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

Alexander L. R. Lubbock, Elad Katz, David J. Harrison, Ian M. Overton*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Tissue microarrays (TMAs) allow multiplexed analysis of tissue samples and are frequently used to estimate biomarker protein expression in tumour biopsies. TMA Navigator (www.tmanavigator.org) is an open access web application for analysis of TMA data and related information, accommodating categorical, semi-continuous and continuous expression scores. Non-biological variation, or batch effects, can hinder data analysis and may be mitigated using the ComBat algorithm, which is incorporated with enhancements for automated application to TMA data. Unsupervised grouping of samples (patients) is provided according to Gaussian mixture modelling of marker scores, with cardinality selected by Bayesian information criterion regularization. Kaplan-Meier survival analysis is available, including comparison of groups identified by mixture modelling using the Mantel-Cox log-rank test. TMA Navigator also supports network inference approaches useful for TMA datasets, which often constitute comparatively few markers. Tissue and cell-type specific networks derived from TMA expression data offer insights into the molecular logic underlying pathophenotypes, towards more effective and personalized medicine. Output is interactive, and results may be exported for use with external programs. Private anonymous access is available, and user accounts may be generated for easier data management.

Original languageEnglish
Pages (from-to)W562-W568
Number of pages7
JournalNucleic Acids Research
Volume41
Issue numberW1
DOIs
Publication statusPublished - Jul 2013

Keywords

  • False discovery rate
  • Breast-cancer
  • Protein expression
  • Quantitative-analysis
  • Gene networks
  • Human-disease
  • Pathways
  • Validation
  • Optimization
  • Technology

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