PREMIX: PRivacy-preserving EstiMation of Individual admiXture
Feng Chen1, Michelle Dow1, Sijie Ding2
1Department of Biomedical Informatics, UC San Diego, La Jolla, CA.
Abstract:
In this paper we proposed a framework: PRivacy-preserving EstiMation of Individual admiXture (PREMIX) using Intel software guard extensions (SGX). SGX is a suite of software and hardware architectures to enable efficient and secure computation over confidential data. PREMIX enables multiple sites to securely collaborate on estimating individual admixture within a secure enclave inside Intel SGX. We implemented a feature selection module to identify most discriminative Single Nucleotide Polymorphism (SNP) based on informativeness and an Expectation Maximization (EM)-based Maximum Likelihood estimator to identify the individual admixture. Experimental results based on both simulation and 1000 genome data demonstrated the efficiency and accuracy of the proposed framework. PREMIX ensures a high level of security as all operations on sensitive genomic data are conducted within a secure enclave using SGX.
Related Concept Videos
Mechanistic Models: Compartment Models in Individual and Population Analysis
Analysis of Population Pharmacokinetic Data
Estimating Population Mean with Unknown Standard Deviation
William S. Gosset (1876–1937) of the...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Law of Independent Assortment
Estimating Population Mean with Known Standard Deviation
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...


