title: Effects of resolution reduction on data analysis.
abstract: BACKGROUND
  There is often a need in flow cytometry to display and analyze histograms at resolutions lower than those native to the data. It is common, for example, to analyze DNA histograms at 256-channel resolution, even though the data were acquired at 1,024 channels or more. The most common method for reducing resolution, referred to as the consecutive summation (CS) method, can introduce distortions into the shape of histograms. Peaks that were symmetric in the original data can become skewed in the reduced-resolution histogram. Data analysis can be negatively affected by the distortions produced by reducing the histogram resolution. An alternative technique for reducing histogram resolution, the unbiased summation (US) method, minimizes shape distortion. This paper describes the US method and examines the benefits it provides in the analysis of DNA histograms.
  
  
  METHODS
  Reduced chi-square (RCS) was used to measure the response to three experimental variables in the least-squares analysis of simulated DNA histograms. For each variable (the percentage of coefficient of variation [%CV], number of events, and mean position of the G1 distribution), a test data set of 1,000 histograms was generated at 1,024-channel resolution. Histogram resolutions were reduced with each method and then analyzed with ModFit LT cell-cycle analysis software (Verity Software House, Topsham, ME). S-phase error and processor computation time of each method also were evaluated. A Monte Carlo experiment was performed to compare CS and US methods to theoretically correct reductions.
  
  
  RESULTS
  CS method analysis results were negatively affected by changes in %CV, number of events, and G1 peak position. The US method produced consistently lower RCS values (more accurate results) within the tested ranges. The US method eliminated bias in S-phase error and had negligible impact on analysis processing speed. It improved RCS values 44.50% on average (P < 0.0002) with actual DNA histograms. Whereas the CS method became less accurate (chi-square test) as the amount of reduction increased, the US method was unaffected, producing consistently better results.
  
  
  CONCLUSIONS
  The US method is recommended for reducing histogram resolution in modeling applications such as DNA cell-cycle analysis. It may have implications in other areas of flow cytometric data analysis.
authors.affiliation: Verity Software House, Inc., PO Box 247, Topsham, ME 04086, USA. bch@vsh.com
authors.forename: B
authors.initials: B
authors.lastname: Hunsberger
authors.forename: C B
authors.initials: CB
authors.lastname: Bagwell
authors.forename: D
authors.initials: D
authors.lastname: Herbert
authors.forename: C
authors.initials: C
authors.lastname: Bray
authors.forename: M
authors.initials: M
authors.lastname: Langweiler
mesh_terms: D000465:Algorithms; D002453:Cell Cycle / Q000235:genetics; D016009:Chi-Square Distribution; D004247:DNA / Q000032:analysis; D003627:Data Interpretation, Statistical; D005434:Flow Cytometry / Q000379:methods*; D016193:G1 Phase / Q000235:genetics; D015233:Models, Statistical; D015203:Reproducibility of Results; D016196:S Phase / Q000235:genetics; D016008:Statistical Distributions; D013997:Time Factors
chemical_list: D004247:DNA