standards > model/format > DOI:10.25504/FAIRsharing.qrr33y
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ready Flow Cytometry Data File Standard

Abbreviation: FCS


General Information
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.



How to cite this record FAIRsharing.org: FCS; Flow Cytometry Data File Standard; DOI: https://doi.org/10.25504/FAIRsharing.qrr33y; Last edited: Jan. 8, 2019, 1:35 p.m.; Last accessed: Jul 31 2021 12:23 p.m.


Record updated: Nov. 28, 2016, 12:18 p.m. by The FAIRsharing Team.

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General

Additional Information


Tools

    No tools defined


Schemas

No XSD schemas defined


Access / Retrieve Data

Conditions of Use





Publications

Data File Standard for Flow Cytometry, version FCS 3.1.

Spidlen J, Moore W, Parks D, Goldberg M, Bray C, Bierre P, Gorombey P, Hyun B, Hubbard M, Lange S, Lefebvre R, Leif R, Novo D, Ostruszka L, Treister A, Wood J, Murphy RF, Roederer M, Sudar D, Zigon R, Brinkman RR
Cytometry A 2010

View Paper (PubMed) View Publication

Related Standards

Reporting Guidelines

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Terminology Artifacts

No semantic standards defined

Models and Formats

No syntax standards defined

Identifier Schemas

No identifier schema standards defined

Metrics

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Related Databases (2)
FlowRepository
FlowRepository is a database of flow cytometry experiments where you can query and download data collected and annotated according to the MIFlowCyt standard. Data are generally associated with peer reviewed manuscripts.

Immunology Database and Analysis Portal
The Immunology Database and Analysis Portal (ImmPort) data repository was created for the exploration of clinical and basic research data on immunology and associated findings. ImmPort intends to promote effective data sharing across the basic, clinical and translational research communities. It collects data both from clinical and mechanistic studies on human subjects and from immunology studies on model organisms. The ImmPort ecosystem consists of four components: private data, shared data, data analysis, and resources-for data archiving, dissemination, analyses, and reuse.

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