On the inverse problem in flow cytometry recovering DNA distribution from FMF data

The problem of recovering DNA distribution from cytofluorometric experimental data was investigated. Theoretical analysis led to a convenient formulation of the problem and to uniqueness results for its solution. A minimization algorithm has been implemented to get the optimal estimate of G₁, S, G₂, and M phase percentages. This algorithm was tested in some experimental cases.     

On multiparameter data analysis in flow cytometry

Increasing numbers of parameters that are accessible to simultaneous measurement in flow cytometric instruments, combined with the extremely large sample sizes common in flow cytometry, make it necessary to examine methods of multivariate statistics for their applicability to problems of visualization and quantitative analysis of flow cytometric data. This article describes some approaches to dimensionality reduction that appear well suited for data sets obtained by flow cytometry.     

DNA distribution in biopsy specimens from human cervical carcinoma investigated by flow cytometry.

Flow cytometry was used for the investigation of the DNA distribution in biopsy specimens from 51 patients with cervical carcinoma. Portio biopsy specimens from 9 pregnant women and from 10 patients with cancer of the breast served as controls. The results demonstrate that most specimens from patients suffering from cervical carcinoma contain considerable cell populations with increased DNA as compared with controls. The possible clinical significance of these findings is discussed.     

Analysis of DNA distributions from flow cytometry

A recently proposed automatic procedure for analyzing DNA distribution from flow cytometric data is extensively tested against simulated data. After a discussion of the procedure itself and of the simulation program, the results obtained are reported. They are evidence of the reliability of the procedure in extracting the proper underlying DNA distribution from sets of data obtained under various simulated instances. The different sources of error are then analyzed, along with their quantitative effects on the fit of the fluorescence histogram.     

Identifiability of DNA distribution from flow cytometric data with cell debris

In flow cytometric measurement of cell DNA distribution one of the major problems is accounting for the effect of fragmentation in the staining process. This work considers a recent probabilistic model that has been proposed for the fragmentation process and species under which conditions it is possible to uniquely identify the DNA distributions of the original population using flow cytometric data. Attention is given both to the normal and to the polyploid case. This work was partially supported by a grant of the Italian National Research Council, Special Project “Oncology”, contract number 84.00632.44.     

DNA analysis by flow cytometry

Accurate quantification of DNA from cells of several species is possible with flow cytometry. When one species is used as a reference, cytometric readings from two or more different species can be compared to obtain relative percent DNA or DNA indices. Differences in DNA from the male and female of the same species also can be measured. The method allows rapid screening of chromosomal abnormalities among large clinical populations, and evaluation of errors of sex determination such as XY sex reversal.     

The inverse problem for DNA

The DNA distribution function for a given section of DNA of a given length depends on the nucleotide composition. It can be expressed in terms of other functions, such as specific heat, optical density, etc., if they are measured in the vicinity of the DNA melting point.     

Statistical evaluation of cell kinetic data from DNA flow cytometry (FCM) by the EM algorithm

Flow cytometric DNA measurements yield the amount of DNA for each of a large number of cells. A DNA histogram normally consists of a mixture of one or more constellations of G0/G1-, S-, G2/M-phase cells, together with internal standards, debris, background noise, and one or more populations of clumped cells. We have modelled typical DNA histograms as a mixed distribution with Gaussian densities for the G0/G1 and G2/M phases, an S-phase density, assumed to be uniform between the G0/G1 and G2/M peaks, observed with a Gaussian error, and with Gaussian densities for standards of chicken and trout red blood cells. The debris is modelled as a truncated exponential distribution, and we also have included a uniform background noise distribution over the whole observation interval. We have explored a new approach for maximum-likelihood analyses of complex DNA histograms by the application of the EM algorithm. This algorithm was used for four observed DNA histograms of varying complexity. Our results show that the algorithm works very well, and it converges to reasonable values for all parameters. In simulations from the estimated models, we have investigated bias, variance, and correlations of the estimates.     

Analysis of DNA distributions from flow cytometry. Validation of an automatic procedure against simulated data

A recently proposed automatic procedure for analyzing DNA distribution from flow cytometric data is extensively tested against simulated data. After a discussion of the procedure itself and of the simulation program, the results obtained are reported. They are evidence of the reliability of the procedure in extracting the proper underlying DNA distribution from sets of data obtained under various simulated instances. The different sources of error are then analyzed, along with their quantitative effects on the fit of the fluorescence histogram.     

Multi-user system for analysis of data from flow cytometry.

A new program is described for the analysis of DNA histograms from flow cytometry. The fundamental model representing the cell population is similar to one described previously. It assumes the population is grouped into compartments, each consisting of cells having approximately the same DNA content. After staining the cells with an appropriate fluorochrome, the fluorescence distribution of cells within each compartment is assumed to be Gaussian. In the present algorithm, the parameters of the model can either be computed directly by the program from the data, or can be specified as input by the user. When synchronous cell populations lacking distinct G1 and G2/M phases are analyzed, the parameter values must first be obtained using an appropriate control. Percentages of cells in the various compartments are computed using a gradient search method described by Bevington.     

Using flowViz to visualize flow cytometry data

Summary: Automated analysis of flow cytometry (FCM) data isessential for it to become successful as a high throughput technology.We believe that the principles of Trellis graphics can be adaptedto provide useful visualizations that can aid such automation.In this article, we describe the R/Bioconductor package flowVizthat implements such visualizations. Availability: flowViz is available as an R package from theBioconductor project: http://bioconductor.org Contact: dsarkar{at}fhcrc.org Associate Editor: Olga Troyanskaya     

Introduction to flow cytometry data file standard

The Data File Standards Committee of the Society for Analytical Cytology presents a Standard to be used for the storage of data associated with flow cytometric measurements. The Standard specifies a format that provides for the inclusion of all information necessary to fully describe: 1) the instrument used for the measurement; 2) the sample measured; 3) the data obtained; and 4) the results of analysis of the data. The Committee and the Society for Analytical Cytology point out that the use of this Standard by all those individuals and companies that generate or use data taken with flow cytometers or generate methods of analysis for the data will encourage the sharing of such data and methods of analysis.     

Precision of DNA flow cytometry in inter-institutional analyses

A Bladder Cancer Flow Cytometry Network study has been carried out to further identify and quantify sources of inter- and intra-laboratory variability. Replicate samples containing four mixtures of peripheral blood lymphocytes and aneuploid cell lines were distributed together with reference standards to six laboratories. The samples were stained for DNA using propidium iodide, with each laboratory using its own staining protocol. Two of each of the four sample types and a reference standard were analyzed by each laboratory on 3 separate days to obtain cellular DNA distributions. DNA index (DI) and hyperdiploid fraction (HDF) were calculated for each histogram using an automated technique. The results showed significant inter- and intra-laboratory differences. Results were evaluated by a two-way analysis of variance to estimate components of the overall variation attributable to individual sources. Error variation was found to be the major component of random variation. Specimen means were also compared for each laboratory. No significant differences were noted in mean DI for similar specimens; however, agreement in HDF between similar specimens was lacking in most laboratories. Prediction intervals were computed to estimate the range of values expected for a single specimen based on the analysis of the previous six. Prediction intervals for DI were quite good while those for HDF were troublesome due to wide variation. The results of these studies indicate that intra- and inter-laboratory variability are high enough that results for a single sample may not be sufficiently precise to allow comparison to results obtained in other laboratories.(ABSTRACT TRUNCATED AT 250 WORDS)     

Nonparametric discriminant analysis of phytoplankton species using data from analytical flow cytometry

BACKGROUND: Analytical flow cytometry (AFC) provides rapid and accurate measurement of particles from heterogeneous populations. AFC has been used to classify and identify phytoplankton species, but most methods of discriminant analysis of resulting data have depended on normality assumptions and outcomes have been disappointing. METHODS AND RESULTS: In this study, we consider nonparametric methods based on density estimation. In addition to the familiar kernel method, methods based on wavelets are also implemented. Full five-dimensional wavelet estimation proves to be computationally prohibitive with current workstation power, so we employ projection pursuit for reduction of dimensionality. AFC typically produces very large samples, so we also investigate data simplification through binning. Further modifications to the discrimination strategy are suggested by specific features of phytoplankton data, namely, a hierarchical group structure, the possible presence of many groups, and the likelihood of encountering an aberrant group in a test sample. CONCLUSIONS: We apply all the resultant procedures to appropriate subsets of a very large data set, demonstrate their efficacy, and compare their error rates with those of more conventional methods. We further show that incorporation of the specific features of phytoplankton data into the analysis leads to improved results and provides a general framework for analysis of such data.     

Determination of liposome size distribution by flow cytometry

BACKGROUND: An essential parameter that describes the quality of liposome suspensions is the mean size, respectively the size distribution. Currently several analytical methods including laser light scattering techniques (LLST) are being employed. METHODS: Here we present an alternative technique using flow cytometry (FCM) to characterize uni- and polydisperse suspensions. As model liposomes preparations containing dipalmitoylphosphatidylcholine (DPPC) were used. A constant number of particles (1,500/s) in the fluid stream and a representative number of 10,000 particles of each sample was measured. Fluorescence-labeled latex beads were measured identically, and their side scatter signals were calibrated and correlated to the results obtained with liposome vesicles. RESULTS: Evaluation of the measurement and validation of the FCM results in comparison to LLST confirm the reliability of results obtained with our method. Latex beads in the range of 100-1000 nm were used for calibration to classify liposomes. Although measurement characteristics and calculation in both methods are basically different, very good agreement of the results was achieved. CONCLUSIONS: Demonstration of stability, reproducibility, and reliability of results make the employment of this method acceptable for an adequate routine analysis technique.     

Web servlet-assisted, dial-in flow cytometry data analysis

BACKGROUND: The obvious benefits of centralized data storage notwithstanding, the size of modern flow cytometry data files discourages their transmission over commonly used telephone modem connections. The proposed solution is to install at the central location a web servlet that can extract compact data arrays, of a form dependent on the requested display type, from the stored files and transmit them to a remote client computer program for display. METHODS: A client program and a web servlet, both written in the Java programming language, were designed to communicate over standard network connections. The client program creates familiar numerical and graphical display types and allows the creation of gates from combinations of user-defined regions. Data compression techniques further reduce transmission times for data arrays that are already much smaller than the data file itself. RESULTS: For typical data files, network transmission times were reduced more than 700-fold for extraction of one-dimensional (1-D) histograms, between 18 and 120-fold for 2-D histograms, and 6-fold for color-coded dot plots. Numerous display formats are possible without further access to the data file. CONCLUSIONS: This scheme enables telephone modem access to centrally stored data without restricting flexibility of display format or preventing comparisons with locally stored files.     

Measurement variability in DNA flow cytometry of replicate samples

A Bladder Cancer Flow Cytometry Network study has been carried out aimed at identification of the sources of inter- and intralaboratory variability. Replicate "cocktail" samples containing a mixture of peripheral blood lymphocytes and an aneuploid cell line and samples of peripheral blood lymphocytes serving as a DNA reference standard were distributed to five network laboratories. The samples were stained for DNA using propidium iodide, with each laboratory using its own staining protocol. Sets of these samples were analyzed by flow cytometry to obtain cellular DNA distributions. DNA index and hyperdiploid fraction were calculated for each histogram using an automated technique. Results were evaluated by analysis of variance to identify sources of variability. Three important sources of variation were found that affect flow cytometry in general and- the transportability of flow cytometry results to routine clinical use in particular. The significant variation among laboratories that is constant across time most probably represents stable differences in instrumentation, instrument set-up, and laboratory techniques. This variation can be compensated for, if it is known and stable, to develop transportable classification criteria. The second type of variation, termed the interaction component, represents differences among laboratories that are not constant across time. Sources of this variation include inconsistency in sample preparation, staining, and analysis. The elimination of this type of variation is required for meaningful comparison of data within and among laboratories and the creation of interlaboratory data-bases. The third type of variation represents pure measurement variability and affects the sensitivity of the technique.