Privacy of single-cell gene expression data

The possibility that single-cell gene expression datasets could leak information about individuals' genotypes has been largely unexplored. Walker et al. showed that even noisy genotype predictions derived from these data can be linked to the corresponding genotype profiles with significant accuracy.

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Publication Details

Journal
Patterns
Published
2024-11-01
DOI
https://doi.org/10.1016/j.patter.2024.101096
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

Privacy of single-cell gene expression data

Hyunghoon Cho
Patterns
Single-cell and spatial transcriptomics
article

Privacy of single-cell gene expression data

Hyunghoon Cho
article en

Abstract

The possibility that single-cell gene expression datasets could leak information about individuals' genotypes has been largely unexplored. Walker et al. showed that even noisy genotype predictions derived from these data can be linked to the corresponding genotype profiles with significant accuracy.

PatternsVol. 5(11)
Yale University (US)
NIH Office of the Director
Openalex Percentile: Top 82%
Single-cell and spatial transcriptomics
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Privacy of single-cell gene expression data — Hyunghoon Cho · Patterns (2024) | TGRS Research Map | TGRS