title: The use of simultaneous confidence bands for comparison of single parameter fluorescent intensity data.
abstract: Despite the utility of multiparameter flow cytometry for a wide variety of biological applications, comparing single parameter histograms of fluorescence intensity remains a mainstay of flow cytometric analysis. Even comparisons requiring multiparameter gating strategies often end with single parameter histograms as the final readout. When histograms overlap, analysis relies on comparison of mean or median fluorescence intensities, or determination of percent positive based on an arbitrary cutoff. Earlier attempts to address this problem utilized either simple channel-by-channel subtraction without statistical evaluation, or the Kolmogorov-Smirnov (KS) or Chi-square test statistics, both of which proved to be overly sensitive to small and biologically insignificant differences. Here we present a method for the comparison of two single-parameter histograms based on difference curves and their simultaneous confidence bands generated by bootstrapping raw channel data. Bootstrapping is a nonparametric statistical approach that can be used to generate confidence intervals without distributional assumptions about the data. We have constructed simultaneous confidence bands and show them to be superior to KS and Cox methods. The method constructs 95% confidence bands about the difference curves, provides a P value for the comparison and calculates the area under the difference curve (AUC) as an estimate of percent positive and the area under the confidence band (AUCSCB95), providing a lower estimate of the percent positive. To demonstrate the utility of this new approach we have examined single-color fluorescence intensity data taken from a cell surface proteomic survey of a lung cancer cell line (A549) and a published fluorescence intensity data from a rhodamine efflux assay of P-glycoprotein activity, comparing rhodamine 123 loading and efflux in CD4 and CD8 T-cell populations. SAS source code is provided as supplementary material.
authors.affiliation: Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.
authors.forename: Dongha
authors.initials: D
authors.lastname: Kim
authors.affiliation: University of Pittsburgh Cancer Center, Pittsburgh, Pennsylvania.|Department of Cardiothoracic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.|McGowan Institute of Regenerative Medicine, Pittsburgh, Pennsylvania.
authors.forename: Vera S
authors.initials: VS
authors.lastname: Donnenberg
authors.affiliation: Department of Biostatistics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, Pennsylvania.
authors.forename: John W
authors.initials: JW
authors.lastname: Wilson
authors.affiliation: University of Pittsburgh Cancer Center, Pittsburgh, Pennsylvania.|McGowan Institute of Regenerative Medicine, Pittsburgh, Pennsylvania.|Department of Medicine, University of Pittsburgh School of Medicine.
authors.forename: Albert D
authors.initials: AD
authors.lastname: Donnenberg
mesh_terms: D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1 / Q000032:analysis*; D000465:Algorithms; D019540:Area Under Curve; D015496:CD4-Positive T-Lymphocytes / Q000166:cytology*; D018414:CD8-Positive T-Lymphocytes / Q000166:cytology*; D045744:Cell Line, Tumor; D003627:Data Interpretation, Statistical; D005434:Flow Cytometry / Q000379:methods*; D006801:Humans; D040901:Proteomics / Q000379:methods*; D020112:Rhodamine 123; D013194:Staining and Labeling
chemical_list: D020168:ATP Binding Cassette Transporter, Subfamily B, Member 1; D020112:Rhodamine 123
keywords: bootstrapping; mean fluorescence intensity; simultaneous confidence bands; single parameter histograms