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      Extracting a Cellular Hierarchy from High-dimensional Cytometry Data with SPADE

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          Abstract

          Multiparametric single-cell analysis is critical for understanding cellular heterogeneity. Despite recent technological advances in single-cell measurements, methods for analyzing high-dimensional single-cell data are often subjective, labor intensive and require prior knowledge of the biological system under investigation. To objectively uncover cellular heterogeneity from single-cell measurements, we present a novel computational approach, Spanning-tree Progression Analysis of Density-normalized Events (SPADE). We applied SPADE to cytometry data of mouse and human bone marrow. In both cases, SPADE organized cells in a hierarchy of related phenotypes that partially recapitulated well-described patterns of hematopoiesis. In addition, SPADE produced a map of intracellular signal activation across the landscape of human hematopoietic development. SPADE revealed a functionally distinct cell population, natural killer (NK) cells, without using any NK-specific parameters. SPADE is a versatile method that facilitates the analysis of cellular heterogeneity, the identification of cell types, and comparison of functional markers in response to perturbations.

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          Most cited references18

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          Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry.

          A novel instrument for real time analysis of individual biological cells or other microparticles is described. The instrument is based on inductively coupled plasma time-of-flight mass spectrometry and comprises a three-aperture plasma-vacuum interface, a dc quadrupole turning optics for decoupling ions from neutral components, an rf quadrupole ion guide discriminating against low-mass dominant plasma ions, a point-to-parallel focusing dc quadrupole doublet, an orthogonal acceleration reflectron analyzer, a discrete dynode fast ion detector, and an 8-bit 1 GHz digitizer. A high spectrum generation frequency of 76.8 kHz provides capability for collecting multiple spectra from each particle-induced transient ion cloud, typically of 200-300 micros duration. It is shown that the transients can be resolved and characterized individually at a peak frequency of 1100 particles per second. Design considerations and optimization data are presented. The figures of merit of the instrument are measured under standard inductively coupled plasma (ICP) operating conditions ( 900 for m/z = 159, the sensitivity with a standard sample introduction system of >1.4 x 10(8) ion counts per second per mg L(-1) of Tb and an abundance sensitivity of (6 x 10(-4))-(1.4 x 10(-3)) (trailing and leading masses, respectively) are shown. The mass range (m/z = 125-215) and abundance sensitivity are sufficient for elemental immunoassay with up to 60 distinct available elemental tags. When 500) can be used, which provides >2.4 x 10(8) cps per mg L(-1) of Tb, at (1.5 x 10(-3))-(5.0 x 10(-3)) abundance sensitivity. The real-time simultaneous detection of multiple isotopes from individual 1.8 microm polystyrene beads labeled with lanthanides is shown. A real time single cell 20 antigen expression assay of model cell lines and leukemia patient samples immuno-labeled with lanthanide-tagged antibodies is presented.
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            Web-based analysis and publication of flow cytometry experiments.

            Cytobank is a Web-based application for storage, analysis, and sharing of flow cytometry experiments. Researchers use a Web browser to log in and use a wide range of tools developed for basic and advanced flow cytometry. In addition to providing access to standard cytometry tools from any computer, Cytobank creates a platform and community for developing new analysis and publication tools. Figure layouts created on Cytobank are designed to allow transparent access to the underlying experiment annotation and data processing steps. Since all flow cytometry files and analysis data are stored on a central server, experiments and figures can be viewed or edited by anyone with the proper permission, from any computer with Internet access. Once a primary researcher has performed the initial analysis of the data, collaborators can engage in experiment analysis and make their own figure layouts using the gated, compensated experiment files. Cytobank is available to the scientific community at http://www.cytobank.org. (c) 2010 by John Wiley & Sons, Inc.
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              Interpreting flow cytometry data: a guide for the perplexed.

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                Author and article information

                Journal
                9604648
                20305
                Nat Biotechnol
                Nature biotechnology
                1087-0156
                1546-1696
                9 September 2011
                2 October 2011
                2 April 2012
                : 29
                : 10
                : 886-891
                Affiliations
                [1 ]Department of Radiology, Stanford University, Stanford, CA
                [2 ]Department of Microbiology and Immunology, Stanford University, Stanford, CA
                [3 ]Computer Systems Laboratory, Stanford University, Stanford, CA
                [4 ]Department of Bioinformatics and Computational Biology, University of Texas, M.D. Anderson Cancer Center, Houston, TX
                Author notes
                [* ]To whom correspondence can be addressed - pqiu@ 123456mdanderson.org
                Article
                nihpa321951
                10.1038/nbt.1991
                3196363
                21964415
                d3054416-c7b7-46a1-acb7-9a60db8d27cc

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                History
                Funding
                Funded by: National Cancer Institute : NCI
                Award ID: R01 CA130826-04 || CA
                Categories
                Article

                Biotechnology
                Biotechnology

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