| Literature DB >> 22302573 |
Michael C Turchin1, Joel N Hirschhorn.
Abstract
Meta-analysis across genome-wide association studies is a common approach for discovering genetic associations. However, in some meta-analysis efforts, individual-level data cannot be broadly shared by study investigators due to privacy and Institutional Review Board concerns. In such cases, researchers cannot confirm that each study represents a unique group of people, leading to potentially inflated test statistics and false positives. To resolve this problem, we created a software tool, Gencrypt, which utilizes a security protocol known as one-way cryptographic hashes to allow overlapping participants to be identified without sharing individual-level data.Entities:
Mesh:
Year: 2012 PMID: 22302573 PMCID: PMC3307118 DOI: 10.1093/bioinformatics/bts045
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937