Sunday, October 20, 2019

Fwd: genopri abstract

9:30 – 10:15am Presentation Session 3: "Models" (Session Chair: Xiaoqian Jiang)

Enhancing open data sharing for functional genomics experiments:
Measures to quantify genomic information leakage & identify file
formats for privacy preservation

Mark Gerstein, Yale University (USA)

Abstract: Functional genomics experiments on human subjects present a
privacy conundrum. On one hand, many of the conclusions we infer from
these experiments are not tied to the identity of individuals but
represent universal statements about biology and disease. On the other
hand, the raw sequencing reads or the phenotypic information inferred
from these experiments can leak information about patients' variants,
which presents privacy challenges in terms of data sharing. There is a
great desire to share data as broadly as possible. Therefore,
measuring the amount of variant information leaked in a variety of
experiments is a key first step in protecting private information. In
this study, we propose metrics to quantify private information leakage
in functional genomics data, linking attacks to validate the proposed
metrics and file formats that maximize the potential for data sharing
while protecting individuals' private information.