Bioinformatics pp 271-297 | Cite as

Using the QAPgrid Visualization Approach for Biomarker Identification of Cell-Specific Transcriptomic Signatures

  • Chloe Warren
  • Mario Inostroza-Ponta
  • Pablo Moscato
Part of the Methods in Molecular Biology book series (MIMB, volume 1526)


In this chapter, we illustrate the use of an integrated mathematical method for joint clustering and visualization of large-scale datasets. In applying these clustering methodologies to biological datasets, we aim to identify differentially expressed genes according to cell type by building molecular signatures supported by statistical scores. In doing so, we also aim to find a global map of highly co-expressed clusters. Variations in these clusters may well indicate other pathological trends and changes.

Key words

Clustering Visualization Neuroscience Genetics 



The authors would like to thank Prof. Manuel Graeber for his suggestion about the datasets to be explored.


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Chloe Warren
    • 1
  • Mario Inostroza-Ponta
    • 2
  • Pablo Moscato
    • 1
  1. 1.Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine (CIBM), Faculty of Engineering and Built EnvironmentThe University of NewcastleCallaghanAustralia
  2. 2.Departamento de Ingeniería Informática, Facultad de IngenieríaUniversidad de Santiago de ChileSantiagoChile

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