Evidence map›Paper›PMID 37128365›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2022

Facilitating Federated Genomic Data Analysis by Identifying Record Correlations while Ensuring Privacy.

Leonard Dervishi, Xinyue Wang, Wentao Li, Anisa Halimi, Jaideep Vaidya, Xiaoqian Jiang, Erman Ayday

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Descriptor:IEEE data descriptions · 2024
    Article
  8. Ensuring Trust in Genomics Research.... IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications : (TPS-ISA ...). IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications · 2023
    Article
  9. Article
  10. Efficient Federated Kinship Relationship Identification.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    Article
  11. Article
  12. Secure Discovery of Genetic Relatives across Large-Scale and Distributed Genomic Datasets.Research in computational molecular biology : ... Annual International Conference, RECOMB ... : proceedings. RECOMB (Conference : 2005- )
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Leonard DervishiCase Western Reserve University, Cleveland, OH.
Xinyue WangRutgers University, Newark, NJ.
Wentao LiUTHealth, Houston, TX.
Anisa HalimiIBM Research Europe, Dublin, Ireland.
Jaideep VaidyaRutgers University, Newark, NJ.
Xiaoqian JiangUTHealth, Houston, TX.
Erman AydayCase Western Reserve University, Cleveland, OH.

Funding

Supplement for high performance compute clustersR35GM134927 · NIGMS · RUTGERS THE STATE UNIV OF NJ NEWARK · PI VAIDYA, JAIDEEP · 2020 to 2024
$2.1M
Privacy Challenges of Genomic Data-Sharing Beacons and SolutionsR01LM013429 · NLM · CASE WESTERN RESERVE UNIVERSITY · PI AYDAY, ERMAN · 2020 to 2023
$1.2M
NIGMS NIH HHS R35 GM134927NLM NIH HHS R01 LM013429
6 · The paper itself

Abstract

With the reduction of sequencing costs and the pervasiveness of computing devices, genomic data collection is continually growing. However, data collection is highly fragmented and the data is still siloed across different repositories. Analyzing all of this data would be transformative for genomics research. However, the data is sensitive, and therefore cannot be easily centralized. Furthermore, there may be correlations in the data, which if not detected, can impact the analysis. In this paper, we take the first step towards identifying correlated records across multiple data repositories in a privacy-preserving manner. The proposed framework, based on random shuffling, synthetic record generation, and local differential privacy, allows a trade-off of accuracy and computational efficiency. An extensive evaluation on real genomic data from the OpenSNP dataset shows that the proposed solution is efficient and effective.

Indexed as

Computer SecurityPrivacyData CollectionGenomicsHumans

Identifiers

PMID37128365
PMCPMC10148342

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.