Literature DB >> 19937951

Data File Standard for Flow Cytometry, version FCS 3.1.

Josef Spidlen1, Wayne Moore, David Parks, Michael Goldberg, Chris Bray, Pierre Bierre, Peter Gorombey, Bill Hyun, Mark Hubbard, Simon Lange, Ray Lefebvre, Robert Leif, David Novo, Leo Ostruszka, Adam Treister, James Wood, Robert F Murphy, Mario Roederer, Damir Sudar, Robert Zigon, Ryan R Brinkman.   

Abstract

The flow cytometry data file standard provides the specifications needed to completely describe flow cytometry data sets within the confines of the file containing the experimental data. In 1984, the first Flow Cytometry Standard format for data files was adopted as FCS 1.0. This standard was modified in 1990 as FCS 2.0 and again in 1997 as FCS 3.0. We report here on the next generation flow cytometry standard data file format. FCS 3.1 is a minor revision based on suggested improvements from the community. The unchanged goal of the standard is to provide a uniform file format that allows files created by one type of acquisition hardware and software to be analyzed by any other type.The FCS 3.1 standard retains the basic FCS file structure and most features of previous versions of the standard. Changes included in FCS 3.1 address potential ambiguities in the previous versions and provide a more robust standard. The major changes include simplified support for international characters and improved support for storing compensation. The major additions are support for preferred display scale, a standardized way of capturing the sample volume, information about originality of the data file, and support for plate and well identification in high throughput, plate based experiments. Please see the normative version of the FCS 3.1 specification in Supporting Information for this manuscript (or at http://www.isac-net.org/ in the Current standards section) for a complete list of changes.

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Year:  2010        PMID: 19937951      PMCID: PMC2892967          DOI: 10.1002/cyto.a.20825

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.355


  4 in total

1.  MIFlowCyt: the minimum information about a Flow Cytometry Experiment.

Authors:  Jamie A Lee; Josef Spidlen; Keith Boyce; Jennifer Cai; Nicholas Crosbie; Mark Dalphin; Jeff Furlong; Maura Gasparetto; Michael Goldberg; Elizabeth M Goralczyk; Bill Hyun; Kirstin Jansen; Tobias Kollmann; Megan Kong; Robert Leif; Shannon McWeeney; Thomas D Moloshok; Wayne Moore; Garry Nolan; John Nolan; Janko Nikolich-Zugich; David Parrish; Barclay Purcell; Yu Qian; Biruntha Selvaraj; Clayton Smith; Olga Tchuvatkina; Anne Wertheimer; Peter Wilkinson; Christopher Wilson; James Wood; Robert Zigon; Richard H Scheuermann; Ryan R Brinkman
Journal:  Cytometry A       Date:  2008-10       Impact factor: 4.355

2.  Proposed new data file standard for flow cytometry, version FCS 3.0.

Authors:  L C Seamer; C B Bagwell; L Barden; D Redelman; G C Salzman; J C Wood; R F Murphy
Journal:  Cytometry       Date:  1997-06-01

3.  A proposal for a flow cytometric data file standard.

Authors:  R F Murphy; T M Chused
Journal:  Cytometry       Date:  1984-09

4.  Gating-ML: XML-based gating descriptions in flow cytometry.

Authors:  Josef Spidlen; Robert C Leif; Wayne Moore; Mario Roederer; Ryan R Brinkman
Journal:  Cytometry A       Date:  2008-12       Impact factor: 4.355

  4 in total
  22 in total

1.  FCS 3.1 Implementation guidance.

Authors:  Chris Bray; Josef Spidlen; Ryan R Brinkman
Journal:  Cytometry A       Date:  2012-01-25       Impact factor: 4.355

2.  ISAC's Gating-ML 2.0 data exchange standard for gating description.

Authors:  Josef Spidlen; Wayne Moore; Ryan R Brinkman
Journal:  Cytometry A       Date:  2015-05-14       Impact factor: 4.355

3.  Methods for discovery and characterization of cell subsets in high dimensional mass cytometry data.

Authors:  Kirsten E Diggins; P Brent Ferrell; Jonathan M Irish
Journal:  Methods       Date:  2015-05-13       Impact factor: 3.608

Review 4.  Computational flow cytometry: helping to make sense of high-dimensional immunology data.

Authors:  Yvan Saeys; Sofie Van Gassen; Bart N Lambrecht
Journal:  Nat Rev Immunol       Date:  2016-06-20       Impact factor: 53.106

5.  ISAC's classification results file format.

Authors:  Josef Spidlen; Chris Bray; Ryan R Brinkman
Journal:  Cytometry A       Date:  2014-11-18       Impact factor: 4.355

6.  CytoML for cross-platform cytometry data sharing.

Authors:  Greg Finak; Wenxin Jiang; Raphael Gottardo
Journal:  Cytometry A       Date:  2018-12       Impact factor: 4.355

Review 7.  Computational analysis of high-throughput flow cytometry data.

Authors:  J Paul Robinson; Bartek Rajwa; Valery Patsekin; Vincent Jo Davisson
Journal:  Expert Opin Drug Discov       Date:  2012-06-18       Impact factor: 6.098

Review 8.  Recommendations from the iSBTc-SITC/FDA/NCI Workshop on Immunotherapy Biomarkers.

Authors:  Lisa H Butterfield; A Karolina Palucka; Cedrik M Britten; Madhav V Dhodapkar; Leif Håkansson; Sylvia Janetzki; Yutaka Kawakami; Thomas-Oliver Kleen; Peter P Lee; Cristina Maccalli; Holden T Maecker; Vernon C Maino; Michele Maio; Anatoli Malyguine; Giuseppe Masucci; Graham Pawelec; Douglas M Potter; Licia Rivoltini; Lupe G Salazar; Dolores J Schendel; Craig L Slingluff; Wenru Song; David F Stroncek; Hideaki Tahara; Magdalena Thurin; Giorgio Trinchieri; Sjoerd H van Der Burg; Theresa L Whiteside; Jon M Wigginton; Francesco Marincola; Samir Khleif; Bernard A Fox; Mary L Disis
Journal:  Clin Cancer Res       Date:  2011-05-10       Impact factor: 12.531

9.  Flow cytometry data standards.

Authors:  Josef Spidlen; Parisa Shooshtari; Tobias R Kollmann; Ryan R Brinkman
Journal:  BMC Res Notes       Date:  2011-03-07

10.  Data File Standard for Flow Cytometry, Version FCS 3.2.

Authors:  Wayne Moore; David Parks; Josef Spidlen; Michael Goldberg; Kim Blenman; James S Cavenaugh; Ryan Brinkman
Journal:  Cytometry A       Date:  2020-09-16       Impact factor: 4.355

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