[VanBUG] Bioinformatics Event: Privacy-Preserving Sharing and Analysis of Human Genomic Data‏

The VanBUG team occasionally forwards events of interest to the local
bioinformatics community. The upcoming event is posted on the
Bioinformatics Event Calendar at: http://www.vanbug.org/calendar/

*** SFU Computational Biology Seminar special summer meeting ***

Haixu Tang
School of Informatics and Computing
Indiana University, Bloomington

Privacy-Preserving Sharing and Analysis of Human Genomic Data

Time and Date:
Tuesday, May 22nd at 1 p.m

IRMACS Theatre, 10900 ASB

Given rapid cost reduction, genome sequencing may soon become a routine
tool for clinical diagnosis and therapy selection. However, the
analytical demand is hard to meet because computational and personnel
resources for storing and analyzing sequencing data are expensive.
Furthermore, there are barriers related to complicated procedures for
researchers to get access to sensitive human genomic data, which are
designed to protect the privacy of human subjects. A critical issue is
the need for the techniques that offer practical protection: data are
expected to be conveniently used by biomedical researchers and
healthcare practitioners, but need to be protected to the highest
possible level, making it impractical to re-identify human subjects from
the data. These techniques are also expected to help outsource the
intensive computation involved in data analyses to low-cost
public/commercial computing systems, without endangering the privacy of
the parties that donate the data. In this talk, I will discuss our
recent works on developing these techniques. I will first present our
practical approaches to quantify the potential privacy risks in human
genome data, using genome-wide association data as an example, and the
techniques to mitigate these threats. In the second part of my talk, I
will the computational technique that allows a human genome center to
leverage the low-cost public resources for the analysis on human
sequencing data. Based on thorough privacy analysis, I will show that
this technique can outsource most human genome computing to the public
server, while completely preserve the privacy of the participants of the
genome studies.

This is joint work with Professor Xiaofeng Wang at Indiana University,
and several graduate students.

The SFU Computational Biology Seminar is supported by BCID (SFU-CTEF
supported Bioinformatics for Combating Infectious Diseases Project),
CORDS (the Centre for Operations Research and Decision Sciences) and

Seminar Webpage:

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