privacy-preserving mapping

Project Details

Project Lead
Yongan Zhao 
Project Manager
Yongan Zhao 
Project Members
Lei Wang, Diyue Bu, Sujun Li, Saliya Ekanayake  
Institution
Indiana University, School of Informatics and Computing  
Discipline
Biosciences, n.e.c. (617) 
Subdiscipline
26.99 Biological Sciences/Life Sciences, Other 

Abstract

This project is to design and implement a novel method to map human genomic data to reference genome in a privacy-preserving manner, due the data contains sensitive information, such as phenotype and disease potential, of data donor.

Intellectual Merit

There is no cloud-based read mapping tool on human genomic data. With the reduction of sequencing cost and precision medicine initiative, this kind of tool is urgent to utilize both huge amount of human genomic data and powerful clouds.

Broader Impacts

This is the first step to utilize the power of cloud computing in human genomic data processing. And then we want to explore more opportunities in privacy-preserving cloud computing on human genomic data.

Scale of Use

Our data is about 1T bytes. It'd be better if memory is large enough to reduce the overhead of loading data frequently.