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Comprehensive comparison of large-scale tissue expression datasets.

Alberto Santos1, Kalliopi Tsafou1, Christian Stolte2

  • 1Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

Peerj
|July 10, 2015
PubMed
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This study integrates protein expression data across tissues, finding high agreement between methods. Combining datasets improves data quality and coverage, creating the TISSUES resource for easier access.

Area of Science:

  • Proteomics
  • Bioinformatics
  • Genomics

Background:

  • Accurate protein expression data is crucial for understanding tissue function.
  • Existing high-throughput technologies for mapping protein expression in tissues lack systematic comparison and integration.
  • Distinguishing between tissue-specific and ubiquitous protein expression is often assumed but not empirically demonstrated.

Purpose of the Study:

  • To comprehensively evaluate and integrate diverse experimental and computational datasets of tissue protein expression.
  • To assess the agreement between different data sources, including high-throughput methods, literature curation, and text mining.
  • To develop a unified resource for accessing and visualizing integrated tissue expression data.

Main Methods:

  • Systematic comparison and integration of protein expression data from various high-throughput technologies.
Keywords:
DatabasesImmunohistochemistryMass spectrometryMicroarraysRNA sequencingTissue expressionTissue-specificity

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  • Evaluation of agreement with literature curation and text mining findings.
  • Development of comparable confidence scores for different evidence types.
  • Creation of the TISSUES web resource for data visualization and access.

    • Main Results:

    • High agreement was observed between different experimental techniques for mapping tissue protein expression.
    • Datasets largely support the distinction between tissue-specific and ubiquitous protein expression.
    • Combining datasets, using developed confidence scores, significantly improved data quality and coverage.
    • The TISSUES resource provides a user-friendly interface for integrated data exploration.

    Conclusions:

    • Integration of diverse protein expression datasets enhances data quality and coverage.
    • The TISSUES resource offers a valuable tool for researchers studying tissue-specific protein expression.
    • This work validates existing protein expression data and provides a foundation for future research.