Evidence map›Paper›PMID 29934598›Full record

ArticleNature communications2018

Analysis of sensitive information leakage in functional genomics signal profiles through genomic deletions.

Arif Harmanci, Mark Gerstein

Abstract read
In one paragraph

Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. AI applications in functional genomics.Computational and structural biotechnology journal · 2021
    Review
  14. Article
  15. Review
  16. Big Data Approaches in Heart Failure Research.Current heart failure reports · 2020
    Review
  17. Article
  18. Navigating ethical quandaries with the privacy dilemma of biomedical datasets.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2020
    Article
  19. Article
  20. When Biology Gets Personal: Hidden Challenges of Privacy and Ethics in Biological Big Data.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2019
    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

2 authors.

Arif HarmanciProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA. arif.o.harmanci@uth.tmc.edu.ORCID http://orcid.org/0000-0002-9696-1118
Mark GersteinProgram in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA. mark@gersteinlab.org.ORCID http://orcid.org/0000-0002-9746-3719

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functional genomics experiments, such as RNA-seq, provide non-individual specific information about gene expression under different conditions such as disease and normal. There is great desire to share these data. However, privacy concerns often preclude sharing of the raw reads. To enable safe sharing, aggregated summaries such as read-depth signal profiles and levels of gene expression are used. Projects such as GTEx and ENCODE share these because they ostensibly do not leak much identifying information. Here, we attempt to quantify the validity of this statement, measuring the leakage of genomic deletions from signal profiles. We present information theoretic measures for the degree to which one can genotype these deletions. We then develop practical genotyping approaches and demonstrate how to use these to identify an individual within a large cohort in the context of linking attacks. Finally, we present an anonymization method removing much of the leakage from signal profiles.

Indexed as

Data AnonymizationGenetic PrivacyGenomicsSequence DeletionBase SequenceGenotyping TechniquesHumansSequence Analysis, RNA

Identifiers

PMID29934598
PMCPMC6015012

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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.