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@article{Abu-Absi2003,
        author = "N. R. Abu-Absi and A. Zamamiri and J. Kacmar and S. J. Balogh and F. Srienc",
        title = "Automated flow cytometry for acquisition of time-dependent population data",
        journal = "Cytometry A",
        pages = "87-96",
        volume = "51",
        number = "2",
        edition = "2003/01/24",
        year = "2003",
        month = "Feb",
        abstract = "BACKGROUND: The implementation of flow cytometry in many experimental settings can be limited by the extensive amount of sample handling and preparation required for analysis. We describe a system that automatically performs sample handling and flow cytometric analysis, thus allowing one to construct detailed pictures of changes in cell population distributions as a function of time. METHODS: Cell samples from bioreactors were loaded into a microchamber designed to perform all sample preparation steps including washing, fixation, staining, and dilution. The sample was then transported into a sample loop of known volume from which it was injected into the flow cell for determination of cell counts and measurement of scattering and fluorescence parameters. The apparatus was fully automated and controlled with a personal computer equipped with a data acquisition card. An inexpensive mechanism that continuously replenished the sheath fluid was implemented to ensure continuous and uninterrupted operation of the flow cytometer for several days. The device was interfaced with a FACSCalibur equipped with CellQuest software for data acquisition and analysis. RESULTS: The set-up was tested with batch cultures of Saccharomyces cerevisiae expressing the green fluorescent protein (GFP). On-line cell counts showed close agreement with off-line measurements throughout the exponential growth of a yeast culture. The time course of light scattering, GFP fluorescence, and viability distributions provided a detailed description of changes occurring in growing cell cultures based on sampling approximately every 15 min for more than 40 consecutive hours. Therefore, the device could be used to obtain descriptions of the dynamic behavior of cell populations with no user intervention required for several days. CONCLUSIONS: The system significantly expanded the utility of flow cytometry by eliminating cumbersome and time-consuming steps that make the application of flow cytometry impractical in certain situations. It is anticipated that the described set-up will find utility in biotechnology applications such as monitoring of cell cultures, screening of biologically active compounds, and in functional genomics efforts for phenotypic characterizations of cells.",
        annote = "Abu-Absi, Nicholas R Zamamiri, Abdelqader Kacmar, James Balogh, Steven J Srienc, Friedrich Research Support, U.S. Gov't, Non-P.H.S. United States Cytometry. Part A : the journal of the International Society for Analytical Cytology Cytometry A. 2003 Feb;51(2):87-96.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12541283"
}

@article{1227,
        author = "G. Basso and C. Case and M. C. Dell'Orto",
        title = "Diagnosis and genetic subtypes of leukemia combining gene expression and flow cytometry",
        journal = "Blood Cells Mol Dis",
        pages = "164-8",
        volume = "39",
        number = "2",
        edition = "2007/06/26",
        year = "2007",
        month = "Sep-Oct",
        abstract = "Acute leukemia, defined as a genetic disease, is the most common cancer in children representing about one half of all cancers among persons younger than 15 years. Acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) each represents a heterogeneous complex of disorders, with genetic abnormalities presenting in more than 80% of ALLs and more than 90% of AMLs. The diagnostic gold standard and classification of leukaemia involves various methods including morphology, cytochemistry, cytogenetics and molecular genetics, immunophenotyping, and molecular biology. These diagnostic methods are a prerequisite for individual treatment strategies and for the evaluation of treatment response especially considering that many distinct types of acute leukemia are known to carry predictable prognoses and warrant specific therapy. The quantification of gene expression is essential in determination of tailored therapeutic decisions. Microarray technology offers the possibility of quantifying thousands of genes in a single analysis, thus potentially becoming an essential tool for molecular classification to be used in routine leukaemia diagnostics. MLL+ leukaemia is a perfect example as to the exact correspondence between gene expression and protein expression evaluated by flow cytometry. Applying computational analysis to flow cytometry results, it is possible to distinguish the MLL+ acute leukemia from MLL- acute leukemia using as the top ranked antigen some top ranked genes described in the Microarray evaluation. Key markers discriminating different leukemia phenotypes can be identified by univariate hypothesis testing from a data set of immunophenotypic markers described by two variables, one reflecting the intensity of expression (MESF) and the other the pattern of distribution (CV). A current multi center study called Microarray Innovations in Leukemia (MILE Study) uses higher density gene chips providing nearly complete coverage of the human genome. The study which has analyzed thus far 1837 retrospective cases shows that each important leukemia subtype has a specific genetic fingerprint, meaning that different combinations of genes whose expression is linked to each subtype can be identified allowing for patient tailored therapy. Moreover, the study has achieved 97% diagnostic accuracy on samples from tested patients. Statistical analysis has shown a high concordance level between standard diagnostic procedures and those of the microarray technology--globally around 95.6%. Additionally it is possible to correctly classify some subgroups incorrectly identified using gold standard methods. Thus, from a technical viewpoint, gene expression profiling in tandem with flow cytometry should be a viable alternative to standard diagnostic approaches. Whether gene expression profiling will become a practical diagnostic alternative remains to be seen.",
        annote = "Basso, Giuseppe Case, Colette Dell'Orto, Marta Campo United States Blood cells, molecules & diseases Blood Cells Mol Dis. 2007 Sep-Oct;39(2):164-8. Epub 2007 Jun 27.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17588788"
}

@article{1342,
        author = "Y. Benjamini and Y. Hochberg",
        title = "Controlling the False Discovery Rate - a Practical and Powerful Approach to Multiple Testing",
        journal = "Journal of the Royal Statistical Society Series B-Methodological",
        pages = "289-300",
        volume = "57",
        number = "1",
        year = "1995",
        issn = "0035-9246",
        abstract = "The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses - the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferroni-type procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.",
        annote = "Qe453 Times Cited:4266 Cited References Count:14",
        uri = "<Go to ISI>://A1995QE45300017"
}

@article{56,
        author = "T. Bernas and E. K. Asem and J. P. Robinson and B. Rajwa",
        title = "Quadratic form: a robust metric for quantitative comparison of flow cytometric histograms",
        journal = "Cytometry A",
        pages = "715-26",
        volume = "73",
        number = "8",
        edition = "2008/06/19",
        year = "2008",
        month = "Aug",
        abstract = "Comparison of fluorescence distributions is a fundamental part of the analysis of flow cytometric data. This approach is applied to detect differences between control and test sample and thus analyze a biological response. Comparison of standard test samples over time provides an estimate of instrument stability for quality control. However, application of statistical methods of distribution comparison in flow cytometry is difficult owing to instrument noise and the complex shape of intensity distributions. We applied quadratic form (QF) as a mathematical metric for comparison of flow cytometry histograms. QF operates on histograms as vectors and calculates the total distance in an interbin manner using a matrix of distances between single histogram bins. Euclidean interbin distance and histograms normalized to unity were used. Critical values corresponding to 95% significance level were calculated using Monte-Carlo simulation and single-maximum Gaussian distributions populated with several numbers of events. The QF statistic was then validated for non-Gaussian single-maximum distributions and multiple-maxima distributions. We determined that the critical values for Gaussian distributions depended on standard deviations and number of events in the compared histograms. A simple empirical function was constructed to characterize this dependence. Furthermore, it was verified that critical values (corresponding to 95% significance) for non-Gaussian histograms were similar to values for the Gaussian histograms characterized by the same standard deviation. We applied the QF statistic to estimate the differences between histograms of DNA content (ploidy) in cells of old and young leaf tissue of Brassica campestris. Furthermore, we quantified differences in fluorescence intensity in immunostaining of human lymphocytes. Quadratic form (QF) provides a true (mathematical) metric for estimation of distance between flow cytometry histograms of arbitrary shape. QF can be applied as a statistical test for estimation of significance of the distance measure. The respective critical values depend only on the number of events and standard deviations of compared histograms and are not affected by distribution shape. Therefore, applications of QF do not require assumptions concerning distribution shape and can be easily implemented in practice. This notion was confirmed using empirical distributions of DNA content in plant tissue and distributions of immunofluorescence in human cells.",
        annote = "Bernas, Tytus Asem, Elikplimi K Robinson, J Paul Rajwa, Bartek Comparative Study United States Cytometry. Part A : the journal of the International Society for Analytical Cytology Cytometry A. 2008 Aug;73(8):715-26.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18561196"
}

@article{59,
        author = "M. J. Boedigheimer and J. Ferbas",
        title = "Mixture modeling approach to flow cytometry data",
        journal = "Cytometry A",
        pages = "421-9",
        volume = "73",
        number = "5",
        edition = "2008/04/03",
        year = "2008",
        month = "may",
        abstract = "Flow Cytometry has become a mainstay technique for measuring fluorescent and physical attributes of single cells in a suspended mixture. These data are reduced during analysis using a manual or semiautomated process of gating. Despite the need to gate data for traditional analyses, it is well recognized that analyst-to-analyst variability can impact the dataset. Moreover, cells of interest can be inadvertently excluded from the gate, and relationships between collected variables may go unappreciated because they were not included in the original analysis plan. A multivariate non-gating technique was developed and implemented that accomplished the same goal as traditional gating while eliminating many weaknesses. The procedure was validated against traditional gating for analysis of circulating B cells in normal donors (n = 20) and persons with Systemic Lupus Erythematosus (n = 42). The method recapitulated relationships in the dataset while providing for an automated and objective assessment of the data. Flow cytometry analyses are amenable to automated analytical techniques that are not predicated on discrete operator-generated gates. Such alternative approaches can remove subjectivity in data analysis, improve efficiency and may ultimately enable construction of large bioinformatics data systems for more sophisticated approaches to hypothesis testing.",
        annote = "Boedigheimer, Michael J Ferbas, John Comparative Study Research Support, Non-U.S. Gov't United States Cytometry. Part A : the journal of the International Society for Analytical Cytology Cytometry A. 2008 May;73(5):421-9.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18383311"
}

@article{Borowitz1993,
        author = "M. J. Borowitz and K. L. Guenther and K. E. Shults and G. T. Stelzer",
        title = "Immunophenotyping of acute leukemia by flow cytometric analysis. Use of CD45 and right-angle light scatter to gate on leukemic blasts in three-color analysis",
        journal = "Am J Clin Pathol",
        pages = "534-40",
        volume = "100",
        number = "5",
        edition = "1993/11/01",
        year = "1993",
        month = "Nov",
        abstract = "This article describes a procedure for performing routine three-color flow cytometric analysis for acute leukemia on lysed whole bone marrow preparations. This technique uses the combination of CD45 intensity and right-angle light scatter (RALS) to distinguish leukemic cells from normal lymphocytes, monocytes, neutrophils, eosinophils, and nucleated red blood cells. On this display, leukemic cells occupy a unique blast region characterized by intermediate CD45 density and low RALS, which, in normal marrows, contains less than 5% of the total cells. This approach was applied to 39 cases of acute leukemia and 8 cases of myelodysplasia or myeloproliferative disorders. The estimate of blasts by flow cytometric analysis was correlated highly with morphologic leukemic cell counts over a wide range. Moreover, the pattern seen on the CD45-RALS display was different for different French-American-British subtypes of leukemia, suggesting that this pattern might be useful for categorization. When CD45-peridin chlorophyll alpha protein was combined with other pairs of fluorescein isothiocyanate- and phycoerythrin-conjugated reagents, it was possible to set an analysis window on the leukemic blasts and display dual-parameter (ie, green vs. red fluorescence) data regarding expression of two additional markers on the leukemic population. This gating strategy was superior to traditional forward-angle versus RALS displays in that it did a better job of isolating the leukemic cells analytically.",
        annote = "Borowitz, M J Guenther, K L Shults, K E Stelzer, G T United states American journal of clinical pathology Am J Clin Pathol. 1993 Nov;100(5):534-40.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=8249893"
}

@article{1501,
        author = "C. Chan and F. Feng and J. Ottinger and D. Foster and M. West and T. B. Kepler",
        title = "Statistical mixture modeling for cell subtype identification in flow cytometry",
        journal = "Cytometry A",
        pages = "693-701",
        volume = "73",
        number = "8",
        edition = "2008/05/23",
        year = "2008",
        month = "Aug",
        abstract = "Statistical mixture modeling provides an opportunity for automated identification and resolution of cell subtypes in flow cytometric data. The configuration of cells as represented by multiple markers simultaneously can be modeled arbitrarily well as a mixture of Gaussian distributions in the dimension of the number of markers. Cellular subtypes may be related to one or multiple components of such mixtures, and fitted mixture models can be evaluated in the full set of markers as an alternative, or adjunct, to traditional subjective gating methods that rely on choosing one or two dimensions. Four color flow data from human blood cells labeled with FITC-conjugated anti-CD3, PE-conjugated anti-CD8, PE-Cy5-conjugated anti-CD4, and APC-conjugated anti-CD19 Abs was acquired on a FACSCalibur. Cells from four murine cell lines, JAWS II, RAW 264.7, CTLL-2, and A20, were also stained with FITC-conjugated anti-CD11c, PE-conjugated anti-CD11b, PE-Cy5-conjugated anti-CD8a, and PE-Cy7-conjugated-CD45R/B220 Abs, respectively, and single color flow data were collected on an LSRII. The data were fitted with a mixture of multivariate Gaussians using standard Bayesian statistical approaches and Markov chain Monte Carlo computations. Statistical mixture models were able to identify and purify major cell subsets in human peripheral blood, using an automated process that can be generalized to an arbitrary number of markers. Validation against both traditional expert gating and synthetic mixtures of murine cell lines with known mixing proportions was also performed. This article describes the studies of statistical mixture modeling of flow cytometric data, and demonstrates their utility in examples with four-color flow data from human peripheral blood samples and synthetic mixtures of murine cell lines.",
        annote = "Chan, Cliburn Feng, Feng Ottinger, Janet Foster, David West, Mike Kepler, Thomas B 1P30 AI 64518/AI/NIAID NIH HHS/United States HHSN268200500019C/PHS HHS/United States UL1 RR024128/RR/NCRR NIH HHS/United States Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S. United States Cytometry. Part A : the journal of the International Society for Analytical Cytology Cytometry A. 2008 Aug;73(8):693-701.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18496851"
}

@article{Chattopadhyay2008,
        author = "P. K. Chattopadhyay and C. M. Hogerkorp and M. Roederer",
        title = "A chromatic explosion: the development and future of multiparameter flow cytometry",
        journal = "Immunology",
        pages = "441-9",
        volume = "125",
        number = "4",
        edition = "2009/01/13",
        year = "2008",
        month = "Dec",
        abstract = "Multiparameter flow cytometry has matured tremendously since the 1990s, giving rise to a technology that allows us to study the immune system in unprecedented detail. In this article, we review the development of hardware, reagents, and data analysis tools for multiparameter flow cytometry and discuss future advances in the field. Finally, we highlight new applications that use this technology to reveal previously unappreciated aspects of cell biology and immunity.",
        annote = "Chattopadhyay, Pratip K Hogerkorp, Carl-Magnus Roederer, Mario Review England Immunology Immunology. 2008 Dec;125(4):441-9.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19137647"
}

@article{Chattopadhyay2006,
        author = "P. K. Chattopadhyay and D. A. Price and T. F. Harper and M. R. Betts and J. Yu and E. Gostick and S. P. Perfetto and P. Goepfert and R. A. Koup and S. C. {De Rosa} and M. P. Bruchez and M. Roederer",
        title = "Quantum dot semiconductor nanocrystals for immunophenotyping by polychromatic flow cytometry",
        journal = "Nat Med",
        pages = "972-7",
        volume = "12",
        number = "8",
        edition = "2006/07/25",
        year = "2006",
        month = "Aug",
        abstract = "Immune responses arise from a wide variety of cells expressing unique combinations of multiple cell-surface proteins. Detailed characterization is hampered, however, by limitations in available probes and instrumentation. Here, we use the unique spectral properties of semiconductor nanocrystals (quantum dots) to extend the capabilities of polychromatic flow cytometry to resolve 17 fluorescence emissions. We show the need for this power by analyzing, in detail, the phenotype of multiple antigen-specific T-cell populations, revealing variations within complex phenotypic patterns that would otherwise remain obscure. For example, T cells specific for distinct epitopes from one pathogen, and even those specific for the same epitope, can have markedly different phenotypes. The technology we describe, encompassing the detection of eight quantum dots in conjunction with conventional fluorophores, should expand the horizons of flow cytometry, as well as our ability to characterize the intricacies of both adaptive and innate cellular immune responses.",
        annote = "Chattopadhyay, Pratip K Price, David A Harper, Theresa F Betts, Michael R Yu, Joanne Gostick, Emma Perfetto, Stephen P Goepfert, Paul Koup, Richard A De Rosa, Stephen C Bruchez, Marcel P Roederer, Mario R01 EB 000364/EB/NIBIB NIH HHS/United States Research Support, N.I.H., Extramural Research Support, N.I.H., Intramural Research Support, U.S. Gov't, Non-P.H.S. Technical Report United States Nature medicine Nat Med. 2006 Aug;12(8):972-7. Epub 2006 Jul 23.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16862156"
}

@article{1301,
        author = "C. Cortes and V. Vapnik",
        title = "Support-Vector Networks",
        journal = "Machine Learning",
        pages = "273-297",
        volume = "20",
        number = "3",
        year = "1995",
        month = "Sep",
        issn = "0885-6125",
        abstract = "The support-vector network is a new learning machine for two-group classification problems. The machine conceptually implements the following idea: input vectors are non-linearly mapped to a very high-dimension feature space. In this feature space a linear decision surface is constructed. Special properties of the decision surface ensures high generalization ability of the learning machine. The idea behind the support-vector network was previously implemented for the restricted case where the training data can be separated without errors. We here extend this result to non-separable training data. High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated. We also compare the performance of the support-vector network to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.",
        annote = "Rx354 Times Cited:2060 Cited References Count:14",
        uri = "<Go to ISI>://A1995RX35400003"
}

@article{1646,
        author = "W. Cui and W. Ma and Q. Lin",
        title = "[CD45-gating for flow cytometric immunophenotyping of leukemia]",
        journal = "Zhongguo Yi Xue Ke Xue Yuan Xue Bao",
        pages = "199-203",
        volume = "22",
        number = "2",
        edition = "2003/08/09",
        year = "2000",
        month = "Apr",
        abstract = "OBJECTIVE: To establish a reliable and rapid multiparameter flow cytometric approach for leukemia immunophenotyping. METHODS: Leukemia blast cells which exhibit a character of low CD45 expression and low side scatter density are easily recognized by CD45-SSC gating, we measured 46 patients and 3 normal persons of immunophenotyping by this gating method as well as traditional forwardscatter-side scatter (FSC-SSC) gating method. RESULTS: 5 of 46 immunophenotypic results from FSC-SSC gating showed false diagnosis, which were corrected by CD45-SSC gating. Further, immunophenotypic mapping of 46 different acute leukemia were obtained by CD45-SSC gating and three-color staining, The expression of related antigen could be readily observed. CONCLUSIONS: CD45-SSC gating is a reliable and easy method to subclassify leukemia. Three-color staining, which is able to analyze the expression among two related antigens, not only be helpful in leukemia diagnosis but also contribute to study the occurrence, development and prognosis of diseases.",
        annote = "Cui, W Ma, W Lin, Q English Abstract China Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2000 Apr;22(2):199-203.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12903529"
}

@misc{1303,
        author = "Evgenia Dimitriadou and Kurt Hornik and Friedrich Leisch and David Meyer and Andreas Weingessel",
        title = "e1071: Misc Functions of the Department of Statistics",
        year = "2008",
        uri = "http://cran.r-project.org/src/contrib/e1071_1.5-19.tar.gz"
}

@misc{1258,
        author = "B. Ellis and P. Haaland and F. Hahne and N. {Le Meur} and N. Gopalakrishnan",
        title = "flowCore: Basic structures for flow cytometry data",
        year = "2009",
        uri = "http://bioconductor.org/packages/2.3/bioc/html/flowCore.html"
}

@article{1225,
        author = "W. G. Finn",
        title = {Diagnostic pathology and laboratory medicine in the age of "omics": a paper from the 2006 William Beaumont Hospital Symposium on Molecular Pathology},
        journal = "J Mol Diagn",
        pages = "431-6",
        volume = "9",
        number = "4",
        edition = "2007/07/27",
        year = "2007",
        month = "Sep",
        abstract = "Functional genomics and proteomics involve the simultaneous analysis of hundreds or thousands of expressed genes or proteins and have spawned the modern discipline of computational biology. Novel informatic applications, including sophisticated dimensionality reduction strategies and cancer outlier profile analysis, can distill clinically exploitable biomarkers from enormous experimental datasets. Diagnostic pathologists are now charged with translating the knowledge generated by the omics revolution into clinical practice. Food and Drug Administration-approved proprietary testing platforms based on microarray technologies already exist and will expand greatly in the coming years. However, for diagnostic pathology, the greatest promise of the omics age resides in the explosion in information technology (IT). IT applications allow for the digitization of histological slides, transforming them into minable data and enabling content-based searching and archiving of histological materials. IT will also allow for the optimization of existing (and often underused) clinical laboratory technologies such as flow cytometry and high-throughput core laboratory functions. The state of pathology practice does not always keep up with the pace of technological advancement. However, to use fully the potential of these emerging technologies for the benefit of patients, pathologists and clinical scientists must embrace the changes and transformational advances that will characterize this new era.",
        annote = "Finn, William G Review United States The Journal of molecular diagnostics : JMD J Mol Diagn. 2007 Sep;9(4):431-6. Epub 2007 Jul 25.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17652635"
}

@article{Gates2009,
        author = "I. V. Gates and Y. Zhang and C. Shambaugh and M. A. Bauman and C. Tan and J. L. Bodmer",
        title = "Quantitative measurement of Varicella Zoster Virus infection using semi-automated flow cytometry",
        journal = "Appl Environ Microbiol",
        edition = "2009/02/10",
        year = "2009",
        month = "Feb 5",
        abstract = "Varicella Zoster Virus (VZV, HHV-3) is the etiological cause of chickenpox and, upon reactivation from latency, zoster. Currently, vaccines are available to prevent both diseases effectively. A critical requirement to manufacturing of safe and potent vaccines is the measurement of the biological activity to ensure proper dosing and efficacy, while minimizing potentially harmful secondary effects induced by immunization. In the case of live virus-containing vaccines, such as VZV-containing vaccines, biological activity is determined using an infectivity assay in a susceptible cellular host in vitro. Infectivity measurements generally rely on the enumeration of plaques by visual inspection of an infected cell monolayer. These plaque assays are generally very tedious, labor-intensive, have modest throughput and high associated variability. In this study, we have developed a flow cytometry assay to measure the infectivity of the attenuated vaccine strain (Oka/Merck) of VZV in MRC-5 cells with improved throughput. The assay is performed in 96-well tissue culture microtiter plates and is based on the detection and quantification of infected cells expressing VZV glycoproteins on their surface. Multiple assay parameters have been investigated, including specificity, limit of detection (LOD), limit of quantification (LOQ), range of linear response, signal to noise ratio and precision. This novel assay appears to be in good concordance with the classical plaque assay results and therefore provides a viable, higher throughput alternative to the plaque assay.",
        annote = "Journal article Applied and environmental microbiology Appl Environ Microbiol. 2009 Feb 5.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19201967"
}

@article{1659,
        author = "R. Gelman and C. Wilkening",
        title = "Analyses of quality assessment studies using CD45 for gating lymphocytes for CD3(+)4(+)%",
        journal = "Cytometry",
        pages = "1-4",
        volume = "42",
        number = "1",
        edition = "2000/02/19",
        year = "2000",
        month = "Feb 15",
        abstract = "BACKGROUND: The purpose of this study was to assess whether laboratories which do not use CD45 for gating lymphocytes with three- (or four-) color flow cytometry (non-CD45 laboratories) for CD3(+)4(+)% and CD3(+)8(+)% do worse on quality assessment (QA) studies than laboratories which do use CD45 (CD45 laboratories). METHODS: Data came from blood specimens donated by 62 donors (50 HIV-positive) assayed over 2 years (November, 1996-October, 1998) by 35 laboratories in the NIAID DAIDS Flow Cytometry QA Program. RESULTS: Non-CD45 laboratories were significantly more likely to be classified as having unacceptable inter-laboratory results (far from the group median) than CD45 laboratories (5.6% vs 1.5%, P = 0.005 for CD3(+)4(+)%; 10.4% vs 5.0%, P = 0.007 for CD3(+)8(+)%). The intra-laboratory range of results on blinded replicates was significantly more likely to be deemed unacceptable (range >4%) in non-CD45 laboratories than in CD45 laboratories for CD3(+)8(+)% (14. 5% vs 3.5%, P = 0.002) but not for CD3(+)4(+)% (2.6% vs 1.5%, P = 0. 62). These differences in favor of CD45 gating were observed even though the non-CD45 laboratories had been doing three-color flow cytometry in the QA program significantly longer (P = 0.05) than the CD45 laboratories, and so would be expected to have fewer problems with the assay. CONCLUSIONS: Laboratories which choose to use a single CD3/CD4/CD8 tube for immunophenotyping may be sacrificing both accuracy and reproducibility.",
        annote = "Gelman, R Wilkening, C AI38855/AI/NIAID NIH HHS/United States AI41110/AI/NIAID NIH HHS/United States AI45175/AI/NIAID NIH HHS/United States Comparative Study Research Support, U.S. Gov't, P.H.S. United states Cytometry Cytometry. 2000 Feb 15;42(1):1-4.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=10679736"
}

@article{115,
        author = "R. C. Gentleman and V. J. Carey and D. M. Bates and B. Bolstad and M. Dettling and S. Dudoit and B. Ellis and L. Gautier and Y. Ge and J. Gentry and K. Hornik and T. Hothorn and W. Huber and S. Iacus and R. Irizarry and F. Leisch and C. Li and M. Maechler and A. J. Rossini and G. Sawitzki and C. Smith and G. Smyth and L. Tierney and J. Y. Yang and J. Zhang",
        title = "Bioconductor: open software development for computational biology and bioinformatics",
        journal = "Genome Biol",
        pages = "R80",
        volume = "5",
        number = "10",
        edition = "2004/10/06",
        year = "2004",
        abstract = "The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples.",
        annote = "Gentleman, Robert C Carey, Vincent J Bates, Douglas M Bolstad, Ben Dettling, Marcel Dudoit, Sandrine Ellis, Byron Gautier, Laurent Ge, Yongchao Gentry, Jeff Hornik, Kurt Hothorn, Torsten Huber, Wolfgang Iacus, Stefano Irizarry, Rafael Leisch, Friedrich Li, Cheng Maechler, Martin Rossini, Anthony J Sawitzki, Gunther Smith, Colin Smyth, Gordon Tierney, Luke Yang, Jean Y H Zhang, Jianhua England Genome biology Genome Biol. 2004;5(10):R80. Epub 2004 Sep 15.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15461798"
}

@article{1231,
        author = "F. Hahne and D. Arlt and M. Sauermann and M. Majety and A. Poustka and S. Wiemann and W. Huber",
        title = "Statistical methods and software for the analysis of highthroughput reverse genetic assays using flow cytometry readouts",
        journal = "Genome Biol",
        pages = "R77",
        volume = "7",
        number = "8",
        edition = "2006/08/19",
        year = "2006",
        abstract = "Highthroughput cell-based assays with flow cytometric readout provide a powerful technique for identifying components of biologic pathways and their interactors. Interpretation of these large datasets requires effective computational methods. We present a new approach that includes data pre-processing, visualization, quality assessment, and statistical inference. The software is freely available in the Bioconductor package prada. The method permits analysis of large screens to detect the effects of molecular interventions in cellular systems.",
        annote = "Hahne, Florian Arlt, Dorit Sauermann, Mamatha Majety, Meher Poustka, Annemarie Wiemann, Stefan Huber, Wolfgang Research Support, Non-U.S. Gov't England Genome biology Genome Biol. 2006;7(8):R77. Epub 2006 Aug 17.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16916453"
}

@article{Inokuma2007,
        author = "M. Inokuma and C. {dela Rosa} and C. Schmitt and P. Haaland and J. Siebert and D. Petry and M. Tang and M. A. Suni and S. A. Ghanekar and D. Gladding and J. F. Dunne and V. C. Maino and M. L. Disis and H. T. Maecker",
        title = "Functional T cell responses to tumor antigens in breast cancer patients have a distinct phenotype and cytokine signature",
        journal = "J Immunol",
        pages = "2627-33",
        volume = "179",
        number = "4",
        edition = "2007/08/07",
        year = "2007",
        month = "Aug 15",
        abstract = "The overall prevalence with which endogenous tumor Ags induce host T cell responses is unclear. Even when such responses are detected, they do not usually result in spontaneous remission of the cancer. We hypothesized that this might be associated with a predominant phenotype and/or cytokine profile of tumor-specific responses that is different from protective T cell responses to other chronic Ags, such as CMV. We detected significant T cell responses to CEA, HER-2/neu, and/or MAGE-A3 in 17 of 21 breast cancer patients naive to immunotherapy. The pattern of T cell cytokines produced in response to tumor-associated Ags (TAAs) in breast cancer patients was significantly different from that produced in response to CMV or influenza in the same patients. Specifically, there was a higher proportion of IL-2-producing CD8(+) T cells, and a lower proportion of IFN-gamma-producing CD4(+) and/or CD8(+) T cells responding to TAAs compared with CMV or influenza Ags. Finally, the phenotype of TAA-responsive CD8(+) T cells in breast cancer patients was almost completely CD28(+)CD45RA(-) (memory phenotype). CMV-responsive CD8(+) T cells in the same patients were broadly distributed among phenotypes, and contained a high proportion of terminal effector cells (CD27(-)CD28(-)CD45RA(+)) that were absent in the TAA responses. Taken together, these results suggest that TAA-responsive T cells are induced in breast cancer patients, but those T cells are phenotypically and functionally different from CMV- or influenza-responsive T cells. Immunotherapies directed against TAAs may need to alter these T cell signatures to be effective.",
        annote = "Inokuma, Margaret dela Rosa, Corazon Schmitt, Charles Haaland, Perry Siebert, Janet Petry, Douglas Tang, Mengxiang Suni, Maria A Ghanekar, Smita A Gladding, Daiva Dunne, John F Maino, Vernon C Disis, Mary L Maecker, Holden T U54 CA090818/CA/NCI NIH HHS/United States Clinical Trial Comparative Study Research Support, N.I.H., Extramural United States Journal of immunology (Baltimore, Md. : 1950) J Immunol. 2007 Aug 15;179(4):2627-33.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17675526"
}

@misc{Inokuma2008,
        author = "M. Inokuma and C. {dela Rosa} and C. Schmitt and P. Haaland and J. Siebert and D. Petry and M. Tang and M. A. Suni and S. A. Ghanekar and D. Gladding and J. F. Dunne and V. C. Maino and M. L. Disis and H. T. Maecker",
        booktitle = "96-well plate data deposited with Flow Informatics and Computational Cytometry Society website.",
        year = "2008",
        uri = "http://www.ficcs.org/software.html#Data_Files"
}

@article{Kelliher2005,
        author = "A. S. Kelliher and D. W. Parent and D. C. Anderson and M. E. Dorn and J. L. Hahn and S. Eapen and F. I. Preffer",
        title = "Novel use of the BD FACS SPA to automate custom monoclonal antibody panel preparations for immunophenotyping",
        journal = "Cytometry B Clin Cytom",
        pages = "40-5",
        volume = "66",
        number = "1",
        edition = "2005/05/27",
        year = "2005",
        month = "Jul",
        abstract = "BACKGROUND: The effective and accurate diagnosis of hematologic malignancies relies on flow cytometric immunophenotyping. Selected combinations of monoclonal antibodies (mAbs) arranged in multicolor panels allow for the accurate definition of normal and abnormal hematologic cell populations. The most time-consuming and crucial step in the staining process involves dispensing combinations of multiple mAbs into their appropriate staining tubes. This step is prone to error, requires concentration and accuracy, and is dependent on technologist experience.The Becton Dickinson BioScience (BD) FACS Sample Prep Assistant (SPA) is touted as a breakthrough in automated in vitro diagnostic sample preparation. The SPA is designed to automate BD MultiTESk and BD TriTest lyse/no-wash assays. However, because most cases in our laboratory require tedious application of unique four-color mAb cocktails for leukemia and lymphoma testing, we wondered whether the SPA would be helpful in accurately dispensing these mixtures. METHODS: The mAb panels were prepared by the SPA in two separate timed runs and on separate days. Eleven specimens (nine from patients and two from normal volunteers) were split and stained with four-color cocktails created by the SPA or manually. The percentage of positive (%P) cells and mean fluorescent intensity for each mAb pair were determined. These values were plotted against each other and correlation values were calculated. To quantitate timesaving in the laboratory, two technologists prepared individually the same mAb panels and were timed. RESULTS: The correlation between the two methods was high; r(2) was 0.988 for 158 %P antigen pairs; no bias between the manual and robotic methods was detected with the Wilcoxon rank test. Bland-Altman analysis indicated no obvious relation between the difference and the mean of %P cells, suggesting that the SPA successfully dispensed antibodies for leukemia/lymphoma panels. The two methods may be interchangeable, although the limited sample size prohibits this conclusion from Bland-Altman statistics alone. In addition, one possible error was detected in the SPA-prepared panels. The SPA averaged 65 min/run, the experienced technologist 12.95 min/run, and the inexperienced technologist 54.9 min/run. CONCLUSIONS: SPA dispensing time was twice the average manual dispensing time; however, SPA use was completely automated and freed the technologist to perform other tasks. SPA use permitted preemptive preparation of mAb panels and thus streamlined processing; however, the cost of the assay and the amount of reagent waste increased. It is certain that software modifications by BD could decrease the SPA reagent dispense time and decrease the cost associated with reagent waste when the SPA is used in this novel fashion.",
        annote = "Kelliher, Abigail S Parent, David W Anderson, David C Dorn, Michelle E Hahn, Jessica L Eapen, Sara Preffer, Frederic I Comparative Study United States Cytometry. Part B, Clinical cytometry Cytometry B Clin Cytom. 2005 Jul;66(1):40-5.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15918157"
}

@article{1318,
        author = "K. I. Kim and M. A. {van de Wiel}",
        title = "Effects of dependence in high-dimensional multiple testing problems",
        journal = "BMC Bioinformatics",
        pages = "114",
        volume = "9",
        edition = "2008/02/27",
        year = "2008",
        abstract = "BACKGROUND: We consider effects of dependence among variables of high-dimensional data in multiple hypothesis testing problems, in particular the False Discovery Rate (FDR) control procedures. Recent simulation studies consider only simple correlation structures among variables, which is hardly inspired by real data features. Our aim is to systematically study effects of several network features like sparsity and correlation strength by imposing dependence structures among variables using random correlation matrices. RESULTS: We study the robustness against dependence of several FDR procedures that are popular in microarray studies, such as Benjamin-Hochberg FDR, Storey's q-value, SAM and resampling based FDR procedures. False Non-discovery Rates and estimates of the number of null hypotheses are computed from those methods and compared. Our simulation study shows that methods such as SAM and the q-value do not adequately control the FDR to the level claimed under dependence conditions. On the other hand, the adaptive Benjamini-Hochberg procedure seems to be most robust while remaining conservative. Finally, the estimates of the number of true null hypotheses under various dependence conditions are variable. CONCLUSION: We discuss a new method for efficient guided simulation of dependent data, which satisfy imposed network constraints as conditional independence structures. Our simulation set-up allows for a structural study of the effect of dependencies on multiple testing criterions and is useful for testing a potentially new method on pi0 or FDR estimation in a dependency context.",
        annote = "Kim, Kyung In van de Wiel, Mark A Comparative Study Evaluation Studies England BMC bioinformatics BMC Bioinformatics. 2008 Feb 25;9:114.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18298808"
}

@article{1293,
        author = "Y. Klipper-Aurbach and M. Wasserman and N. Braunspiegel-Weintrob and D. Borstein and S. Peleg and S. Assa and M. Karp and Y. Benjamini and Y. Hochberg and Z. Laron",
        title = "Mathematical formulae for the prediction of the residual beta cell function during the first two years of disease in children and adolescents with insulin-dependent diabetes mellitus",
        journal = "Med Hypotheses",
        pages = "486-90",
        volume = "45",
        number = "5",
        edition = "1995/11/01",
        year = "1995",
        month = "Nov",
        abstract = "On the basis of a retrospective study of 71 children followed for 24 months after diagnosis of type I insulin dependent diabetes a fitted mathematical model was constructed for the prediction of the course of beta cell function from the time of diagnosis. Two equations were derived, one for the maximal basal (B-max) and the other for the maximal i.v. glucagon stimulated peak C-peptide (P-max) levels reached during the remission period. The prognostic variables selected for analysis were: peak C-peptide levels at diagnosis (Po), age sex, degree of obesity, pubertal rating, the presence of islet cell antibodies (ICA) and levels of GHb. Multivariate analysis of the data showed that Po (p = 0.0006), puberty (p = 0.041). obesity (p = 0.0021), sex (p = 0.031), ICA (p = 0.0045) and GHb(p = 0.0066) significantly contributed to the prediction formula obtained for B-max whereas the contribution of the above variables for P-max were: Po (p = 0.0019), puberty (p = 0.0187), obesity (p = 0.0058), sex (p = 0.0598), ICA (p = 0.0187) and GHb (p = 0.0027). The residuals of the observed values from the values fitted by the predicted equations served to define two separate groups demonstrating distinct differences in the natural course of beta cell function in type I diabetes. This fitted model may thus be useful in distinguishing between newly diagnosed young patients who will undergo remission, requiring lower insulin doses, and those who have little chance for remission. It might also be helpful in the selection of patients most likely to benefit from immunosuppression or modulation, to maximize the benefit to risk ratio for such patients.",
        annote = "Klipper-Aurbach, Y Wasserman, M Braunspiegel-Weintrob, N Borstein, D Peleg, S Assa, S Karp, M Benjamini, Y Hochberg, Y Laron, Z Research Support, Non-U.S. Gov't England Medical hypotheses Med Hypotheses. 1995 Nov;45(5):486-90.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=8748093"
}

@article{1662,
        author = "F. Lacombe and F. Durrieu and A. Briais and P. Dumain and F. Belloc and E. Bascans and J. Reiffers and M. R. Boisseau and P. Bernard",
        title = "Flow cytometry CD45 gating for immunophenotyping of acute myeloid leukemia",
        journal = "Leukemia",
        pages = "1878-86",
        volume = "11",
        number = "11",
        edition = "1997/11/22",
        year = "1997",
        month = "Nov",
        abstract = "A flow cytometry method has been introduced into the routine investigation of whole bone marrow samples following red blood cell lysis on the basis of a primary CD45/side scatter (SSC) gating procedure. Blast cells were first identified by CD45/SSC gating in 74 cases of acute myeloid leukemia (AML) and the results were compared to a conventional FSC/SSC gating procedure and to MGG-staining smears. The percentages of blast cells in these samples as defined by the morphological analysis of MGG smears correlated better with the values determined by CD45/SSC gating (r = 0.94) than with the blast cell counts recorded with FSC/SSC gating (r = 0.76). These findings were not surprising because while CD45 expression was regularly lower on leukemic blasts than on normal lymphoid and monocytic cells, the FCS/SSC characteristics of these populations were overlapping. In 53 samples, the blast cell populations were also analyzed with a panel of FITC-conjugated monoclonal antibodies that were utilized in double labeling with CD45-PE. We show that the CD45/SSC gating procedure improved phenotypic determination of the blast cells in three ways: (1) by discriminating between leukemic blast cells and residual normal cells; (2) by excluding normal cells from the phenotypic analysis of leukemic blast cells; and (3) by identifying blast cell heterogeneity in many cases of leukemia on the basis of different CD45 display. Moreover, this immunophenotyping procedure on whole bone marrow samples also allowed an efficient discrimination between the various cell lineages and facilitated the analysis of leukemic blasts present in low proportions.",
        annote = "Lacombe, F Durrieu, F Briais, A Dumain, P Belloc, F Bascans, E Reiffers, J Boisseau, M R Bernard, P England Leukemia : official journal of the Leukemia Society of America, Leukemia Research Fund, U.K Leukemia. 1997 Nov;11(11):1878-86.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=9369421"
}

@article{108,
        author = "J. A. Lee and J. Spidlen and K. Boyce and J. Cai and N. Crosbie and M. Dalphin and J. Furlong and M. Gasparetto and M. Goldberg and E. M. Goralczyk and B. Hyun and K. Jansen and T. Kollmann and M. Kong and R. Leif and S. McWeeney and T. D. Moloshok and W. Moore and G. Nolan and J. Nolan and J. Nikolich-Zugich and D. Parrish and B. Purcell and Y. Qian and B. Selvaraj and C. Smith and O. Tchuvatkina and A. Wertheimer and P. Wilkinson and C. Wilson and J. Wood and R. Zigon and R. H. Scheuermann and R. R. Brinkman",
        title = "MIFlowCyt: the minimum information about a Flow Cytometry Experiment",
        journal = "Cytometry A",
        pages = "926-30",
        volume = "73",
        number = "10",
        edition = "2008/08/30",
        year = "2008",
        month = "Oct",
        abstract = "A fundamental tenet of scientific research is that published results are open to independent validation and refutation. Minimum data standards aid data providers, users, and publishers by providing a specification of what is required to unambiguously interpret experimental findings. Here, we present the Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) standard, stating the minimum information required to report flow cytometry (FCM) experiments. We brought together a cross-disciplinary international collaborative group of bioinformaticians, computational statisticians, software developers, instrument manufacturers, and clinical and basic research scientists to develop the standard. The standard was subsequently vetted by the International Society for Advancement of Cytometry (ISAC) Data Standards Task Force, Standards Committee, membership, and Council. The MIFlowCyt standard includes recommendations about descriptions of the specimens and reagents included in the FCM experiment, the configuration of the instrument used to perform the assays, and the data processing approaches used to interpret the primary output data. MIFlowCyt has been adopted as a standard by ISAC, representing the FCM scientific community including scientists as well as software and hardware manufacturers. Adoptionof MIFlowCyt by the scientific and publishing communities will facilitate third-party understanding and reuse of FCM data.",
        annote = "Lee, Jamie A Spidlen, Josef Boyce, Keith Cai, Jennifer Crosbie, Nicholas Dalphin, Mark Furlong, Jeff Gasparetto, Maura Goldberg, Michael Goralczyk, Elizabeth M Hyun, Bill Jansen, Kirstin Kollmann, Tobias Kong, Megan Leif, Robert McWeeney, Shannon Moloshok, Thomas D Moore, Wayne Nolan, Garry Nolan, John Nikolich-Zugich, Janko Parrish, David Purcell, Barclay Qian, Yu Selvaraj, Biruntha Smith, Clayton Tchuvatkina, Olga Wertheimer, Anne Wilkinson, Peter Wilson, Christopher Wood, James Zigon, Robert International Society for Advancement of Cytometry Data Standards Task Force Scheuermann, Richard H Brinkman, Ryan R AI40076/AI/NIAID NIH HHS/United States EB005034/EB/NIBIB NIH HHS/United States Research Support, N.I.H., Extramural United States Cytometry. Part A : the journal of the International Society for Analytical Cytology Cytometry A. 2008 Oct;73(10):926-30.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18752282"
}

@article{111,
        author = "K. Lo and R. R. Brinkman and R. Gottardo",
        title = "Automated gating of flow cytometry data via robust model-based clustering",
        journal = "Cytometry A",
        pages = "321-32",
        volume = "73",
        number = "4",
        edition = "2008/03/01",
        year = "2008",
        month = "Apr",
        abstract = "The capability of flow cytometry to offer rapid quantification of multidimensional characteristics for millions of cells has made this technology indispensable for health research, medical diagnosis, and treatment. However, the lack of statistical and bioinformatics tools to parallel recent high-throughput technological advancements has hindered this technology from reaching its full potential. We propose a flexible statistical model-based clustering approach for identifying cell populations in flow cytometry data based on t-mixture models with a Box-Cox transformation. This approach generalizes the popular Gaussian mixture models to account for outliers and allow for nonelliptical clusters. We describe an Expectation-Maximization (EM) algorithm to simultaneously handle parameter estimation and transformation selection. Using two publicly available datasets, we demonstrate that our proposed methodology provides enough flexibility and robustness to mimic manual gating results performed by an expert researcher. In addition, we present results from a simulation study, which show that this new clustering framework gives better results in terms of robustness to model misspecification and estimation of the number of clusters, compared to the popular mixture models. The proposed clustering methodology is well adapted to automated analysis of flow cytometry data. It tends to give more reproducible results, and helps reduce the significant subjectivity and human time cost encountered in manual gating analysis.",
        annote = "Lo, Kenneth Brinkman, Ryan Remy Gottardo, Raphael Research Support, Non-U.S. Gov't United States Cytometry. Part A : the journal of the International Society for Analytical Cytology Cytometry A. 2008 Apr;73(4):321-32.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18307272"
}

@article{1648,
        author = "R. J. Lock and P. F. Virgo and R. S. Evely",
        title = "Pitfalls of CD45 gating strategies in leukaemia immunophenotyping",
        journal = "Clin Lab Haematol",
        pages = "67",
        volume = "25",
        number = "1",
        edition = "2003/01/25",
        year = "2003",
        month = "Feb",
        annote = "Lock, R J Virgo, P F Evely, R S Comment Letter England Clinical and laboratory haematology Clin Lab Haematol. 2003 Feb;25(1):67.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12542446"
}

@article{1644,
        author = "S. H. Maljaei and E. Kermani I. Asvadi and E. Ziaei J. Eivazi and A. Nikanfar and J. Vaez",
        title = "Usefulness of CD45 density in the diagnosis of B-cell chronic lymphoproliferative disorders",
        journal = "Indian J Med Sci",
        pages = "187-94",
        volume = "59",
        number = "5",
        edition = "2005/06/30",
        year = "2005",
        month = "may",
        abstract = "BACKGROUND: Although many B-cell chronic lymphoproliferative disorders (BCLPDs) including B-cell chronic lymphocytic leukemia (B-CLL) have characteristic clinical and biological features, the overlapping morphologic and immunophenotypic profiles of various BCLPDs, is still the main problem. AIM: Our aim was to evaluate the usefulness of CD45 expression in the immunological classification of BCLPDs. SETTING AND DESIGN: A prospective study was set in a university hospital to investigate the CD45 intensity, particularly in B-CLL. MATERIALS AND METHODS: The expression of CD45 in 37 patients with BCLPD including typical B-CLL (Group I), atypical B-CLL and CLL/PLL (II), and hairy cell leukemia (HCL), B-prolymphocytic leukemia (B-PLL), and B-non Hodgkin's lymphoma (B-NHL) as non-CLL BCLPDs (III) and in eight healthy age matched controls (IV) was quantitatively compared by flow cytometric CD45/RALS gating strategy. Statistical analysis: The mean, median, and peak channel scores of CD45 obtained for the four groups were compared using one-way analysis of variance test. A P value RESULTS: Lower CD45 density is associated highly with typical CLL and differences between typical CLL and other groups were significant (P< 0.001, 0.001, and 0.001). Non-CLL cases had significantly brighter CD45 expression than atypical CLL (P=0.014). No differences were found between normal lymphocytes and non-CLL BCLPD cases. CONCLUSIONS: CD45 is a useful marker, to discriminate the typical CLL from the non-CLL BCLPD and from atypical CLL.",
        annote = "Maljaei, Seyyed Hadi Asvadi-E-Kermani, Iraj Eivazi-E-Ziaei, Jamal Nikanfar, Alireza Vaez, Jalil Comparative Study India Indian journal of medical sciences Indian J Med Sci. 2005 May;59(5):187-94.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15985726"
}

@article{McCoy2002,
        author = "J. P., McCoy Jr.",
        title = "Basic principles of flow cytometry",
        journal = "Hematol Oncol Clin North Am",
        pages = "229-43",
        volume = "16",
        number = "2",
        edition = "2002/07/04",
        year = "2002",
        month = "Apr",
        abstract = "Although the basic principles of flow cytometry have changed little in the past quarter century, the applications of this technology have evolved substantially. As in the past, cytometers interrogate individual cells or particles in a stream with a laser as the cells move past a set of stationary detectors. Increasingly, more colors of fluorescence are being detected by cytometers, faster analysis and sorting rates are becoming possible, cytometers capable of multidirectional sorting are being marketed, and more reagents are becoming available for a wide variety of applications. Furthermore, flow cytometry has not stopped evolving. The development of narrow spectrum flourescent probes, the integration of molecular biologic techniques with flow cytometry, and the evaluation of cell-free markers such as cytokines will be key components in the continuing evolution of flow cytometry.",
        annote = "McCoy, J Philip Jr Review United States Hematology/oncology clinics of North America Hematol Oncol Clin North Am. 2002 Apr;16(2):229-43.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12094472"
}

@article{Murthi2005,
        author = "S. Murthi and S. Sankaranarayanan and B. Xia and G. M. Lambert and J. J. Rodriguez and D. W. Galbraith",
        title = "Performance analysis of a dual-buffer architecture for digital flow cytometry",
        journal = "Cytometry A",
        pages = "109-18",
        volume = "66",
        number = "2",
        edition = "2005/06/24",
        year = "2005",
        month = "Aug",
        abstract = "BACKGROUND: Most current commercial flow cytometers employ analog circuitry to provide feature values describing the pulse waveforms produced from suspended cells and particles. This restricts the type of features that can be extracted (typically pulse height, width, and integral) and consequently places a limit on classification performance. In previous work, we described a first-generation digital data acquisition and processing system that was used to demonstrate the classification advantages provided by the extraction of additional waveform features. An improved version of the system is discussed in this paper, focusing on dual-buffering to ensure increased pulse capture. A mathematical model of the system is also presented for performance analysis. METHODS: The second-generation system incorporates fast digitization of analog pulse waveforms, instantaneous pulse detection hardware, and a novel dual-buffering scheme. A mathematical model of the system was developed to theoretically compute the capture-rate performance. RESULTS: The capture rate of the system was theoretically analyzed and empirically measured. Under typical conditions, a capture rate of 8,000 pulses/s was experimentally achieved. CONCLUSIONS: Based on these results, the dual-buffer architecture shows great potential for use in flow cytometry.",
        annote = "Murthi, Shiva Sankaranarayanan, Sundararajan Xia, Bo Lambert, Georgina M Rodriguez, Jeffrey J Galbraith, David W Comparative Study United States Cytometry. Part A : the journal of the International Society for Analytical Cytology Cytometry A. 2005 Aug;66(2):109-18.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15973697"
}

@article{1663,
        author = "K. Nishikawa and T. Miyasaki and N. Tsukaguchi and Y. Noma and K. Nakagawa and N. Narita",
        title = "[CD45 gating of acute leukemia]",
        journal = "Rinsho Byori",
        pages = "548-53",
        volume = "44",
        number = "6",
        edition = "1996/06/01",
        year = "1996",
        month = "Jun",
        abstract = "Flow cytometry is a powerful tool for immunophenotyping of acute leukemia. Gating of leukemic cells is currently performed on the two dimensional display of forward scatter (FSC) and side scatter (SSC). However, this gating method can not discriminate leukemic cells from contaminated normal cells. Therefore, we used a CD45 monoclonal antibody to detect leukemic cells (CD45dlm cells) in combination with the SSC parameter. This CD45-SSC gating method was very useful for immunotyping of AML and ALL, especially leukemia with a low percentage of blasts. We recommend this new gating method for more accurate immunophenotyping of acute leukemia.",
        annote = "Nishikawa, K Miyasaki, T Tsukaguchi, N Noma, Y Nakagawa, K Narita, N Clinical Trial English Abstract Japan Rinsho byori. The Japanese journal of clinical pathology Rinsho Byori. 1996 Jun;44(6):548-53.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=8752733"
}

@article{Novo2008,
        author = "D. Novo and J. Wood",
        title = "Flow cytometry histograms: transformations, resolution, and display",
        journal = "Cytometry A",
        pages = "685-92",
        volume = "73",
        number = "8",
        edition = "2008/07/11",
        year = "2008",
        month = "Aug",
        abstract = "Flow cytometry data analysis routinely includes the use of one- or two-parameter histograms to visualize the data. These histograms have traditionally been plotted with either a linear or logarithmic scale. However, the recent trend of performing the logarithmic conversion in software has made apparent some limitations of the traditional visual presentation of logarithmic data. This review discusses the mathematics of presenting data on a histogram and emphasizes the difference between scaling and binning. The review introduces the concept of an effective resolution to describe how the bin width changes in a variable bin-width histogram. The change in effective resolution is used to explain the commonly observed valley and picket fencing artifacts. These result from the effective resolution of the display histogram being too high for the data being presented. Recently, several different binning transformations have been described that are becoming more popular because they allow one to view a large dynamic range of data on a single plot, while allowing the display of negative data values. While each of the transforms is based upon different equations, they all exhibit very similar properties. All of the transforms bin the data logarithmically at high channel values and linearly at low channel values. The linear scaling of the lower channels serves to limit the effective resolution of the histogram, thus minimizing the valley and picket fencing artifacts. The newer transformations are not without their own limitations and recommendations for the appropriate manner of presenting flow cytometry data using these newer transformations are discussed.",
        annote = "Novo, David Wood, James Review United States Cytometry. Part A : the journal of the International Society for Analytical Cytology Cytometry A. 2008 Aug;73(8):685-92.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18615596"
}

@article{Parks2006,
        author = "D. R. Parks and M. Roederer and W. A. Moore",
        title = {A new "Logicle" display method avoids deceptive effects of logarithmic scaling for low signals and compensated data},
        journal = "Cytometry A",
        pages = "541-51",
        volume = "69",
        number = "6",
        edition = "2006/04/11",
        year = "2006",
        month = "Jun",
        abstract = "BACKGROUND: In immunofluorescence measurements and most other flow cytometry applications, fluorescence signals of interest can range down to essentially zero. After fluorescence compensation, some cell populations will have low means and include events with negative data values. Logarithmic presentation has been very useful in providing informative displays of wide-ranging flow cytometry data, but it fails to adequately display cell populations with low means and high variances and, in particular, offers no way to include negative data values. This has led to a great deal of difficulty in interpreting and understanding flow cytometry data, has often resulted in incorrect delineation of cell populations, and has led many people to question the correctness of compensation computations that were, in fact, correct. RESULTS: We identified a set of criteria for creating data visualization methods that accommodate the scaling difficulties presented by flow cytometry data. On the basis of these, we developed a new data visualization method that provides important advantages over linear or logarithmic scaling for display of flow cytometry data, a scaling we refer to as \quote{Logicle} scaling. Logicle functions represent a particular generalization of the hyperbolic sine function with one more adjustable parameter than linear or logarithmic functions. Finally, we developed methods for objectively and automatically selecting an appropriate value for this parameter. CONCLUSIONS: The Logicle display method provides more complete, appropriate, and readily interpretable representations of data that includes populations with low-to-zero means, including distributions resulting from fluorescence compensation procedures, than can be produced using either logarithmic or linear displays. The method includes a specific algorithm for evaluating actual data distributions and deriving parameters of the Logicle scaling function appropriate for optimal display of that data. It is critical to note that Logicle visualization does not change the data values or the descriptive statistics computed from them.",
        annote = "Parks, David R Roederer, Mario Moore, Wayne A United States Cytometry. Part A : the journal of the International Society for Analytical Cytology Cytometry A. 2006 Jun;69(6):541-51.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16604519"
}

@book{118,
        author = "{R_Development_Core_Team}",
        title = "R: A Language and Environment for Statistical Computing",
        booktitle = "R: A Language and Environment for Statistical Computing",
        year = "2008",
        publisher = "R Foundation for Statistical Computing",
        isbn = "3-900051-07-0",
        howpublished = "Book",
        uri = "http://www.R-project.org"
}

@book{1300,
        author = "Brian D. Ripley",
        title = "Pattern recognition and neural networks",
        booktitle = "Pattern recognition and neural networks",
        year = "1996",
        publisher = "Cambridge University Press",
        annote = "95025223 B.D. Ripley. ill. ; 26 cm. Includes bibliographical references (p. [355]-390) and indexes.",
        uri = "http://www.loc.gov/catdir/description/cam027/95025223.html",
        uri = "http://www.loc.gov/catdir/toc/cam027/95025223.html",
        uri = "http://www.loc.gov/catdir/enhancements/fy0729/95025223-b.html"
}

@article{Roederer2001a,
        author = "M. Roederer and R. R. Hardy",
        title = "Frequency difference gating: a multivariate method for identifying subsets that differ between samples",
        journal = "Cytometry",
        pages = "56-64",
        volume = "45",
        number = "1",
        edition = "2001/10/13",
        year = "2001",
        month = "Sep 1",
        abstract = "BACKGROUND: In multivariate distributions (for example, in 3- or more color flow cytometric datasets), it can become difficult or impossible to identify populations that differ between samples based only on a combination of univariate or bivariate displays. Indeed, it is possible that such differences can only be identified in \quote{n}-dimensional space, where \quote{n} is the number of parameters measured. Therefore, computer assisted identification of such differences is necessary. Such a method could be used to identify responses (i.e., by comparing cell samples before and after stimulation) in exquisite detail by allowing complete analysis of the collected data on only those events which have responded. METHODS: Multivariate Probability Binning can be used to compare different datasets to identify the distance and statistical significance of a difference between the distributions. An intermediate step in the algorithm provides access to the actual locations within the n-dimensional comparison which are most different between the distributions. Gates based on collections of hyper-rectangular bins can then be applied to datasets, thereby selecting those events (or clusters of events) that are different between samples. We term this process Frequency Difference Gating. RESULTS: Frequency Difference Gating was used in several test scenarios to evaluate its utility. First, we compared PBMC subsets identified by solely by immunofluorescence staining: based on this training data set, the algorithm automatically generated an accurate forward and side-scatter gate to identify lymphocytes. Second, we applied the algorithm to identify subtle differences between CD4 memory subsets based on 8-color immunophenotyping data. The resulting 3-dimensional gate could resolve cells subsets much more frequent in one subset compared to the other; no combination of two-dimensional gates could accomplish this resolution. Finally, we used the algorithm to compare B cell populations derived from mice of different ages or strains, and found that the algorithm could find very subtle differences between the populations. CONCLUSION: Frequency Difference Gating is a powerful tool that automates the process of identifying events comprising underlying differences between samples. It is not a clustering tool; it is not meant to identify subsets in multidimensional space. Importantly, this method may reveal subtle changes in small populations of cells, changes that only occur simultaneously in multiple dimensions in such a way that identification by univariate or bivariate analyses is impossible. Finally, the method may significantly aid in the analysis of high-order multivariate data (i.e., 6-12 color flow cytometric analyses), where identification of differences between datasets becomes so time-consuming as to be impractical. Published 2001 Wiley-Liss, Inc.",
        annote = "Roederer, M Hardy, R R Comparative Study United States Cytometry Cytometry. 2001 Sep 1;45(1):56-64.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cm\Rpackage{flowFP}McCoyd=Retrieve&db=PubMed&dopt=Citation&list_uids=11598947"
}

@article{Roederer2001b,
        author = "M. Roederer and W. Moore and A. Treister and R. R. Hardy and L. A. Herzenberg",
        title = "Probability binning comparison: a metric for quantitating multivariate distribution differences",
        journal = "Cytometry",
        pages = "47-55",
        volume = "45",
        number = "1",
        edition = "2001/10/13",
        year = "2001",
        month = "Sep 1",
        abstract = "BACKGROUND: While several algorithms for the comparison of univariate distributions arising from flow cytometric analyses have been developed and studied for many years, algorithms for comparing multivariate distributions remain elusive. Such algorithms could be useful for comparing differences between samples based on several independent measurements, rather than differences based on any single measurement. It is conceivable that distributions could be completely distinct in multivariate space, but unresolvable in any combination of univariate histograms. Multivariate comparisons could also be useful for providing feedback about instrument stability, when only subtle changes in measurements are occurring. METHODS: We apply a variant of Probability Binning, described in the accompanying article, to multidimensional data. In this approach, hyper-rectangles of n dimensions (where n is the number of measurements being compared) comprise the bins used for the chi-squared statistic. These hyper-dimensional bins are constructed such that the control sample has the same number of events in each bin; the bins are then applied to the test samples for chi-squared calculations. RESULTS: Using a Monte-Carlo simulation, we determined the distribution of chi-squared values obtained by comparing sets of events from the same distribution; this distribution of chi-squared values was identical as for the univariate algorithm. Hence, the same formulae can be used to construct a metric, analogous to a t-score, that estimates the probability with which distributions are distinct. As for univariate comparisons, this metric scales with the difference between two distributions, and can be used to rank samples according to similarity to a control. We apply the algorithm to multivariate immunophenotyping data, and demonstrate that it can be used to discriminate distinct samples and to rank samples according to a biologically-meaningful difference. CONCLUSION: Probability binning, as shown here, provides a useful metric for determining the probability with which two or more multivariate distributions represent distinct sets of data. The metric can be used to identify the similarity or dissimilarity of samples. Finally, as demonstrated in the accompanying paper, the algorithm can be used to gate on events in one sample that are different from a control sample, even if those events cannot be distinguished on the basis of any combination of univariate or bivariate displays. Published 2001 Wiley-Liss, Inc.",
        annote = "Roederer, M Moore, W Treister, A Hardy, R R Herzenberg, L A Comparative Study United States Cytometry Cytometry. 2001 Sep 1;45(1):47-55.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11598946"
}

@article{Roederer2001c,
        author = "M. Roederer and A. Treister and W. Moore and L. A. Herzenberg",
        title = "Probability binning comparison: a metric for quantitating univariate distribution differences",
        journal = "Cytometry",
        pages = "37-46",
        volume = "45",
        number = "1",
        edition = "2001/10/13",
        year = "2001",
        month = "Sep 1",
        abstract = "BACKGROUND: Comparing distributions of data is an important goal in many applications. For example, determining whether two samples (e.g., a control and test sample) are statistically significantly different is useful to detect a response, or to provide feedback regarding instrument stability by detecting when collected data varies significantly over time. METHODS: We apply a variant of the chi-squared statistic to comparing univariate distributions. In this variant, a control distribution is divided such that an equal number of events fall into each of the divisions, or bins. This approach is thereby a mini-max algorithm, in that it minimizes the maximum expected variance for the control distribution. The control-derived bins are then applied to test sample distributions, and a normalized chi-squared value is computed. We term this algorithm Probability Binning. RESULTS: Using a Monte-Carlo simulation, we determined the distribution of chi-squared values obtained by comparing sets of events derived from the same distribution. Based on this distribution, we derive a conversion of any given chi-squared value into a metric that is analogous to a t-score, i.e., it can be used to estimate the probability that a test distribution is different from a control distribution. We demonstrate that this metric scales with the difference between two distributions, and can be used to rank samples according to similarity to a control. Finally, we demonstrate the applicability of this metric to ranking immunophenotyping distributions to suggest that it indeed can be used to objectively determine the relative distance of distributions compared to a single control. CONCLUSION: Probability Binning, as shown here, provides a useful metric for determining the probability that two or more flow cytometric data distributions are different. This metric can also be used to rank distributions to identify which are most similar or dissimilar. In addition, the algorithm can be used to quantitate contamination of even highly-overlapping populations. Finally, as demonstrated in an accompanying paper, Probability Binning can be used to gate on events that represent significantly different subsets from a control sample. Published 2001 Wiley-Liss, Inc.",
        annote = "Roederer, M Treister, A Moore, W Herzenberg, L A Comparative Study United States Cytometry Cytometry. 2001 Sep 1;45(1):37-46.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=11598945"
}

@article{Rogers2008,
        author = "W. T. Rogers and A. R. Moser and H. A. Holyst and A. Bantly and E. R. Mohler 3rd and G. Scangas and J. S. Moore",
        title = "Cytometric fingerprinting: quantitative characterization of multivariate distributions",
        journal = "Cytometry A",
        pages = "430-41",
        volume = "73",
        number = "5",
        edition = "2008/04/03",
        year = "2008",
        month = "may",
        abstract = "Recent technological advances in flow cytometry instrumentation provide the basis for high-dimensionality and high-throughput biological experimentation in a heterogeneous cellular context. Concomitant advances in scalable computational algorithms are necessary to better utilize the information that is contained in these high-complexity experiments. The development of such tools has the potential to expand the utility of flow cytometric analysis from a predominantly hypothesis-driven mode to one of discovery, or hypothesis-generating research. A new method of analysis of flow cytometric data called Cytometric Fingerprinting (CF) has been developed. CF captures the set of multivariate probability distribution functions corresponding to list-mode data and then \quote{flattens} them into a computationally efficient fingerprint representation that facilitates quantitative comparisons of samples. An experimental and synthetic data were generated to act as reference sets for evaluating CF. Without the introduction of prior knowledge, CF was able to \quote{discover} the location and concentration of spiked cells in ungated analyses over a concentration range covering four orders of magnitude, to a lower limit on the order of 10 spiked events in a background of 100,000 events. We describe a new method for quantitative analysis of list-mode cytometric data. CF includes a novel algorithm for space subdivision that improves estimation of the probability density function by dividing space into nonrectangular polytopes. Additionally it renders a multidimensional distribution in the form of a one-dimensional multiresolution hierarchical fingerprint that creates a computationally efficient representation of high dimensionality distribution functions. CF supports both the generation and testing of hypotheses, eliminates sources of operator bias, and provides an increased level of automation of data analysis.",
        annote = "Rogers, Wade T Moser, Allan R Holyst, Herbert A Bantly, Andrew Mohler, Emile R 3rd Scangas, George Moore, Jonni S Research Support, N.I.H., Extramural United States Cytometry. Part A : the journal of the International Society for Analytical Cytology Cytometry A. 2008 May;73(5):430-41.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18383310"
}

@article{106,
        author = "J. Spidlen and R. C. Leif and W. Moore and M. Roederer and R. R. Brinkman",
        title = "Gating-ML: XML-based gating descriptions in flow cytometry",
        journal = "Cytometry A",
        pages = "1151-7",
        volume = "73A",
        number = "12",
        edition = "2008/09/06",
        year = "2008",
        month = "Dec",
        abstract = "The lack of software interoperability with respect to gating due to lack of a standardized mechanism for data exchange has traditionally been a bottleneck, preventing reproducibility of flow cytometry (FCM) data analysis and the usage of multiple analytical tools. To facilitate interoperability among FCM data analysis tools, members of the International Society for the Advancement of Cytometry (ISAC) Data Standards Task Force (DSTF) have developed an XML-based mechanism to formally describe gates (Gating-ML). Gating-ML, an open specification for encoding gating, data transformations and compensation, has been adopted by the ISAC DSTF as a Candidate Recommendation. Gating-ML can facilitate exchange of gating descriptions the same way that FCS facilitated for exchange of raw FCM data. Its adoption will open new collaborative opportunities as well as possibilities for advanced analyses and methods development. The ISAC DSTF is satisfied that the standard addresses the requirements for a gating exchange standard.",
        annote = "Spidlen, Josef Leif, Robert C Moore, Wayne Roederer, Mario International Society for the Advancement of Cytometry Data Standards Task Force Brinkman, Ryan R EB005034/EB/NIBIB NIH HHS/United States Research Support, N.I.H., Extramural United States Cytometry. Part A : the journal of the International Society for Analytical Cytology Cytometry A. 2008 Dec;73A(12):1151-7.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18773465"
}

@article{1246,
        author = "G. {Te Kronnie} and S. Bicciato and G. Basso",
        title = "Acute leukemia subclassification: a marker protein expression perspective",
        journal = "Hematology",
        pages = "165-70",
        volume = "9",
        number = "3",
        edition = "2004/06/19",
        year = "2004",
        month = "Jun",
        abstract = "Improved leukemia classification and tailoring of therapy have greatly improved patient outcome particularly for children with acute leukemia (AL). Using immunophenotyping, molecular genetics and cytogenetics the low hanging fruits of biomedical research have been successfully incorporated in routine diagnosis of leukemia subclasses. Future improvements in the classification and understanding of leukemia biology will very likely be more slow and laborious. Recently, gene expression profiling has provided a framework for the global molecular analysis of hematological cancers, and high throughput proteomic analysis of leukemia samples is on the way. Here we consider classification of acute leukemia samples by flow cytometry using the marker proteins of immunophenotyping as a component of the proteome. Marker protein expressions are converted into quantitative expression values and subjected to computational analysis. Quantitative multivariate analysis from panels of marker proteins has demonstrated that marker protein expression profiles can distinguish MLLre from non-MLLre ALL cases and also allow to specifically distinguish MLL/AF4 cases. Potentially, these quantitative expression analyses can be used in clinical diagnosis. Immunophenotypic data collection using flow cytometry is a fast and relatively easily accessible technology that has already been implemented in most centers for leukemia diagnosis and the translation into quantitative expression data sets is a matter of flow cytometer settings and output calibration. However, before application in clinical diagnostics can occur it is crucial that quantitative immunophenotypic data set analysis is validated in independent experiments and in large data sets.",
        annote = "Te Kronnie, Geertruy Bicciato, Silvio Basso, Giuseppe Research Support, Non-U.S. Gov't Review England Hematology (Amsterdam, Netherlands) Hematology. 2004 Jun;9(3):165-70.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15204097"
}

@article{1232,
        author = "J. Toedling and P. Rhein and R. Ratei and L. Karawajew and R. Spang",
        title = "Automated in-silico detection of cell populations in flow cytometry readouts and its application to leukemia disease monitoring",
        journal = "BMC Bioinformatics",
        pages = "282",
        volume = "7",
        edition = "2006/06/07",
        year = "2006",
        abstract = "BACKGROUND: Identification of minor cell populations, e.g. leukemic blasts within blood samples, has become increasingly important in therapeutic disease monitoring. Modern flow cytometers enable researchers to reliably measure six and more variables, describing cellular size, granularity and expression of cell-surface and intracellular proteins, for thousands of cells per second. Currently, analysis of cytometry readouts relies on visual inspection and manual gating of one- or two-dimensional projections of the data. This procedure, however, is labor-intensive and misses potential characteristic patterns in higher dimensions. RESULTS: Leukemic samples from patients with acute lymphoblastic leukemia at initial diagnosis and during induction therapy have been investigated by 4-color flow cytometry. We have utilized multivariate classification techniques, Support Vector Machines (SVM), to automate leukemic cell detection in cytometry. Classifiers were built on conventionally diagnosed training data. We assessed the detection accuracy on independent test data and analyzed marker expression of incongruently classified cells. SVM classification can recover manually gated leukemic cells with 99.78% sensitivity and 98.87% specificity. CONCLUSION: Multivariate classification techniques allow for automating cell population detection in cytometry readouts for diagnostic purposes. They potentially reduce time, costs and arbitrariness associated with these procedures. Due to their multivariate classification rules, they also allow for the reliable detection of small cell populations.",
        annote = "Toedling, Joern Rhein, Peter Ratei, Richard Karawajew, Leonid Spang, Rainer Research Support, Non-U.S. Gov't England BMC bioinformatics BMC Bioinformatics. 2006 Jun 5;7:282.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16753055"
}

@article{Tung2004,
        author = "J. W. Tung and D. R. Parks and W. A. Moore and L. A. Herzenberg",
        title = "New approaches to fluorescence compensation and visualization of FACS data",
        journal = "Clin Immunol",
        pages = "277-83",
        volume = "110",
        number = "3",
        edition = "2004/03/30",
        year = "2004",
        month = "Mar",
        abstract = "The Fluorescence Activated Cell Sorter (FACS) is an invaluable tool for clinicians and researchers alike in phenotyping and sorting individual cells. With the advances in FACS methodology, notably intracellular staining for cytokines, transcription factors and phosphoproteins, and with increases in the number of fluorescence detection channels, researchers now have the opportunity to study individual cells in far greater detail than previously possible. In this chapter, we discuss High-Definition (Hi-D) FACS methods that can improve analysis of lymphocyte subsets in mouse and man. We focus on the reasons why fluorescence compensation, which is necessary to correct for spectral overlap between two or more fluorochromes used in the same staining combination, is best done as a computed transformation rather than using the analog circuitry available on many flow cytometers. In addition, we introduce a new data visualization method that scales the axes on histograms and two-dimensional contour (or dot) plots to enable visualization of signals from all cells, including those that have minimal fluorescence values and are not properly represented with traditional logarithmic axes. This \quote{Logicle} visualization method, we show, provides superior representations of compensated data and makes correctly compensated data look correct. Finally, we discuss controls that facilitate recognition of boundaries between positive and negative subsets.",
        annote = "Tung, James W Parks, David R Moore, Wayne A Herzenberg, Leonard A Herzenberg, Leonore A EB000231/EB/NIBIB NIH HHS/United States Research Support, U.S. Gov't, P.H.S. Review United States Clinical immunology (Orlando, Fla.) Clin Immunol. 2004 Mar;110(3):277-83.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15047205"
}

@article{1237,
        author = "G. Valet",
        title = "Cytomics, the human cytome project and systems biology: top-down resolution of the molecular biocomplexity of organisms by single cell analysis",
        journal = "Cell Prolif",
        pages = "171-4",
        volume = "38",
        number = "4",
        edition = "2005/08/16",
        year = "2005",
        month = "Aug",
        abstract = "A large amount of structural and functional information is obtained by molecular cell phenotype analysis of tissues, organs and organisms at the single cell level by image or flow cytometry in combination with bioinformatic knowledge extraction (cytomics) concerning nuclei acids, proteins and metabolites (cellular genomics, proteomics and metabolomics) as well as cell function parameters like intracellular pH, transmembrane potentials or ion gradients. In addition, differential molecular cell phenotypes between diseased and healthy cells provide molecular data patterns for (i) predictive medicine by cytomics or for (ii) drug discovery purposes using reverse engineering of the data patterns by biomedical cell systems biology. Molecular pathways can be explored in this way including the detection of suitable target molecules, without detailed a priori knowledge of specific disease mechanisms. This is useful during the analysis of complex diseases such as infections, allergies, rheumatoid diseases, diabetes or malignancies. The top-down approach reaching from single cell heterogeneity in cell systems and tissues down to the molecular level seems suitable for a human cytome project to systematically explore the molecular biocomplexity of human organisms. The analysis of already existing data from scientific studies or routine diagnostic procedures will be of immediate value in clinical medicine, for example as personalized therapy by cytomics.",
        annote = "Valet, G England Cell proliferation Cell Prolif. 2005 Aug;38(4):171-4.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=16098176"
}

@book{1298,
        author = "W. N. Venables and Brian D. Ripley",
        title = "Modern applied statistics with S",
        booktitle = "Modern applied statistics with S",
        series = "Statistics and computing",
        edition = "4th",
        year = "2002",
        publisher = "Springer",
        annote = "2002022925 (OCoLC)ocm49312402 W.N. Venables, B.D. Ripley. ill. ; 25 cm. Previously published as: Modern applied statistics with S-PLUS, c1999. Includes bibliographical references (p. 465-480) and index.",
        uri = "http://www.loc.gov/catdir/toc/fy042/2002022925.html",
        uri = "http://www.loc.gov/catdir/enhancements/fy0812/2002022925-d.html"
}

@article{1282,
        author = "E. Zamir and B. Geiger and N. Cohen and Z. Kam and B. Z. Katz",
        title = "Resolving and classifying haematopoietic bone-marrow cell populations by multi-dimensional analysis of flow-cytometry data",
        journal = "Br J Haematol",
        pages = "420-31",
        volume = "129",
        number = "3",
        edition = "2005/04/22",
        year = "2005",
        month = "may",
        abstract = "The study of normal or malignant haematopoiesis requires the analysis of heterogeneous cell populations using multiple morphological and molecular criteria. Flow cytometry has the capacity to acquire multi-parameter information of large haematopoietic cell populations, utilizing various combinations of >200 molecular markers (clusters of differentiation, CD). However, current flow cytometry analyses are based on serial gating of two-parametric scatter plots--a process that is inherently incapable to discriminate all subgroups of cells in the data. Here we studied the cellular diversity of normal bone marrows (BM) using multi-dimensional cluster analysis of six-parametric flow cytometry data (four CD, forward scatter and side scatter), focusing mainly on the myeloid lineage. Twenty-three subclasses of cells were resolved, many of them inseparable even when examined in all possible two-parametric scatter plots. The multi-dimensional analysis could distinguish the haematopoietic progenitors according to International Society of Haematotherapy and Graft Engineering criteria from other types of immature cells. Based on the defined clusters, we designed a classifier that assigns BM cells in samples to subclasses based on robust six-dimensional position and extended shape. The analysis presented here can manage successfully both the increasing numbers of haematopoietic cellular markers and sample heterogeneity. This should enhance the ability to study normal haematopoiesis, and to identify and monitor haematopoietic disorders.",
        annote = "Zamir, Eli Geiger, Benjamin Cohen, Nir Kam, Zvi Katz, Ben-Zion Research Support, Non-U.S. Gov't England British journal of haematology Br J Haematol. 2005 May;129(3):420-31.",
        uri = "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15842667"
}

