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Publications and Presentations

Verity Software House has a rich heritage of research publications in the field of flow cytometry. This page lists some of the publications to which Verity has contributed. Where possible, we have provided links to the periodicals listed.

We also produce white papers and lecture notes on a broad range of topics in flow cytometry. These are available directly from this site.

Papers, Presentations and Posters

Sometimes Simpler Is Better: VLog, a General but Easy-to-Implement Log-Like Transform for Cytometry Bagwell and company introduce a new transform that improves on HyperLog, Logicle, and Hyperbolic Sine.
Impaired Subset Progression and Polyfunctionality of T Cells in Mice Exposed to Methamphetamine during Chronic LCMV Infection Sriram, Hill, Cenna, Gofman, Fernandes, Haldar, and Potula make extensive use of GemStone and its TriCom tool to examine impairments related to methamphetamine exposure in mice.
High-Dimensional Modeling of Peripheral Blood Mononuclear Cells from a Helios Instrument Bagwell, Leipold, Maecker, and Stelzer explore 48 correlated measurements from a Helios instrument, revealing new relationships and cell type characteristics.
Sometimes Simpler Is Better: VLog, An Easy-to-Implement Log-Like Transform for Cytometry Bagwell and others report on a new transformation for flow cytometry data: VLog.
CD34+ Stem Cell Enumeration with T-Cell Evaluation: A comparison between manual and automated analysis methods Alrazzak, Wallace, and others evaluate manual ISHAGE analysis and automated analysis with GemStone at Roswell Park Cancer Institute
Probability state modeling theory Bagwell and others explain the theory of probability state modeling and how it is well-suited for high-dimensional, objective, and automated analysis of flow data. Cytometry Part A, 2015
Human B-cell and progenitor stages as determined by probability state modeling of multidimensional cytometry data Bagwell, Hill, Wood, Wallace, Alrazzak, Kelliher, and Preffer investigate the underlying coordination of cell-surface and intracytoplasmic antigen expression for B-cells using Probablility State Modeling. Cytometry Part B, 2015
Human B-Cell and Progenitor Stages as Determined by Probability State Modeling of Multidimensional Cytometry Data Bagwell, Hill, Wood, Wallace, Kelliher and Prefer use probability state modeling to examine human B-Cell progression. Poster for ICCS 2014.
Automating Software Compensation for Fluorescence Spillover Hunsberger, Hawley, Wallace, Bantly, Theorell, Greig, Donahue, and Bagwell examine V-Comp™, a fully-automated compensation system. Poster for Cyto 2014.
A GemStone™ Workshop on Probability State Modeling of CD3+ Cells from CyTOF-Derived Data Bagwell, Hill, Hunsberger, et al, peel apart 39-parameter CyTOF™ data with GemStone™, with staging and activation markers. Poster for Cyto 2014.
Modeling Peripheral Blood B cells with GemStone™ and 39-Parameter CyTOF Data Hill, Bagwell, Leipold, and Maecker explore B-Cells with 39-parameter CyTOF™ data using GemStone™. Poster for Cyto 2014.
Probability state modeling of memory CD8+ T-cell differentiation.
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Inokuma, Maino, and Bagwell explore the world of CD8 T-cells with GemStone™ and Probablilty State Modeling. Journal of Immunological Methods 2013.
Automated quantitation of fetomaternal hemorrhage by flow cytometry for HbF-containing fetal red blood cells using probability state modeling.
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Wong, Hunsberger, Bagwell, and Davis demonstrate the use of GemStone™ Probablilty State Modeling for detection of fetal maternal hemorrhage. International Journal of Laboratory Hematology 2013.
Automated analysis of GPI-deficient leukocyte flow cytometric data using GemStone™. Miller, Hunsberger, and Bagwell present a study that uses a hands-off automated approach to analysis of PNH cases, using a modeling system built on GemStone. Cytometry Part B 2012.
Automated analysis of flow cytometric data for CD34+ stem cell enumeration using a probability state model. Herbert, Miller, and Bagwell describe their study to analyze CD34+ stem cells in an automated approach based on GemStone. Cytometry Part B 2012.
Modeling of DNA Content, GLIIFCA 2011 Bruce Bagwell explains some recent improvements in GemStone modeling that radically improve analysis of continuums. Presented at the 2011 GLIIFCA meeting.
Modeling Kinetic Processes Without the Benefit of Time as a Measurement This is Bruce Bagwell's talk on kinetic processes, in which he shares an imaginary conversation with Mack Fulwyler. Presented at the 2011 Research Course in Flow Cytometry in Albuquerque, NM, USA.
Visualization of CD4 T-cell memory and effector differentiation using GemStone GemStone's overlay plots and TriCOM displays are integral to this study by Inokuma, Trotter, et al. CD4 T-Cells are examined in great detail. Presented at the CYTO 2011 conference in Baltimore, MD, USA.
Automated Detection of GPI-deficiency in Paroxysmal Nocturnal Hemoglobinuria (PNH) This poster by Hunsberger and Miller describes PNH analysis using a completely automated modeling approach with GemStone. Presented at the CYTO 2011 conference in Baltimore, MD, USA.
Using GemStone in the Routine Analysis of Clinical Stem Cell Listmode Data This poster by Grieg, Miller, and Herbert describes an automated CD34 enumeration assay using GemStone. Presented at the CYTO 2011 conference in Baltimore, MD, USA.
Automated Modeling of Human B-Cell Progressions In Bone Marrow and Detection of Minimum Residual Disease This poster by Bagwell, Stewart, Wood, and Preffer explores automated modeling of B-Cell progressions using GemStone. Presented at the CYTO 2011 conference in Baltimore, MD, USA.
Comparison of DNA Analysis Using Probability State Modeling and Non-Linear Least Squares Modeling This poster by Bray and Baldetorp compares DNA analysis by ModFit and GemStone. Presented at the CYTO 2011 conference in Baltimore, MD, USA.
The Cytometry Game: Past and Future Bruce Bagwell's lecture compares cytometry analysis and Sudoku as he explores our past and future approaches. Presented at several locations in 2010.
A Novel Modeling System for Analysis of High Dimensional data: Definition of T-cell Effector and Memory Subsets Using GemStone Software This poster by Inokuma, Trotter, et al, explores the use of GemStone for analyzing high-dimensional T-Cell data. Presented at the CYTO 2010 conference in Seattle, WA, USA.
Improved algorithms for the analysis and classification of HbF-containing Red Blood Cells This poster by Davis, Hunsberger, et al, compares traditional analysis approaches with GemStone analysis for Fetal Maternal Hemorrhage. Presented at the CYTO 2010 conference in Seattle, WA, USA.
Multi-parametric Cell Cycle Analysis: A comparison of transition state-related cluster and probability state analyses This poster by Bray, Bagwell, et al, compares GemStone state analysis with a gate-based analysis of DNA, cyclins A2 and B1, and phospho-S10-histone H3. Presented at the CYTO 2010 conference in Seattle, WA, USA.
Probability State Modeling Analysis of CD38, CD10, and CD19 Up-regulation in Early Human B-Cell Development In this poster by Bagwell, Stewart, et al, Probability State Modeling was used to determine the relative order of CD38, CD19, and CD10 up-regulation for a number of uninvolved bone marrow specimens. Presented at the CYTO 2010 conference in Seattle, WA, USA.


White Papers, Lectures, Pre-prints

High dimensional flow cytometry for comprehensive leukocyte immunophenotyping (CLIP) in translational research Angélique Biancotto, John Fuchs, Ann Williams, Pradeep Dagur, and Philip McCoy Jr explore new paradigms for the assessment of comprehensive leukocyte immunophenotyping (CLIP).
Polychromatic flow cytometry: A rapid method for the reduction and analysis of complex multiparameter data This paper by Petrausch, Haley, et al, describes a powerful multiparameter analysis approach using WinList's FCOM function to reduce greatly the complexity of analyzing high-dimensional data.
HyperLogTM - A Flexible Log-like Transform for Negative, Zero, and Positive Valued Data Pre-print of a peer-reviewed article in Cytometry 2005, focused on ways to display data for flow cytometry.
A Journey Through Flow Cytometric Immunofluorescence Analysis Pre-print of article by C. Bruce Bagwell from Clinical Immunology Newsletter, Vol 16, Number 3, 1996
Super Enhanced D-Value The mathematics behind the Super Enhanced D-Value (SED) calculation.
Using FCOM for Subset Analysis Explains this easy-to-use WinList feature
Enhanced Proliferation Analysis Integrates WinList and ModFit LT
Effects of Resolution Reduction on Data Analysis Pre-print of a peer-reviewed article in Cytometry 2003, describing a new resolution reduction algorithm
Linear to Log Data Conversions Explores linear-to-log data conversions in WinList
Examination of DNA Guidelines Examines several critical criteria for DNA analysis


A Sampling of Peer-Reviewed Publications

Contact us for a more complete listing.

Multiparameter DNA content analysis identifies distinct groups in primary breast cancer. Dayal, Sales, Cover, et al.
British Cancer Journal 2013

Automated analysis of GPI-deficient leukocyte flow cytometric data using GemStone™. Miller, Hunsberger, and Bagwell.
Cytometry Part B 2012

Automated analysis of flow cytometric data for CD34+ stem cell enumeration using a probability state model. Herbert, Miller, and Bagwell.
Cytometry Part B 2012

A deep profiler's guide to cytometry. Bendall, Nolan, Roederer, Chattopadhyay.
Trends in Immunology V33 issue 7, 2012

Cervical carcinoma-associated fibroblasts are DNA diploid and do not show evidence for somatic genetic alterations, Willem Ernst Corver et al,
Cellular Oncology, 2011.

DNA/Cell Cycle Analysis As Prognostic Indicators in Breast Tumors Revisited, 
Clinics in Laboratory Medicine, 2001.

Optimizing Flow Cytometric DNA Ploidy and S-Phase Fraction 
as Independent Prognostic Markers for Node-Negative Breast Cancer Specimens,
Communications in Clinical Cytometry, Vol 46:3, pps 121-135, 2001.

Data File Standard for Flow Cytometry, Version FCS3.0,
Cytometry Originally in 1990 ;11(3):323-32, Version 3.0 in 1996.

Fetal RBC detection,
Laboratory Hematology 2:49, 1996.

Flow cytometric detection of fetal hemoglobin (Hb F) containing red blood cells,
International Journal of Hematology 64:S157, 1996.

A Journey through Flow Cytometric Immunofluorescence Analyses - 
Finding Accurate and Robust Algorithms that Estimate Positive Fraction Distributions, 
Clinical Immunology Newsletter, Vol. 16, No. 3, 1996.

A new homogeneous assay system for specific nucleic acid sequences: poly-dA and poly-A detection, 
Nucleic Acids Research, Vol: 22, No. 12, 242-2425, 1994.

Guidelines for implementation of clinical DNA cytometry, 
Cytometry, 14(5):472-7, 1993.

Software Spectral Overlap Compensation For Any Number of Flow Cytometry Parameters, 
New York Academy of Sciences, .20(677):167-84,1993.

Parathyroid carcinoma: the relationship of nuclear DNA content to clinical outcome,
Surgery, 113(3):290-6, 1993.

DNA signal splitting improves detection and analysis of tetraploid populations,
Cytometry, 13(7):787-9, 1992.

DNA Histogram Debris Theory and Compensation,
Cytometry. 12:107-118, 1991.



The HyperLog™ Transformation for Compensated Data
Presented at the 28th Annual Course in Flow Cytometry, Los Alamos, NM, USA
June, 2005

Displaying Flow Data
Presented at the Clinical Flow Cytometry Course, XVII, Pittsburgh, Pennsylvania, USA
September, 2004

Compensation Basics
Presented at ISAC XXII Congress, Montpellier, France, 
May, 2004

Breast CA Prognosis 
Presented at 27th Annual Course in Flow Cytometry, Bowdoin College, Maine, USA
June, 2004

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