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Graphical Displays for Biomarker Data

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A Picture is Worth a Thousand Tables

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Abstract

Analysis of high-dimensional biomarker data is in general of exploratory nature and aims to discover or dissect subgroups of patients sharing a specific pattern of biomarker measurements. One major challenge is to extract the relevant markers from the extremely large pool of measured markers. Specific techniques such as grouping and ordering and dimension reduction allow to aggregate huge amounts of data into single meaningful graphics. These graphics can guide the direction of exploration during the analysis. We present graphical tools for unsupervised and supervised objectives based on gene expression data of multiple myeloma patients which are part of the MAQC-II project.

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Authors and Affiliations

  1. Division of Biostatistics, German Cancer Research Center, Im Neuenheimer Feld 280, 69120, Heidelberg, Germany

    Manuela Zucknick, Thomas Hielscher, Martin Sill & Axel Benner

Authors
  1. Manuela Zucknick
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  2. Thomas Hielscher
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  3. Martin Sill
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  4. Axel Benner
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Corresponding author

Correspondence to Manuela Zucknick .

Editor information

Editors and Affiliations

  1. Clinical Pharmacology, Actelion Pharmaceuticals Ltd., Gewerbestr. 16, Allschwil, 4123, Switzerland

    Andreas Krause

  2. Tibco Software Inc., Broadway 632, New York, 10012, New York, USA

    Michael O'Connell

A.1 Appendix

A.1 Appendix

Table A.1 Subsets of genes identified in fifth principal component. Gene titles are abbreviated to show at most 40 characters
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Table A.2 Subset of genes identified in first principal component. Gene titles are abbreviated to show at most 40 characters
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Zucknick, M., Hielscher, T., Sill, M., Benner, A. (2012). Graphical Displays for Biomarker Data. In: Krause, A., O'Connell, M. (eds) A Picture is Worth a Thousand Tables. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-5329-1_8

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