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Issue No.12 - Dec. (2011 vol.17)
pp: 1882-1891
Steffen Oeltze , Universität Magdeburg
Wolfgang Freiler , SimVis GmbH, Vienna
Reyk Hillert , University of Magdeburg
Helmut Doleisch , SimVis GmbH, Vienna
Bernhard Preim , University of Magdeburg
Walter Schubert , University of Magdeburg
ABSTRACT
In Toponomics, the function protein pattern in cells or tissue (the toponome) is imaged and analyzed for applications in toxicology, new drug development and patient-drug-interaction. The most advanced imaging technique is robot-driven multi-parameter fluorescence microscopy. This technique is capable of co-mapping hundreds of proteins and their distribution and assembly in protein clusters across a cell or tissue sample by running cycles of fluorescence tagging with monoclonal antibodies or other affinity reagents, imaging, and bleaching in situ. The imaging results in complex multi-parameter data composed of one slice or a 3D volume per affinity reagent. Biologists are particularly interested in the localization of co-occurring proteins, the frequency of co-occurrence and the distribution of co-occurring proteins across the cell. We present an interactive visual analysis approach for the evaluation of multi-parameter fluorescence microscopy data in toponomics. Multiple, linked views facilitate the definition of features by brushing multiple dimensions. The feature specification result is linked to all views establishing a focus+context visualization in 3D. In a new attribute view, we integrate techniques from graph visualization. Each node in the graph represents an affinity reagent while each edge represents two co-occurring affinity reagent bindings. The graph visualization is enhanced by glyphs which encode specific properties of the binding. The graph view is equipped with brushing facilities. By brushing in the spatial and attribute domain, the biologist achieves a better understanding of the function protein patterns of a cell. Furthermore, an interactive table view is integrated which summarizes unique fluorescence patterns. We discuss our approach with respect to a cell probe containing lymphocytes and a prostate tissue section.
INDEX TERMS
Visual Analytics, Fluorescence Microscopy, Toponomics, Protein Interaction, Graph Visualization.
CITATION
Steffen Oeltze, Wolfgang Freiler, Reyk Hillert, Helmut Doleisch, Bernhard Preim, Walter Schubert, "Interactive, Graph-based Visual Analysis of High-dimensional, Multi-parameter Fluorescence Microscopy Data in Toponomics", IEEE Transactions on Visualization & Computer Graphics, vol.17, no. 12, pp. 1882-1891, Dec. 2011, doi:10.1109/TVCG.2011.217
REFERENCES
[1] A. Barysenka, A. W. M. Dress, and W. Schubert, An information theoretic thresholding method for detecting protein colocalizations in stacks of fluorescence images. J Biotechnol, 149 (3): 127–131, 2010.
[2] S. Bhattacharya, G. Mathew, E. Ruban, D. B. A. Epstein, A. Krusche, R. Hillert, W. Schubert, and M. Khan, Toponome imaging system: in situ protein network mapping in normal and cancerous colon from the same patient reveals more than five-thousand cancer specific protein clusters and their subcellular annotation by using a three symbol code. J Proteome Res, 9 (12): 6112–6125, 2010.
[3] B. Chapman, G. Jost, and R. v. d. Pas, Using OpenMP: Portable shared memory parallel programming. The MIT Press, 2007.
[4] W. S. Cleveland and R. McGill, Graphical perception: Theory, experimentation, and application to the development of graphical methods. J Am Stat Assoc, 79 (387): 531–554, 1984.
[5] W. de Leeuw, P. J. Verschure, and R. van Liere, Visualization and analysis of large data collections: a case study applied to confocal microscopy data. IEEE Trans Visual Comput Graph, 12 (5): 1251–1258, 2006.
[6] J. Dietzsch, J. Heinrich, K. Nieselt, and D. Bartz, SpRay: A visual analytics approach for gene expression data. In Proc. IEEE Symp. Visual Analytics Science and Technology VAST, pages 179–186, 2009.
[7] H. Doleisch, M. Gasser, and H. Hauser, Interactive feature specification for focus+context visualization of complex simulation data. In Proc. of IEEE TCVG - EUROGRAPHICS Symp. on Vis., pages 239–248, 2003.
[8] H. Doleisch and H. Hauser, Smooth brushing for focus+context visualization of simulation data in 3D. Journal of WSCG, 10 (1): 147–154, 2002.
[9] A. Dress, T. Lokot, L. Pustyl'nikov, and W. Schubert, Poisson numbers and poisson distributions in subset surprisology. Annals of Combinatorics, 8: 473–485, 2005.
[10] M. Friedenberger, M. Bode, A. Krusche, and W. Schubert, Fluorescence detection of protein clusters in individual cells and tissue sections by using toponome imaging system: sample preparation and measuring procedures. Nat Protoc, 2 (9): 2285–2294, 2007.
[11] T. M. J. Fruchterman and E. M. Reingold, Graph drawing by force-directed placement. Softw. Pract. Exper., 21: 1129–1164, 1991.
[12] G. Furnas, Generalized fisheye views. In Proc. of the ACM CHI Conf. on Human Factors in Computing Systems, pages 16–23, 1986.
[13] E. Gansner and Y. Koren, Improved circular layouts. In M. Kaufmann, and D. Wagner editors, Graph Drawing, volume 4372 of Lecture Notes in Computer Science, pages 386–398. Springer, 2007.
[14] N. Gehlenborg, S. I. O'Donoghue, N. S. Baliga, A. Goesmann, M. A. Hibbs, H. Kitano, O. Kohlbacher, H. Neuweger, R. Schneider, D. Tenen-baum, and A.-C. Gavin, Visualization of omics data for systems biology. Nat Methods, 7 (3 Suppl): S56–S68, 2010.
[15] H. Hauser, Generalizing focus+context visualization. In Scientific Visualization: The Visual Extraction of Knowledge from Data, pages 305–327, 2005.
[16] D. Holten, Hierarchical edge bundles: Visualization of adjacency relations in hierarchical data. IEEE Trans Visual Comput Graph, 12 (5): 741 –748, 2006.
[17] D. Holten and J. J. van Wijk, Force-directed edge bundling for graph visualization. Comput Graph Forum, 28 (3): 983–990, 2009.
[18] Z. Hu, J. Mellor, J. Wu, and C. DeLisi, VisANT: an online visualization and analysis tool for biological interaction data. BMC Bioinformatics, 5: 17, 2004.
[19] M. Meyer, T. Munzner, and H. Pfister, MizBee: A multiscale synteny browser. IEEE Trans Visual Comput Graph, 15: 897–904, 2009.
[20] P. Muigg, J. Kehrer, S. Oeltze, H. Piringer, H. Doleisch, B. Preim, and H. Hauser, A four-level focus+context approach to interactive visual analysis of temporal features in large scientific data. Comput Graph Forum, 27 (3): 775–782, 2008.
[21] S. Oeltze, H. Doleisch, H. Hauser, P. Muigg, and B. Preim, Interactive visual analysis of perfusion data. IEEE Trans Visual Comput Graph, 13 (6): 1392–1399, 2007.
[22] G. A. Pavlopoulos, S. I. O'Donoghue, V. P. Satagopam, T. G. Soldatos, E. Pafilis, and R. Schneider, Arena3D: visualization of biological networks in 3D. BMC Syst Biol, 2: 104, 2008.
[23] S. P. Perfetto, P. K. Chattopadhyay, and M. Roederer, Seventeen-colour flow cytometry: unravelling the immune system. Nat Rev Immunol, 4 (8): 648–655, 2004.
[24] R. Rao and S. K. Card, The table lens: merging graphical and symbolic representations in an interactive focus + context visualization for tabular information. In Proc. of the ACM CHI Conf. on Human Factors in Computing Systems, pages 318–322, 1994.
[25] B. E. Rogowitz, L. A. Treinish, and S. Bryson, How not to lie with visualization. Comput. Phys., 10:268–273, 1996.
[26] M. Sarkar and M. H. Brown, Graphical fisheye views of graphs. In Proc. of the ACM CHI Conf. on Human Factors in Computing Systems, pages 83–91, 1992.
[27] W. Schubert, Multiple antigen-mapping microscopy of human tissue. In Advances in analytical cellular pathology, Excerpta Medica, pages 97– 98. Elsevier, 1990.
[28] W. Schubert, Topological proteomics, toponomics, melk-technology. Adv Biochem Eng Biotechnol, 83: 189–209, 2003.
[29] W. Schubert, A three-symbol code for organized proteomes based on cyclical imaging of protein locations. Cytometry A, 71 (6): 352–360, 2007.
[30] W. Schubert, On the origin of cell functions encoded in the toponome. J Biotechnol, 149 (4): 252–259, 2010.
[31] W. Schubert, M. Bode, R. Hillert, A. Krusche, and M. Friedenberger, To-ponomics and neurotoponomics: a new way to medical systems biology. Expert Rev Proteomics, 5 (2): 361–369, 2008.
[32] W. Schubert, B. Bonnekoh, A. J. Pommer, L. Philipsen, R. Bckelmann, Y. Malykh, H. Gollnick, M. Friedenberger, M. Bode, and A. W. M. Dress, Analyzing proteome topology and function by automated multidimensional fluorescence microscopy. Nat Biotechnol, 24 (10): 1270–1278, 2006.
[33] W. Schubert, M. Friedenberger, M. Bode, A. Krusche, and R. Hillert, Functional architecture of the cell nucleus: towards comprehensive toponome reference maps of apoptosis. Biochim Biophys Acta, 1783 (11): 2080–2088, 2008.
[34] W. Schubert, A. Gieseler, A. Krusche, and R. Hillert, Toponome mapping in prostate cancer: detection of 2000 cell surface protein clusters in a single tissue section and cell type specific annotation by using a three symbol code. J Proteome Res, 8 (6): 2696–2707, 2009.
[35] H.-J. J, M. John, A. Unger, and H. Schumann, Visual analysis of bipartite biological networks. In VCBM'08: Proc. of the Eurographics Workshop on Visual Computing for Biomedicine, pages 135–142, 2008.
[36] P. Shannon, A. Markiel, O. Ozier, N. S. Baliga, J. T. Wang, D. Ramage, N. Amin, B. Schwikowski, and T. Ideker, Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res, 13 (11): 2498–2504, 2003.
[37] A. Symeonidis and I. Tollis, Visualization of biological information with circular drawings. In Proc. Int'l Symp. on Biological and Medical Data Analysis (ISBMDA), pages 468–478, 2004.
[38] G. H. Weber, O. Rubel, M.-Y. Y, A. H. DePace, C. C. Fowlkes, S. V. E. Keranen, C. L. Luengo Hendriks, H. Hagen, D. W. Knowles, J. Malik, M. D. Biggin, and B. Hamann, Visual exploration of three-dimensional gene expression using physical views and linked abstract views. IEEE/ACM Trans Comput Biol Bioinformatics, 6 (2): 296–309, 2009.
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