Data File Standard for Flow Cytometry, VersionFCS3.2

被引:6
|
作者
Spidlen, Josef [1 ]
Moore, Wayne [2 ]
Parks, David [3 ]
Goldberg, Michael [4 ]
Blenman, Kim [5 ]
Cavenaugh, James S.
Brinkman, Ryan [6 ,7 ,8 ]
机构
[1] BD Life Sci FlowJo, Informat, Ashland, OR USA
[2] Stanford Univ, Sch Med, Genet Dept, Stanford, CA 94305 USA
[3] Stanford Univ, Stanford Shared FACS Facil, Stanford, CA 94305 USA
[4] BD Biosci, San Jose, CA USA
[5] Yale Sch Med, New Haven, CT USA
[6] BC Canc Agcy, Terry Fox Lab, Vancouver, BC, Canada
[7] Univ British Columbia, Dept Med Genet, Vancouver, BC, Canada
[8] Cytapex Bioinformat Inc, Vancouver, BC, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
flow cytometry; FCS; 3; 2; data standard; file format; bioinformatics;
D O I
10.1002/cyto.a.24225
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
FCS 3.2 is a revision of the flow cytometry data standard based on a decade of suggested improvements from the community as well as industry needs to capture instrument conditions and measurement features more precisely. 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 standard retains the overall FCS file structure and most features of previous versions, but also contains a few changes that were required to support new types of data and use cases efficiently. These changes are incompatible with existing FCS file readers. Notably, FCS 3.2 supports mixed data types to, for example, allow FCS measurements that are intrinsically integers (e.g., indices or class assignments) or measurements that are commonly captured as integers (e.g., time ticks) to be more represented as integer values, while capturing other measurements as floating-point values in the same FCS data set. In addition, keywords explicitly specifying dyes, detectors, and analytes were added to avoid having to extract those heuristically and unreliably from measurement names. Types of measurements were formalized, several keywords added, others removed, or deprecated, and various aspects of the specification were clarified. A reference implementation of the cyclic redundancy check (CRC) calculation is provided in two programming languages since a correct CRC implementation was problematic for many vendors. (c) 2020 International Society for Advancement of Cytometry
引用
收藏
页码:100 / 102
页数:3
相关论文
共 50 条
  • [1] Data File Standard for Flow Cytometry, Version FCS 3.1
    Spidlen, Josef
    Moore, Wayne
    Parks, David
    Goldberg, Michael
    Bray, Chris
    Bierre, Pierre
    Gorombey, Peter
    Hyun, Bill
    Hubbard, Mark
    Lange, Simon
    Lefebvre, Ray
    Leif, Robert
    Novo, David
    Ostruszka, Leo
    Treister, Adam
    Wood, James
    Murphy, Robert E.
    Roederer, Mario
    Sudar, Damir
    Zigon, Robert
    Brinkman, Ryan R.
    CYTOMETRY PART A, 2010, 77A (01) : 97 - 100
  • [2] Proposed new data file standard for flow cytometry, version FCS 3.0
    Seamer, LC
    Bagwell, CB
    Barden, L
    Redelman, D
    Salzman, GC
    Wood, JCS
    Murphy, RF
    CYTOMETRY, 1997, 28 (02): : 118 - 122
  • [3] Statistical file matching of flow cytometry data
    Lee, Gyemin
    Finn, William
    Scott, Clayton
    JOURNAL OF BIOMEDICAL INFORMATICS, 2011, 44 (04) : 663 - 676
  • [4] flowIO: Flow cytometry standard conformance testing, editing, and export tool
    Koblizek, Miroslav
    Lebedeva, Anastasia
    Fiser, Karel
    CYTOMETRY PART A, 2018, 93A (08) : 848 - 853
  • [5] Fully Automatic Classification of Flow Cytometry Data
    Piotrowski, Bartosz Pawel
    Kursa, Miron Bartosz
    FOUNDATIONS OF INTELLIGENT SYSTEMS (ISMIS 2018), 2018, 11177 : 3 - 12
  • [6] Flow cytometry data standards
    Spidlen J.
    Shooshtari P.
    Kollmann T.R.
    Brinkman R.R.
    BMC Research Notes, 4 (1)
  • [7] Flow Cytometry Data Analysis
    Yildiz, Eyyup
    Ensari, Tolga
    Sener, Leyla Turker
    2020 28TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2020,
  • [8] BCyto: A shiny app for flow cytometry data analysis
    Bonilha, Caio Santos
    MOLECULAR AND CELLULAR PROBES, 2022, 65
  • [9] flowSim: Near duplicate detection for flow cytometry data
    Montante, Sebastiano
    Chen, Yixuan
    Brinkman, Ryan R.
    CYTOMETRY PART A, 2023, 103 (11) : 889 - 901
  • [10] Rapid Cell Population Identification in Flow Cytometry Data
    Aghaeepour, Nima
    Nikolic, Radina
    Hoos, Holger H.
    Brinkman, Ryan R.
    CYTOMETRY PART A, 2011, 79A (01) : 6 - 13