Spectral Compensation for Linear-Logarithmic Flow Cytometry Acquisitions
- 1 Atrium Medical Centre, Heerlen, The Netherlands
- 2 Atrium Medical Centre, Heerlen, The Netherlands
- 3 Atrium Medical Centre, Heerlen, The Netherlands
Abstract
Compensating for fluorescence overlap in multiparameter flow cytometry datasets, of which one parameter is linear distributed and at least one parameter is logarithmic distributed, leads usually to extreme high compensation values. We investigated this phenomenon with an adapted flow cytometry model, of which the two parameters can easily be converted from linear to logarithmic and vice versa. With the adapted model, spectral compensation was performed both for linear-logarithmic and linear-linear parameter distribution. The results of the flow cytometry model were validated with a real world example which was also compensated twice. The results of the two experiments show that the compensation values equal to the theoretically expected value when both parameters are linear distributed. However, the compensation value exceeds 100% when one of the two parameters is logarithmic distributed. In addition, we found that spectral compensation of differently distributed parameters leads to deformation of the compensated events. With the adapted flow cytometry model presented in this paper it is shown how to correctly compensate flow cytometry acquisitions with different distributed parameters.
- Bagwell, C.B. and Adams, E.G. (1993) Fluorescence Spectral Overlap Compensation for Any Number of Flow Cytometry Parameters. Annals of the New York Academy of Sciences, 677, 167-184. http://dx.doi.org/10.1111/j.1749-6632.1993.tb38775.x
- Corver, W.E., Fleuren, G.J. and Cornelisse, C.J. (2002) Software Compensation Improves the Analysis of Heterogeneous Tumor Samples Stained for Multiparameter DNA Flow Cytometry. Journal of Immunological Methods, 260, 97-107. http://dx.doi.org/10.1016/S0022-1759(01)00550-6
- Maecker, H.T. and Trotter, J. (2006) Flow Cytometry Controls, Instrument Setup, and the Determination of Positivity. Cytometry A, 69, 1037-42. http://dx.doi.org/10.1002/cyto.a.20333
- Roederer, M. (2002) Compensation in Flow Cytometry. Current Protocols in Cytometry, 22, 1.14.1-1.14.20.
- Roederer, M. (2001) Spectral Compensation for Flow Cytometry: Visualization Artifacts, Limitations, and Caveats. Cytometry, 45, 194-205. http://dx.doi.org/10.1002/1097-0320(20011101)45:3 3.0.CO;2-C
- Stewart, C.C. and Stewart, S.J. (1999) Four Color Compensation. Cytometry, 38, 161-175. http://www.liankebio.com/pdf/2003710111301fourcolorcompensation.pdf http://dx.doi.org/10.1002/(SICI)1097-0320(19990815)38:4 3.0.CO;2-A
- Stewart, C.C. and Stewart, S.J. (2003) A Software Method for Color Compensation. Current Protocols in Cytometry, Chapter 10, Unit 10 15.
- Tung, J.W., Parks, D.R., Moore, W.A., Herzenberg, L.A. and Herzenberg, L.A. (2004) New Approaches to Fluorescence Compensation and Visualization of Facs Data. Clinical Immunology, 110, 277-283. http://dx.doi.org/10.1016/j.clim.2003.11.016
- Verity Software House, Inc. (2002) A Discussion of Linear-to-Log Data Conversion in Flow Cytometry. Topsham, 1-6. http://ftp.vsh.com/publication/LinLog.pdf
- van Rodijnen, N.M., et al. (2011) Data-Driven Compensation for Flow Cytometry of Solid Tissues. Advances in Bio-informatics, 2011, Article ID: 184731. http://www.hindawi.com/journals/abi/2011/184731/abs/
- Radcliff, G. and Jaroszeski, M.J. (1998) Basics of Flow Cytometry. Methods in Molecular Biology, 91, 1-24.
- Roederer, M., De Rosa, S., Gerstein, R., Anderson, M., Bigos, M., Stovel, R., Nozaki, T., Parks, D., Herzenberg, L. and Herzenberg, L. (1997) 8 Color, 10-Parameter Flow Cytometry to Elucidate Complex Leukocyte Heterogeneity. Cytometry, 29, 328-339. http://128.210.61.51/cdroms/cyto10a/seminalcontributions/media/keypapers/8color10para.pdf http://dx.doi.org/10.1002/(SICI)1097-0320(19971201)29:4 3.0.CO;2-W