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Advances in Bioinformatics
Volume 2011 (2011), Article ID 184731, 11 pages
Data-Driven Compensation for Flow Cytometry of Solid Tissues
1Department of Pathology, Atrium Medical Centre, P.O. Box 4446, 6401 CX Heerlen, The Netherlands
2TiCC, Tilburg University, Warandelaan 2, 5037 AB Tilburg, The Netherlands
Received 3 February 2011; Revised 20 May 2011; Accepted 8 June 2011
Academic Editor: Shandar Ahmad
Copyright © 2011 Nickolaas Maria van Rodijnen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- C. B. Bagwell and E. G. Adams, “Fluorescence spectral overlap compensation for any number of flow cytometry parameters,” Annals of the New York Academy of Sciences, vol. 677, pp. 167–184, 1993.
- C. C. Stewart and S. J. Stewart, “Four color compensation,” Communications in Clinical Cytometry, vol. 38, no. 4, pp. 161–175, 1999.
- M. Roederer, “Compensation in flow cytometry,” Current Protocols in Cytometry, vol. chapter 1, unit 1.14, 2002.
- L. A. Herzenberg, J. Tung, W. A. Moore, L. A. Herzenberg, and D. R. Parks, “Interpreting flow cytometry data: a guide for the perplexed,” Nature Immunology, vol. 7, no. 7, pp. 681–685, 2006.
- M. Roederer, “Spectral compensation for flow cytometry: visualization artifacts, limitations, and caveats,” Cytometry, vol. 45, no. 3, pp. 194–205, 2001.
- M. P. Leers, R. H. Schoffelen, J. G. Hoop et al., “Multiparameter flow cytometry as a tool for the detection of micrometastatic tumour cells in the sentinel lymph node procedure of patients with breast cancer,” Journal of Clinical Pathology, vol. 55, no. 5, pp. 359–366, 2002.
- M. P. Leers, B. Schutte, P. H. Theunissen, F. C. Ramaekers, and M. Nap, “Heat pretreatment increases resolution in DNA flow cytometry of paraffin-embedded tumor tissue,” Cytometry, vol. 35, no. 3, pp. 260–266, 1999.
- W. E. Corver, C. J. Cornelisse, and G. J. Fleuren, “Simultaneous measurement of two cellular antigens and DNA using fluorescein-isothiocyanate, R-phycoerythrin, and propidium iodide on a standard FACScan,” Cytometry, vol. 15, no. 2, pp. 117–128, 1994.
- R. P. Wersto, F. J. Chrest, J. F. Leary, C. Morris, M. Stetler-Stevenson, and E. Gabrielson, “Doublet discrimination in DNA cell-cycle analysis,” Communications in Clinical Cytometry, vol. 46, no. 5, pp. 296–306, 2001.
- W. E. Corver, G. J. Fleuren, and C. J. Cornelisse, “Software compensation improves the analysis of heterogeneous tumor samples stained for multiparameter DNA flow cytometry,” Journal of Immunological Methods, vol. 260, no. 1-2, pp. 97–107, 2002.
- M. Roederer and R. F. Murphy, “Cell-by-cell autofluorescence correction for low signal-to-noise systems: application to epidermal growth factor endocytosis by 3T3 fibroblasts,” Cytometry, vol. 7, no. 6, pp. 558–565, 1986.
- J. W. Tung, D. R. Parks, W. A. Moore, L. A. Herzenberg, and L. A. Herzenberg, “New approaches to fluorescence compensation and visualization of FACS data,” Clinical Immunology, vol. 110, no. 3, pp. 277–283, 2004.
- D. R. Parks, M. Roederer, and W. A. Moore, “A new “logicle” display method avoids deceptive effects of logarithmic scaling for low signals and compensated data,” Cytometry A, vol. 69, no. 6, pp. 541–551, 2006.
- L. Balkay, fca_readfcs, Matlab central file exchange, vol. File ID: #9608, 2009, http://www.mathworks.com/matlabcentral/fileexchange/9608-fcs-data-reader.
- J. J. More and D. C. Sorensen, “Computing a trust region step,” SIAM Journal on Scientific Computing, vol. 3, pp. 553–572, 1983.
- R. H. Byrd, R. B. Schnabel, and G. A. Shultz, “Approximate solution of the trust region problem by minimization over two-dimensional subspaces,” Mathematical Programming, vol. 40, no. 3, pp. 247–263, 1988.
- M. A. Branch, T. F. Coleman, and Y. Li, “Subspace, interior, and conjugate gradient method for large-scale bound-constrained minimization problems,” SIAM Journal on Scientific Computing, vol. 21, no. 1, pp. 1–23, 1999.
- H. T. Maecker and J. Trotter, “Flow cytometry controls, instrument setup, and the determination of positivity,” Cytometry A, vol. 69, no. 9, pp. 1037–1042, 2006.
- DAKO, “Summit 4.0 reference guide,” Tech. Rep.
- I. Verity Software House, "WINLIST user guide," no. revision date: June 2001.
- M. G. Ormerod, B. Tribukait , and W. Giaretti, “Consensus report of the task force on standardisation of DNA flow cytometry in clinical pathology. DNA flow cytometry task force of the European society for analytical cellular pathology,” Analytical Cellular Pathology, vol. 17, no. 2, pp. 103–110, 1998.
- P. K. Chattopadhyay, C. M. Hogerkorp, and M. Roederer, “A chromatic explosion: the development and future of multiparameter flow cytometry,” Immunology, vol. 125, no. 4, pp. 441–449, 2008.
- J. Quinn, P. W. Fisher, R. J. Capocasale et al., “A statistical pattern recognition approach for determining cellular viability and lineage phenotype in cultured cells and murine bone marrow,” Cytometry A, vol. 71, no. 8, pp. 612–624, 2007.
- G. Walther, N. Zimmerman, W. Moore et al., “Automatic clustering of flow cytometry data with density-based merging,” Advances in Bioinformatics, Article ID 686759, 2009.
- C. C. Stewart and S. J. Stewart, “A software method for color compensation,” Current Protocols in Cytometry, vol. chapter 10, unit 10.15, 2003.