hxsylzpf / dp_penalized_logistic_regression

Differentially private penalized logistic regression.

Differentially private penalized logistic regression

This repository is an application of the differentially private penalized logistic regression method proposed in the following paper:

"Differentially-private logistic regression for detecting multiple-SNP association in GWAS databases." Yu, F., M. Rybar, C. Uhler, S. Fienberg. (2014) Proceedings of the 2014 International Conference on Privacy in Statistical Databases.

The paper is available at here.

Example data generation

The example case/control genotype data (./data/anticase_genotypes_Nov09_interaction1_MAF025_1 and ./data/case_genotypes_Nov09_interaction1_MAF025_1) were generated by HAP-SAMPLE with the following options:

• Population: CEU
• Source for SNPs: Chrom9_Chrom13_snps.txt
• Disease Model File: AR_chrom9_chrom13_Nov09_interaction1_MAF025.txt
• Simulation Type: Case/Control
• Number of Cases: 1000
• Number of Controls: 1000
• Average breaks per cM: 1
• Output Format: SNPs v. Individuals

The disease model file describes a disease with 2 causative SNPs having addive effects. For more details about the disease model, see Malaspinas & Uhler (2010).

Usage

In R:

source("./simulation_for_paper.R")
source("./analyze_simulation_for_paper.R")

Make sure that MATLAB and CVX are installed.

File descriptions

• analyze_simulation_for_paper.R: analyze simulation results generated by simulation_for_paper.R and make plots
• simulation_for_paper.R: perform differentially private elastic-net penalized logistic regression multiple times and save the results to an RData file. Also perform non-private penalized logistic regression and save the results to an RData file.
• analyze_hapsample.R: (helper script) load HapSample data into the workspace.
• run_cvx.R: (helper script) a wrapper for running CVX for MATLAB in R.
• opt_elastic_net_for_R.m: (helper script) a MATLAB function that uses CVX for optimization.

R session info

R version 3.1.2 (2014-10-31)
Platform: x86_64-apple-darwin14.1.0 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] lattice_0.20-29 R.matlab_3.1.1  glmnet_1.9-8    Matrix_1.1-4   

loaded via a namespace (and not attached):
[1] digest_0.6.8      grid_3.1.2        gtable_0.1.2      plyr_1.8.1       
[5] proto_0.3-10      R.methodsS3_1.6.1 R.oo_1.18.0       R.utils_1.34.0   
[9] Rcpp_0.11.4