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Analysis of bivariate flow karyotypes
P N Dean1, S Kolla, M A Van Dilla
1Biomedical Sciences Division, Lawrence Livermore National Laboratory, California 94550.
Abstract:
Bivariate flow karyotype analysis is performed using data from chromosomes stained with two fluorescent dyes, typically chromomycin A3 and Hoechst-33258, and measured in a flow cytometer or cell sorter (Carrano et al.: Proceedings of the National Academy of Sciences of the United States of America 76:1382-1384, 1979; Gray et al.: Proceedings of the National Academy of Sciences of the United States of America 72:1231-1234, 1975; Langlois et al.: Proceedings of the National Academy of Sciences of the United States of America 79:7876-7880, 1982). In the resulting bivariate histogram, most chromosome types appear as individual peaks. In sorting of chromosomes to purify a specific chromosomal type, its corresponding peak in the bivariate histogram is delineated by a rectangular region which surrounds it. All events (objects) that fall within this region trigger the sorting process. In most cases, peaks for different chromosomal types overlap to some extent, and in addition there is always an underlying background due to chromosome fragments and clumps. Thus the sorted population will not be pure; it may include more than one chromosome type and will include debris. To determine the purity of a sort, i.e., the percentage of the sorted material that is of the actual chromosomal type desired, two methods of mathematical analysis have been developed. In the more general method, the bivariate data within an analysis region that includes the sort region, are fit with a series of bivariate Gaussian functions, one for each peak. In a simplified method, the data within the analysis region are transformed into a univariate distribution of either chromomycin A3 or Hoechst-33258 fluorescence. The peaks in these univariate distributions are fit with univariate Gaussian functions. In both methods the purity is determined mathematically. The results of both methods agree well with independent methods of analysis.
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