Dynamic expression profiles from static cytometry data: Component fitting and conversion to relative, "same scale" values

摘要: BACKGROUND Cytometry of asynchronous proliferating cell populations produces data with an extractable time-based feature embedded in the frequency clustered, correlated events. Here, we present a specific case general methodology for calculating dynamic expression profiles epitopes that oscillate during cycle and conversion these values to same scale. METHODS Samples K562 cells from one population were labeled by direct indirect antibody methods cyclins A2 B1 phospho-S10-histone H3. The was used both cyclins. Directly stained samples counter-stained 4'6-diamidino-2-phenylindole indirectly propidium label DNA. S phase cyclin expressions assays scale multi-variate assay. Boolean gating two dimensional, sequential regions set on bivariate displays directly conjugated sample untangle isolate unique, unambiguous along four-dimensional path through cycle. median each region events within region. RESULTS runs plotted as continuous multi-line linear equations form y = [(y(i+1)-y(i))/(x(i+1)-x(i))]x + y(i)-[(y(i+1)-y(i))/(x(i+1)-x(i))]x(i) (line between points (x(i),y(i)) (x(i+1), y(i+1))) capture profile CONCLUSIONS This approach demonstrates provides rule which any other could be measured calculated. These are "state variable" outputs, useful calibrating mathematical models.