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 compen...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.展开更多
文摘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.
