jranaraki / IBDgenes

MATLAB implementation of perturbation based feature selection for finding associated genes to Inflammatory Bowel Disease

title	authors	date
IBDgenes	Javad Rahimipour Anaraki and Hamid Usefi	21/01/19

Notice

The code PFS.m selects the most relevant and independant genes associated to Inflammatory Bowel Disease (IBD). If you need more details and explanation about the algorithm, please contact Javad Rahimipour Anaraki or Hamid Usefi.

Use case

To determine the most important features using the algorithm described in "A Comparative Study of Feature Selection Methods on Genomic Datasets" by Javad Rahimipour Anaraki and Hamid Usefi

Here is a link to the paper: https://ieeexplore.ieee.org/document/8787392

Compile

This code can be run using MATLAB R2006a and above

Run

To run the code, open PFS.m and choose a dataset to apply the method to. The code strats reading the selected dataset using readLargeCSV.m written by Cedric Wannaz. Then it rank features and returns resulting classification accuracy by cAcc.m using SVM classifier. The IBD dataset is downloaded from GEO under accession number GSE3365.

Note

• Dataset should have no column and/or row names, and the class values should be all numeric