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.
| Original language | English |
|---|---|
| Article number | bts045 |
| Pages (from-to) | 886-888 |
| Number of pages | 3 |
| Journal | Bioinformatics |
| Volume | 28 |
| Issue number | 6 |
| DOIs | |
| State | Published - Mar 2012 |
| Externally published | Yes |
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