Cited by 182Bioinformatics and Genomic NetworksAdvanced Proteomics Techniques and ApplicationsComplex Network Analysis Techniques

Where Have All the Interactions Gone? Estimating the Coverage of Two-Hybrid Protein Interaction Maps

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Huang, Hailiang, Jedynak, Bruno M, Bader, Joel S·2007·PLoS Computational Biology

Abstract

Yeast two-hybrid screens are an important method for mapping pairwise physical interactions between proteins. The fraction of interactions detected in independent screens can be very small, and an outstanding challenge is to determine the reason for the low overlap. Low overlap can arise from either a high false-discovery rate (interaction sets have low overlap because each set is contaminated by a large number of stochastic false-positive interactions) or a high false-negative rate (interaction sets have low overlap because each misses many true interactions). We extend capture-recapture theory to provide the first unified model for false-positive and false-negative rates for two-hybrid screens. Analysis of yeast, worm, and fly data indicates that 25% to 45% of the reported interactions are likely false positives. Membrane proteins have higher false-discovery rates on average, and signal transduction proteins have lower rates. The overall false-negative rate ranges from 75% for worm to 90% for fly, which arises from a roughly 50% false-negative rate due to statistical undersampling and a 55% to 85% false-negative rate due to proteins that appear to be systematically lost from the assays. Finally, statistical model selection conclusively rejects the Erdös-Rényi network model in favor of the power law model for yeast and the truncated power law for worm and fly degree distributions. Much as genome sequencing coverage estimates were essential for planning the human genome sequencing project, the coverage estimates developed here will be valuable for guiding future proteomic screens. All software and datasets are available in and , -, and -, and are also available from our Web site, http://www.baderzone.org.

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  • The ratio of confidently predicted PPIs is even lower for protein pairs identified by Y2H (18%) or APMS (14%) screens, consistent with the known larger fraction of false positives in large-scale experimental screens.

    “The ratio of confidently predicted PPIs is even lower for protein pairs identified by Y2H (18%) or APMS (14%) screens (table S1), consistent with the known larger fraction of false positives in large-scale experimental screens (8,22).”

    From Computed structures of core eukaryotic protein complexes (2021) · cites this paper as [22]

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References 63 · Cited by 182

Authors
Huang, H., Jedynak, B. M., & Bader, J. S.
Affiliations
Johns Hopkins University (US)
Corresponding author
Bader, Joel S
Venue
PLoS Computational Biology
Published
2007-11-23
Volume
3
Issue
11
Pages
e214
ISSN
  • 1553-734X (ISSN-L)
  • 1553-7358
OpenAlex
W2022196194
Cited by
182
References
63
Citations by year
2025: 2 · 2024: 6 · 2023: 7 · 2022: 4 · 2021: 16 · 2020: 7 · 2019: 9 · 2018: 5 · 2017: 14 · 2016: 7 · 2015: 7 · 2014: 2 · 2013: 15 · 2012: 18
FWCI
5.82
Type
journal article
Language
en
Open access
Locations
  • PLoS Computational Biology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
Funders
  • National Science Foundation (0546446, CAREER)
  • Johns Hopkins University
  • Deutscher Akademischer Austauschdienst
  • National Institutes of Health
  • National Institute of General Medical Sciences (R41GM073492, R01GM067761)
  • National Center for Research Resources (U54RR020839)
  • Army Research Office
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
Keywords
yeast two-hybrid screen, false discovery rate, false negative rate, capture-recapture models, protein-protein interaction network, power-law degree distribution, membrane proteins, signal transduction proteins, Caenorhabditis elegans, Drosophila
MeSH terms
Computer Simulation, Models, Biological, Sensitivity and Specificity, Reproducibility of Results, Two-Hybrid System Techniques, Protein Interaction Mapping

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