as they are on the website (right click and “save link as…” probably):

• slide (course material, PDF)
• data: the edge list of my facebook network and the nodes’ names (initials) that have to be renamed fbnet-el.txt and fbnet-name.txt, respectively;
• R scripts: for network mining and inference.