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Related Experiment Video

Updated: May 10, 2026

A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies
09:32

A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies

Published on: September 23, 2014

TMA Navigator: Network inference, patient stratification and survival analysis with tissue microarray data.

Alexander L R Lubbock1, Elad Katz, David J Harrison

  • 1MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK.

Nucleic Acids Research
|June 14, 2013
PubMed
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TMA Navigator is a web tool for analyzing tissue microarray data, offering batch effect correction and survival analysis. It aids in understanding molecular pathways for personalized medicine.

Area of Science:

  • Biomedical informatics
  • Computational biology
  • Pathology

Background:

  • Tissue microarrays (TMAs) are crucial for analyzing biomarker protein expression in tumor biopsies.
  • Accurate analysis of TMA data is essential for advancing personalized medicine.

Purpose of the Study:

  • To introduce TMA Navigator, an open-access web application for comprehensive TMA data analysis.
  • To provide tools for mitigating batch effects and performing unsupervised sample grouping and survival analysis.

Main Methods:

  • Incorporation of the ComBat algorithm for automated batch effect correction in TMA data.
  • Gaussian mixture modeling with Bayesian information criterion for unsupervised sample clustering.
  • Kaplan-Meier survival analysis and network inference for TMA datasets.

Related Experiment Videos

Last Updated: May 10, 2026

A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies
09:32

A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies

Published on: September 23, 2014

Main Results:

  • TMA Navigator facilitates analysis of diverse TMA expression scores (categorical, semi-continuous, continuous).
  • The application enables unsupervised patient grouping and survival analysis, identifying significant survival differences.
  • Network inference tools provide insights into molecular logic for pathophenotypes.

Conclusions:

  • TMA Navigator is a valuable resource for researchers analyzing TMA data, supporting biomarker discovery and personalized medicine.
  • The integrated tools enhance data quality and enable deeper biological insights from TMA studies.