ReviewNature reviews. Genetics2022
Functional genomics data: privacy risk assessment and technological mitigation.
Review in Nature reviews. Genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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.
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.
Who cites it
22 citing papers in PubMed.
- Next-Generation Sequencing in Melioidosis: Enhancing Diagnosis, Epidemiology and Antimicrobial Resistance Surveillance.Diagnostics (Basel, Switzerland) · 2026Review
- PRISM-G: an interpretable privacy scoring framework for assessing risk in synthetic human genome data.Bioinformatics (Oxford, England) · 2026Article
- NoisyFlow: differentially private optimal transport using neural networks for secure biomedical data sharing across multiple institutions.Bioinformatics (Oxford, England) · 2026Article
- Data visiting governance: a conceptual framework.Human genomics · 2025Review
- Perspectives on the Current and Future State of Artificial Intelligence in Medical Genetics.American journal of medical genetics. Part A · 2025Review
- Bottlenecks in advancing and applying multiomic data integration-common data resources as rate-limiting drivers-the high-impact use case of atherosclerotic cardiovascular disease.Briefings in bioinformatics · 2025Review
- Secure and federated genome-wide association studies for biobank-scale datasets.Nature genetics · 2025Article
- Secure and scalable gene expression quantification with pQuant.Nature communications · 2025Article
- Article
- Privacy-Enhancing Technologies in Biomedical Data Science.Annual review of biomedical data science · 2024Review
- FedGMMAT: Federated generalized linear mixed model association tests.PLoS computational biology · 2024Article
- Big data and deep learning for RNA biology.Experimental & molecular medicine · 2024Review
- Assessing Privacy Vulnerabilities in Genetic Data Sets: Scoping Review.JMIR bioinformatics and biotechnology · 2024Article
- PPML-Omics: A privacy-preserving federated machine learning method protects patients' privacy in omic data.Science advances · 2024Article
- Navigating ethical challenges in psychological research involving digital remote technologies and people who use alcohol or drugs.The American psychologist · 2024Article
- FAIR compliant database development for human microbiome data samples.Frontiers in cellular and infection microbiology · 2024Article
- sfkit: a web-based toolkit for secure and federated genomic analysis.Nucleic acids research · 2023Article
- Assessing transcriptomic reidentification risks using discriminative sequence models.Genome research · 2023Article
- Navigating bottlenecks and trade-offs in genomic data analysis.Nature reviews. Genetics · 2023Review
- Session Introduction: TOWARDS ETHICAL BIOMEDICAL INFORMATICS: LEARNING FROM OLELO NOEAU, HAWAIIAN PROVERBS.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The generation of functional genomics data by next-generation sequencing has increased greatly in the past decade. Broad sharing of these data is essential for research advancement but poses notable privacy challenges, some of which are analogous to those that occur when sharing genetic variant data. However, there are also unique privacy challenges that arise from cryptic information leakage during the processing and summarization of functional genomics data from raw reads to derived quantities, such as gene expression values. Here, we review these challenges and present potential solutions for mitigating privacy risks while allowing broad data dissemination and analysis.
Indexed as
Identifiers
34759381What Socratic holds
Registered trials
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 Socratic graph.