Literature DB >> 2340769

Data file standard for flow cytometry. Data File Standards Committee of the Society for Analytical Cytology.

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Abstract

This data file standard for flow cytometry (FCS) provides a detailed description of a data file structure designed such that the file can include all of the information necessary to describe fully: 1) the instrument used to obtain the data; 2) the sample measured; 3) the data obtained; and 4) the results of analysis of the data. The file may contain one or more data sets. Each data set includes data from a single sample or acquisition run. Each data set consists of a minimum of four parts--HEADER, TEXT, DATA, and ANALYSIS--all of which are required. The file is structured such that the parts of a data set do not have to be in any particular order, except for the HEADER, which must always be first. The HEADER contains pointers to the beginning and end of each of the other three parts. The file is written as a continuous byte stream, with no line or page formating. The HEADER, TEXT, and ANALYSIS parts are written in ASCII format and the DATA part can be written in ASCII, binary integer or floating point. This Standard, noted as FCS2.0, is based on a standard proposed by Murphy and Chused (Cytometry 5:553-555, 1984). Data written utilizing their proposed format (FCS1.0) is compatible with the format described here. Future versions of the standard will maintain compatibility with older versions.

Mesh:

Year:  1990        PMID: 2340769     DOI: 10.1002/cyto.990110303

Source DB:  PubMed          Journal:  Cytometry        ISSN: 0196-4763


  6 in total

1.  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

Review 2.  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

3.  Admixture mapping of an allele affecting interleukin 6 soluble receptor and interleukin 6 levels.

Authors:  David Reich; Nick Patterson; Vijaya Ramesh; Philip L De Jager; Gavin J McDonald; Arti Tandon; Edwin Choy; Donglei Hu; Bani Tamraz; Ludmila Pawlikowska; Christina Wassel-Fyr; Scott Huntsman; Alicja Waliszewska; Elizabeth Rossin; Rongling Li; Melissa Garcia; Alexander Reiner; Robert Ferrell; Steve Cummings; Pui-Yan Kwok; Tamara Harris; Joseph M Zmuda; Elad Ziv
Journal:  Am J Hum Genet       Date:  2007-03-08       Impact factor: 11.025

4.  FlowCal: A User-Friendly, Open Source Software Tool for Automatically Converting Flow Cytometry Data from Arbitrary to Calibrated Units.

Authors:  Sebastian M Castillo-Hair; John T Sexton; Brian P Landry; Evan J Olson; Oleg A Igoshin; Jeffrey J Tabor
Journal:  ACS Synth Biol       Date:  2016-05-12       Impact factor: 5.110

5.  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

6.  Multivariate analysis of flow cytometric data using decision trees.

Authors:  Svenja Simon; Reinhard Guthke; Thomas Kamradt; Oliver Frey
Journal:  Front Microbiol       Date:  2012-04-02       Impact factor: 5.640

  6 in total

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