Data File Standard for Flow Cytometry, version FCS 3.1

Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada.
Cytometry Part A (Impact Factor: 2.93). 01/2009; 77(1):97-100. DOI: 10.1002/cyto.a.20825
Source: PubMed


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 in the Current standards section) for a complete list of changes.

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    • "The latest version, FCS 3.1, was introduced in 2010 [59]. It retains the basic FCS file structure and most features of previous versions of the standard. "
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    • "The flowPhyto package is compatible with conventional Flow Cytometry Standard (FCS) files (Spidlen et al., 2010), as well as those from the SeaFlow repository. SeaFlow data are stored in a custom binary file (EVT file) created every 3 min and consists of eight 16-bit integer channels (see Ribalet et al., 2010 for more details). "
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    Full-text · Article · Mar 2011 · Bioinformatics
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    • "These values are stored in the Flow Cytometry Standard (FCS) data file format developed by ISAC in 1984 and it is still the common representation of FCM data supported by all instruments and FCM data analysis tools [1]. FCS was recently extended to version 3.1 [2], correcting some ambiguities, improving support for international characters and storing compensation, and adding support for preferred display scale, sample volume, tracking originality of data files and plate and well identification. "
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    ABSTRACT: Flow cytometry is a widely used analytical technique for examining microscopic particles, such as cells. The Flow Cytometry Standard (FCS) was developed in 1984 for storing flow data and it is supported by all instrument and third party software vendors. However, FCS does not capture the full scope of flow cytometry (FCM)-related data and metadata, and data standards have recently been developed to address this shortcoming. The Data Standards Task Force (DSTF) of the International Society for the Advancement of Cytometry (ISAC) has developed several data standards to complement the raw data encoded in FCS files. Efforts started with the Minimum Information about a Flow Cytometry Experiment, a minimal data reporting standard of details necessary to include when publishing FCM experiments to facilitate third party understanding. MIFlowCyt is now being recommended to authors by publishers as part of manuscript submission, and manuscripts are being checked by reviewers and editors for compliance. Gating-ML was then introduced to capture gating descriptions - an essential part of FCM data analysis describing the selection of cell populations of interest. The Classification Results File Format was developed to accommodate results of the gating process, mostly within the context of automated clustering. Additionally, the Archival Cytometry Standard bundles data with all the other components describing experiments. Here, we introduce these recent standards and provide the very first example of how they can be used to report FCM data including analysis and results in a standardized, computationally exchangeable form. Reporting standards and open file formats are essential for scientific collaboration and independent validation. The recently developed FCM data standards are now being incorporated into third party software tools and data repositories, which will ultimately facilitate understanding and data reuse.
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