Project Name

The Iterative Exclusion of Compatible Samples workflow for multi-SNP analysis in complex diseases.

Table of Contents

• Project Name
  • Table of Contents
  • General Information
  • Features
  • Usage
  • Contact

General Information

• IECS workflow is for multi-SNP analysis in complex diseases.
• Existing epistasis detection algorithms can only detect the interaction between two SNPs, or have the problem of heavy computational workload.
• To simultaneously detect the relationship between SNPs (single SNP and multi-SNP combinations) and complex diseases,IECS workflow is proposed.

Features

• Strong recognition ability.
• Small amount of computation.

Usage

How does one go about using it? Provide various use cases and code examples here.

• Copy the "comparison" folder to the default working directory of R.
• Install MDR package.
• Install iecs package.
• To compare MDR, BOOST and IECS in the simulated data set with different noise, run "comparison-different noise-iteration 1000-MDR-BOOST-IECS" script.
• To compare MDR, BOOST and IECS in the simulated data set with different number of samples, run "comparison-different number of samples-iteration 1000-MDR-BOOST-IECS" script.
• To compare MDR, BOOST and IECS in the real data set, run "comparison-choosedata-IECS-MDR-BOOST" script. You can modify two parameters of necessaryconditions function: "consistencythreshold" and "coveragethreshold". You can also modify two parameters of iecs function: "iteration" and "consistencythreshold".
• The data is stored in the "data" directory.
• View the results in the "result" directory or in the R window.
• To generate simulated data with different pathogenic models, different noise and different number of samples, employ generatedata function.

Contact

Created by @gaojun and @xu wei- feel free to contact us!